Module Manual

Bachelor

Technomathematics

Cohort: Winter Term 2018

Updated: 28th September 2018

Program description

Content

Core qualification

Module M0575: Procedural Programming

Courses
Title Typ Hrs/wk CP
Procedural Programming (L0197) Lecture 1 2
Procedural Programming (L0201) Recitation Section (large) 1 1
Procedural Programming (L0202) Practical Course 2 3
Module Responsible Prof. Siegfried Rump
Admission Requirements None
Recommended Previous Knowledge

Elementary PC handling skills

Elementary mathematical skills

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students acquire the following knowledge:

  • They know basic elements of the programming language C. They know the basic data types and know how to use them.

  • They have an understanding of elementary compiler tasks, of the preprocessor and programming environment and know how those interact.

  • They know how to bind programs and how to include external libraries to enhance software packages.

  • They know how to use header files and how to declare function interfaces to create larger programming projects.

  • The acquire some knowledge how the program interacts with the operating system. This allows them to develop programs interacting with the programming environment as well.

  • They learnt several possibilities how to model and implement frequently occurring standard algorithms.

Skills
  • The students know how to judge the complexity of an algorithms and how to program algorithms efficiently.

  • The students are able to model and implement algorithms for a number of standard functionalities. Moreover, they are able to adapt a given API.

Personal Competence
Social Competence

The students acquire the following skills:

  • They are able to work in small teams to solve given weekly tasks, to identify and analyze programming errors and to present their results.

  • They are able to explain simple phenomena to each other directly at the PC.

  • They are able to plan and to work out a project in small teams.

  • They communicate final results and present programs to their tutor.

Autonomy
  • The students take individual examinations as well as a final written examn to prove their programming skills and ability to solve new tasks.

  • The students have many possibilities to check their abilities when solving several given programming exercises.

  • In order to solve the given tasks efficiently, the students have to split those appropriately within their group, where every student solves his or her part individually.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula Computer Science: Core qualification: Compulsory
Electrical Engineering: Core qualification: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Logistics and Mobility: Specialisation Engineering Science: Elective Compulsory
Mechatronics: Core qualification: Compulsory
Technomathematics: Core qualification: Compulsory
Course L0197: Procedural Programming
Typ Lecture
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe
Content
  • basic data types (integers, floating point format, ASCII-characters) and their dependencies on the CPU architecture
  • advanced data types (pointers, arrays, strings, structs, lists)

  • operators (arithmetical operations, logical operations, bit operations)

  • control flow (choice, loops, jumps)

  • preprocessor directives (macros, conditional compilation, modular design)

  • functions (function definitions/interface, recursive functions, "call by value" versus "call by reference", function pointers)

  • essential standard libraries and functions (stdio.h, stdlib.h, math.h, string.h, time.h)

  • file concept, streams

  • basic algorithms (sorting functions, series expansion, uniformly distributed permutation)

  • exercise programs to deepen the programming skills



Literature

Kernighan, Brian W (Ritchie, Dennis M.;)
The C programming language
ISBN: 9780131103702
Upper Saddle River, NJ [u.a.] : Prentice Hall PTR, 2009

Sedgewick, Robert 
Algorithms in C
ISBN: 0201316633
Reading, Mass. [u.a.] : Addison-Wesley, 2007 

Kaiser, Ulrich (Kecher, Christoph.;)
C/C++: Von den Grundlagen zur professionellen Programmierung
ISBN: 9783898428392
Bonn : Galileo Press, 2010

Wolf, Jürgen 
C von A bis Z : das umfassende Handbuch
ISBN: 3836214113
Bonn : Galileo Press, 2009

Course L0201: Procedural Programming
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0202: Procedural Programming
Typ Practical Course
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0577: Nontechnical Complementary Courses for Bachelors

Module Responsible Dagmar Richter
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The Non-technical Academic Programms (NTA)

imparts skills that, in view of the TUHH’s training profile, professional engineering studies require but are not able to cover fully. Self-reliance, self-management, collaboration and professional and personnel management competences. The department implements these training objectives in its teaching architecture, in its teaching and learning arrangements, in teaching areas and by means of teaching offerings in which students can qualify by opting for specific competences and a competence level at the Bachelor’s or Master’s level. The teaching offerings are pooled in two different catalogues for nontechnical complementary courses.

The Learning Architecture

consists of a cross-disciplinarily study offering. The centrally designed teaching offering ensures that courses in the nontechnical academic programms follow the specific profiling of TUHH degree courses.

The learning architecture demands and trains independent educational planning as regards the individual development of competences. It also provides orientation knowledge in the form of “profiles”

The subjects that can be studied in parallel throughout the student’s entire study program - if need be, it can be studied in one to two semesters. In view of the adaptation problems that individuals commonly face in their first semesters after making the transition from school to university and in order to encourage individually planned semesters abroad, there is no obligation to study these subjects in one or two specific semesters during the course of studies.

Teaching and Learning Arrangements

provide for students, separated into B.Sc. and M.Sc., to learn with and from each other across semesters. The challenge of dealing with interdisciplinarity and a variety of stages of learning in courses are part of the learning architecture and are deliberately encouraged in specific courses.

Fields of Teaching

are based on research findings from the academic disciplines cultural studies, social studies, arts, historical studies, migration studies, communication studies and sustainability research, and from engineering didactics. In addition, from the winter semester 2014/15 students on all Bachelor’s courses will have the opportunity to learn about business management and start-ups in a goal-oriented way.

The fields of teaching are augmented by soft skills offers and a foreign language offer. Here, the focus is on encouraging goal-oriented communication skills, e.g. the skills required by outgoing engineers in international and intercultural situations.

The Competence Level

of the courses offered in this area is different as regards the basic training objective in the Bachelor’s and Master’s fields. These differences are reflected in the practical examples used, in content topics that refer to different professional application contexts, and in the higher scientific and theoretical level of abstraction in the B.Sc.

This is also reflected in the different quality of soft skills, which relate to the different team positions and different group leadership functions of Bachelor’s and Master’s graduates in their future working life.

Specialized Competence (Knowledge)

Students can

  • locate selected specialized areas with the relevant non-technical mother discipline,
  • outline basic theories, categories, terminology, models, concepts or artistic techniques in the disciplines represented in the learning area,
  • different specialist disciplines relate to their own discipline and differentiate it as well as make connections, 
  • sketch the basic outlines of how scientific disciplines, paradigms, models, instruments, methods and forms of representation in the specialized sciences are subject to individual and socio-cultural interpretation and historicity,
  • Can communicate in a foreign language in a manner appropriate to the subject.
Skills

Professional Competence (Skills)

In selected sub-areas students can

  • apply basic methods of the said scientific disciplines,
  • auestion a specific technical phenomena, models, theories from the viewpoint of another, aforementioned specialist discipline,
  • to handle simple questions in aforementioned scientific disciplines in a sucsessful manner,
  • justify their decisions on forms of organization and application in practical questions in contexts that go beyond the technical relationship to the subject.
Personal Competence
Social Competence

Personal Competences (Social Skills)

Students will be able

  • to learn to collaborate in different manner,
  • to present and analyze problems in the abovementioned fields in a partner or group situation in a manner appropriate to the addressees,
  • to express themselves competently, in a culturally appropriate and gender-sensitive manner in the language of the country (as far as this study-focus would be chosen), 
  • to explain nontechnical items to auditorium with technical background knowledge.


Autonomy

Personal Competences (Self-reliance)

Students are able in selected areas

  • to reflect on their own profession and professionalism in the context of real-life fields of application
  • to organize themselves and their own learning processes      
  • to reflect and decide questions in front of a broad education background
  • to communicate a nontechnical item in a competent way in writen form or verbaly
  • to organize themselves as an entrepreneurial subject country (as far as this study-focus would be chosen)      
Workload in Hours Depends on choice of courses
Credit points 6
Courses
Information regarding lectures and courses can be found in the corresponding module handbook published separately.

Module M1111: Mechanics for Technomathematicians

Courses
Title Typ Hrs/wk CP
Mechancis I for Technomathematicians (L1436) Lecture 2 3
Mechancis I for Technomathematicians (L1437) Recitation Section (small) 2 1
Mechanics II for Technomathematicians (L1438) Lecture 2 3
Mechanics II for Technomathematicians (L1439) Recitation Section (small) 2 1
Module Responsible Dr. Marc-André Pick
Admission Requirements None
Recommended Previous Knowledge

Elementary knowledge in mathematics and physics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students can

  • describe the axiomatic procedure used in mechanical contexts;
  • present technical knowledge in stereostatics and elastostatics;
  • explain important steps in model design with respect to applications in mechanics;
  • appraise the importance of techno-mathematicians in the business of engineering mechanics.
Skills

The students can

  • explain the important elements of mathematical / mechanical analysis and model formation, and apply it to the context of their own problems;
  • apply basic statical and elastostatic methods to engineering problems;
  • estimate the reach and boundaries of statical methods and extend them to be applicable to wider problem sets.
Personal Competence
Social Competence

The students can work in groups and support each other to overcome difficulties.

Autonomy

Students are capable of determining their own strengths and weaknesses and to organize their time and learning based on those.

Workload in Hours Independent Study Time 128, Study Time in Lecture 112
Credit points 8
Studienleistung
Compulsory Bonus Form Description
Yes 20 % Excercises
Examination Written exam
Examination duration and scale 180 min
Assignment for the Following Curricula Technomathematics: Core qualification: Compulsory
Course L1436: Mechancis I for Technomathematicians
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Marc-André Pick
Language DE
Cycle WiSe
Content

Forces and Equilibrium

Gravity, center of gravity

Constraints and reactions

Trusses

Static and dynamic friction

Elastic bars

State of stress

State of strain

Literature D. Gross, W. Hauger, J. Schröder, W. Wall: Technische Mechanik 1. 11. Auflage, Springer (2011).
Course L1437: Mechancis I for Technomathematicians
Typ Recitation Section (small)
Hrs/wk 2
CP 1
Workload in Hours Independent Study Time 2, Study Time in Lecture 28
Lecturer Dr. Marc-André Pick
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L1438: Mechanics II for Technomathematicians
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Marc-André Pick
Language DE
Cycle SoSe
Content

Beams, frames, arches

Bending of beams

Torsion

Buckling 

Statics of ropes

Principle of virtual forces

Numerical methods in Elasticity

Literature D. Gross, W. Hauger, J. Schröder, W. Wall: Technische Mechanik 2, 4. 11. Auflage, Springer (2011).
Course L1439: Mechanics II for Technomathematicians
Typ Recitation Section (small)
Hrs/wk 2
CP 1
Workload in Hours Independent Study Time 2, Study Time in Lecture 28
Lecturer Dr. Marc-André Pick
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0718: Linear Algebra for Technomathematicians

Courses
Title Typ Hrs/wk CP
Linear Algebra 1 for Technomathematicians (L0587) Lecture 4 4
Linear Algebra 1 for Technomathematicians (L0588) Recitation Section (small) 2 4
Linear Algebra 2 for Technomathematicians (L0589) Lecture 4 4
Linear Algebra 2 for Technomathematicians (L0590) Recitation Section (small) 2 4
Module Responsible Prof. Sabine Le Borne
Admission Requirements None
Recommended Previous Knowledge High school mathematics
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  • define the basic terms of Linear Algebra, illustrate them with examples and detect interrelations,
  • list techniques for proofs,
  • sketch main steps in proofs of central theorems.

Students can furthermore explain the basic steps that arise in modelling and relate them to application scenarios.

Skills

Students are capable to

  • apply the tools of Linear Algebra,
  • implement (MATLAB) and test algorithms (e.g. solution of linear systems of equations, computation of the determinant, computation of eigenvalues and eigenvectors),
  • develop proofs for propositions in Linear Algebra and to document them in a comprehensible manner.


Personal Competence
Social Competence

Students are able to

  • work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge), explain theoretical foundations and support each other with practical aspects regarding the implementation of algorithms,
  • explain solutions/proofs of the excercises at the blackboard in a way suitable for the audience (in the excercise sessions).
Autonomy

Students are capable

  • to assess whether the supporting theoretical and practical excercises are better solved individually or in a team,
  • to work on complex problems over an extended period of time,
  • to assess their individual progess and, if necessary, to ask questions and seek help.
Workload in Hours Independent Study Time 312, Study Time in Lecture 168
Credit points 16
Studienleistung None
Examination Written exam
Examination duration and scale 120 minutes
Assignment for the Following Curricula Technomathematics: Core qualification: Compulsory
Course L0587: Linear Algebra 1 for Technomathematicians
Typ Lecture
Hrs/wk 4
CP 4
Workload in Hours Independent Study Time 64, Study Time in Lecture 56
Lecturer Prof. Sabine Le Borne, Prof. Anusch Taraz
Language DE
Cycle WiSe
Content
  1. Proofs, sets, relations
  2. Fields
  3. Vector spaces
  4. Applications of vector spaces
  5. Linear mappings
  6. Polynomials
  7. Determinants
  8. Groups


Literature
  • G. Fischer, Lineare Algebra: Eine Einführung für Studienanfänger
  • A. Beutelspacher: Lineare Algebra: Eine Einführung in die Wissenschaft der Vektoren, Abbildungen und Matrizen
  • J. Liesen, V. Mehrmann: Lineare Algebra: Ein Lehrbuch über die Theorie mit Blick auf die Praxis
  • G. Strang: Introduction to Linear Algebra
Course L0588: Linear Algebra 1 for Technomathematicians
Typ Recitation Section (small)
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne, Prof. Anusch Taraz
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0589: Linear Algebra 2 for Technomathematicians
Typ Lecture
Hrs/wk 4
CP 4
Workload in Hours Independent Study Time 64, Study Time in Lecture 56
Lecturer Prof. Sabine Le Borne, Prof. Anusch Taraz
Language DE
Cycle SoSe
Content
  1. Eigenvalues
  2. Bilinear forms
  3. Singular value decomposition
  4. Tensor products
  5. Application: Linear ordinary differential equations
Literature siehe Lineare Algebra 1 für Technomathematiker
Course L0590: Linear Algebra 2 for Technomathematicians
Typ Recitation Section (small)
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne, Prof. Anusch Taraz
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0774: Electrical Engineering for Technomathematicians

Courses
Title Typ Hrs/wk CP
Electrical Engineering I for Technomathematicians (L0754) Lecture 2 3
Electrical Engineering I for Technomathematicians (L0755) Recitation Section (small) 1 1
Electrical Engineering II for Technomathematicians (L0756) Lecture 2 3
Electrical Engineering II for Technomathematicians (L0757) Recitation Section (small) 1 1
Module Responsible Dr. Heinz-Dietrich Brüns
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students know the basic theory, relations, and methods of electric and magnetic field computation and linear network theory.  This includes, in particular:  

  • the Maxwell equations in integral form,
  • the formulation of electric and magnetic fields as vector fields in different coordinate systems,
  • the constitutive relations,
  • the Gauss law,
  • the Ampère law,
  • the induction law,
  • the Kirchhoff's laws,
  • the Ohm's law,
  • the concepts and definitions of resistance, capacitance, and inductance,
  • methods for the simplification and analysis of linear networks,
  • complex numbers and their use in steady state sinusoidal analysis,
  • the concept of impedance,
  • the concept  of resonance,
  • locus plots,
  • energy and power in steady state sinusoidal analysis,
  • 3-phase systems,
  • transients

The students can explain the basic steps that arise in modelling and relate them to application scenarios in electrical engineering. 

Skills

The students are able to apply the basic laws of electromagnetism to electric and magnetic field computation. They are able to relate the various field quantities to each other. The studens are able to calculate resistances, capacitances, and inductances of simple configurations. The students know how to apply network theory to calculate the currents and voltages of linear networks and how to design simple circuits.

Personal Competence
Social Competence

Students are able to solve specific problems, alone or in a group, and to present the results accordingly. Students can explain concepts and, on the basis of examples and exercises, verify and deepen their understanding.

Autonomy

Students are able to acquire particular knowledge using textbooks in a self-learning process, to integrate, present, and associate this knowledge with other fields. The students develop persistency to also solve more complicated problems.

Workload in Hours Independent Study Time 156, Study Time in Lecture 84
Credit points 8
Studienleistung None
Examination Written exam
Examination duration and scale 120 minutes
Assignment for the Following Curricula Technomathematics: Core qualification: Compulsory
Course L0754: Electrical Engineering I for Technomathematicians
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Heinz-Dietrich Brüns
Language DE/EN
Cycle WiSe
Content
  • Introduction
  • Electrostatics
  • Stationary electric currents
  • Basic concepts of network theory
  • Stationary magnetic fields

Literature
  • M. Albach, "Elektrotechnik", (Pearson, München, 2011).
Course L0755: Electrical Engineering I for Technomathematicians
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dr. Heinz-Dietrich Brüns
Language DE/EN
Cycle WiSe
Content The exercise sessions serve to deepen the understanding of the concepts of the lecture.
Literature
  • M. Albach, "Elektrotechnik", (Pearson, München, 2011).
Course L0756: Electrical Engineering II for Technomathematicians
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Heinz-Dietrich Brüns
Language DE/EN
Cycle SoSe
Content
  • Periodic and sinusoidal signals
  • Transients
Literature
  • M. Albach, "Elektrotechnik", (Pearson, München, 2011).
Course L0757: Electrical Engineering II for Technomathematicians
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dr. Heinz-Dietrich Brüns
Language DE/EN
Cycle SoSe
Content

The exercise sessions serve to deepen the understanding of the concepts of the lecture.

Literature

M. Albach, "Elektrotechnik", (Pearson, München, 2011).

Module M0690: Analysis for Technomathematicians

Courses
Title Typ Hrs/wk CP
Analysis I for Technomathematicians (L0483) Lecture 4 4
Analysis I for Technomathematicians (L0484) Recitation Section (small) 2 4
Analysis II for Technomathematicians (L0485) Lecture 4 4
Analysis II for Technomathematicians (L0486) Recitation Section (small) 2 4
Module Responsible Prof. Marko Lindner
Admission Requirements None
Recommended Previous Knowledge High school mathematics
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  • name, define and explain the basic properties of the field of real numbers,
  • define and interrelate the basic topological terms in a metric space,
  • in particular, describe their interrelation with the concepts of convergence and continuiuty,
  • define, explain and use the basic terms of differential calculus in several veriables and integral calculus in one variable,

In particular, they are able to correctly define, explain and interrelate all these concepts and to sketch the main ideas in proofs of central theorems.

Students can furthermore explain the basic steps that arise in modelling and relate them to application scenarios.

Skills

Students are able to

  • determine topological properties of concrete sets in metric space,
  • determine and prove convergence and divergence of sequences and series - as well as continuity, uniform continuity and Lipschitz continuity of a given function between two metric spaces,
  • differentiate a function in one or several variables,
  • decide whether a given function is Riemann integrable and compute its integral,
  • compute Taylor polynomial and Taylor series of a given, sufficiently smooth, function in one or more variables,
  • find local and global extrema of a given function - possibly under constraints
Personal Competence
Social Competence Students are able to solve specific problems in groups (e.g. in connection with their regular homework) and to present their results appropriately (e.g. during exercise class).
Autonomy

Students are able to

  • gain further information from additional literature and put it in context with the contents of the lecture,
  • put their knowledge in relation to the contents of other lectures,
  • work on difficult problems over a long period.
Workload in Hours Independent Study Time 312, Study Time in Lecture 168
Credit points 16
Studienleistung None
Examination Written exam
Examination duration and scale 120
Assignment for the Following Curricula Technomathematics: Core qualification: Compulsory
Course L0483: Analysis I for Technomathematicians
Typ Lecture
Hrs/wk 4
CP 4
Workload in Hours Independent Study Time 64, Study Time in Lecture 56
Lecturer Prof. Marko Lindner, Prof. Sabine Le Borne
Language DE
Cycle WiSe
Content
  • logic, sets
  • cardinalities
  • numbers
  • metric space and convergence
  • continuity
Literature
  • K. Königsberger: Analysis I und II
  • O. Forster: Analysis 1 und 2
  • H. Heuser: Lehrbuch der Analysis. Teile 1 und 2
Course L0484: Analysis I for Technomathematicians
Typ Recitation Section (small)
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Marko Lindner, Prof. Sabine Le Borne
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0485: Analysis II for Technomathematicians
Typ Lecture
Hrs/wk 4
CP 4
Workload in Hours Independent Study Time 64, Study Time in Lecture 56
Lecturer Prof. Marko Lindner, Prof. Sabine Le Borne
Language DE
Cycle SoSe
Content
  • differentiation in 1D
  • integration in 1D
  • sequences and series of functions
  • differentiation in several variables
Literature
  • K. Königsberger: Analysis I und II
  • O. Forster: Analysis 1 und 2
  • H. Heuser: Lehrbuch der Analysis. Teile 1 und 2


Course L0486: Analysis II for Technomathematicians
Typ Recitation Section (small)
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Marko Lindner, Prof. Sabine Le Borne
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0553: Objectoriented Programming, Algorithms and Data Structures

Courses
Title Typ Hrs/wk CP
Objectoriented Programming, Algorithms and Data Structures (L0131) Lecture 4 4
Objectoriented Programming, Algorithms and Data Structures (L0132) Recitation Section (small) 1 2
Module Responsible Prof. Rolf-Rainer Grigat
Admission Requirements None
Recommended Previous Knowledge

Lecture Prozedurale Programmierung or equivalent proficiency in imperative programming

Mandatory prerequisite for this lecture is proficiency in imperative programming (C, Pascal, Fortran or similar). You should be familiar with simple data types (integer, double, char), arrays, if-then-else, for, while, procedure calls or function calls, pointers, and you should have used all those in your own programs and therefore should be proficient with editor, compiler, linker and debugger. In this lecture we will immediately start with the introduction of objects and we will not repeat the basics mentioned above.

This remark is especially important for AIW, GES, LUM because those prerequisites are not part of the curriculum. They are prerequisites for the start of those curricula in general. The programs ET, CI and IIW include those prerequisites in the first semester in the lecture Prozedurale Programmierung.

.

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the essentials of software design and the design of a class architecture with reference to existing class libraries and design patterns.

Students can describe fundamental data structures of discrete mathematics and assess the complexity of important algorithms for sorting and searching.



Skills

Students are able to

  • Design software using given design patterns and applying class hierarchies and polymorphism
  • Carry out software development and tests using version management systems and Google Test
  • Sort and search for data efficiently
  • Assess the complexity of algorithms.


Personal Competence
Social Competence

Students can work in teams and communicate in forums.


Autonomy

Students are able to solve programming tasks such as LZW data compression using SVN Repository and Google Test independently and over a period of two to three weeks.


Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 60 Minutes, Content of Lecture, exercises and material in StudIP
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Computer Science: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory
Computer Science: Core qualification: Compulsory
Electrical Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Computer Science: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Logistics and Mobility: Specialisation Engineering Science: Elective Compulsory
Technomathematics: Core qualification: Compulsory
Course L0131: Objectoriented Programming, Algorithms and Data Structures
Typ Lecture
Hrs/wk 4
CP 4
Workload in Hours Independent Study Time 64, Study Time in Lecture 56
Lecturer Prof. Rolf-Rainer Grigat
Language DE
Cycle SoSe
Content

Object oriented analysis and design:   

  • Objectoriented programming in C++ and Java
  • generic programming
  • UML
  • design patterns

Data structures and algorithmes:

  • complexity of algorithms
  • searching, sorting, hash tables,
  • stack, queues, lists,
  • trees (AVL, heap, 2-3-4, Trie, Huffman, Patricia, B),
  • sets, priority queues,
  • directed and undirected graphs (spanning trees, shortest and longest path)
Literature Skriptum
Course L0132: Objectoriented Programming, Algorithms and Data Structures
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Rolf-Rainer Grigat
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1113: Proseminar Technomathematics

Courses
Title Typ Hrs/wk CP
Proseminar Mathematics (L0919) Seminar 2 2
Module Responsible Prof. Anusch Taraz
Admission Requirements None
Recommended Previous Knowledge
  • Analysis & Linear Algebra I + II for Technomathematicians

or

  • Mathematik I + II (for Engineering Students - German or English lecture series), and
  • an advanced course by the lecturer who is responsible for the proseminar
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students acquire a deep understanding of the mathematical subject under consideration.

Skills

Students are able to

  • understand, analyze, classify and work on an advanced mathematical topic,
  • thoroughly study the recommended literature,
  • present their results in a mathematically correct and comprehensible way.
Personal Competence
Social Competence

Students are able to present their results in an appropriate way to the group.

Autonomy

Students are able to prepare a written scientific presentation on their own; in particular to

  • find and critically check relevant literature,
  • make and incorporate their own thoughts,
  • complete the presentation in time.
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Credit points 2
Studienleistung None
Examination Presentation
Examination duration and scale 60 Minutes
Assignment for the Following Curricula Technomathematics: Core qualification: Compulsory
Course L0919: Proseminar Mathematics
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Anusch Taraz, Prof. Sabine Le Borne, Prof. Marko Lindner, Dr. Christian Seifert, Prof. Heinrich Voß, Dozenten des Fachbereiches Mathematik der UHH, Dr. Mijail Guillemard
Language DE
Cycle WiSe/SoSe
Content

Selected topics from the fields

  • Applied Analysis
  • Numerical Linear Algebra
  • Computational mathematics
  • Discrete mathematics
Literature

wird in der Lehrveranstaltung bekannt gegeben

Module M1075: Numerical Mathematics

Courses
Title Typ Hrs/wk CP
Numerical Mathematics (L1357) Lecture 4 6
Numerical Mathematics (L1358) Recitation Section (small) 2 3
Module Responsible Prof. Jens Struckmeier
Admission Requirements None
Recommended Previous Knowledge

Linear Algebra

Analysis

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Numerical Mathematics such as moethods for linear systems of equations and their error analysis, interpolation by polynomials and splines, orthogonalization methods, linear regression, linear optimization, numerical integration, nonlinear equations and eigenvalue problems. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Numerical Mathematics ith the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Written exam
Examination duration and scale 120 minutes
Assignment for the Following Curricula Technomathematics: Core qualification: Compulsory
Course L1357: Numerical Mathematics
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content
  • Linear systems of equations, error analysis
  • Interpolation by polynomials and splines
  • Orthogonalization methods, linear regression
  • Linear optimization, in particular simplex method
  • Numerical integration
  • Nonlinear equations
  • Eigenvalue problems
Literature
  • Numerische Mathematik, Jochen Werner, Vieweg, 1992
  • Numerische Mathematik, Robert Schaback, Holger Wendland, Auflage: 5., vollst. neu bearb. Aufl. 2005 (8. September 2004), Sprache: Deutsch, ISBN-10: 3540213945, ISBN-13: 978-3540213949
  • Numerische Mathematik, Hans-Rudolf Schwarz, Norbert Köckler, Vieweg+Teubner Verlag, 2011, ISBN: 3834815519 ISBN: 9783834815514
  • Stoer/Bulirsch: Numerische Mathematik 1, Roland Freund, Ronald Hoppe, Springer; Auflage: 10., neu bearb. Aufl. 2007 (18. April 2007), Sprache: Deutsch, ISBN-10: 354045389X, ISBN-13: 978-3540453895
  • Numerische Mathematik I, Peter Deuflhard, Andreas Hohmann, Gruyter; Auflage: 3., überarb. A. (18. April 2002), Deutsch, ISBN-10: 3110171821, ISBN-13: 978-3110171822


Course L1358: Numerical Mathematics
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1085: Mathematical Stochastics

Courses
Title Typ Hrs/wk CP
Mathematical Stochastics (L1392) Lecture 4 6
Mathematical Stochastics (L1393) Recitation Section (small) 2 3
Module Responsible Prof. Holger Drees
Admission Requirements None
Recommended Previous Knowledge
  • Analysis
  • Linear Algebra
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Mathematical Stochastics such as probability measures and random experiments, random variables and pushforward measures, classification numbers of random variables and distributions, transition probabilities and stochastic independence, law of large numbers and limit theorems, measurable functions and general measure integral.
  • They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Stochastics with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Written exam
Examination duration and scale 120 minutes
Assignment for the Following Curricula Technomathematics: Core qualification: Compulsory
Course L1392: Mathematical Stochastics
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content
  • Probability measures and random experiments
  • Random variables and pushforward measures, classification numbers of random variables and distributions
  • Multi-level models: Transition probabilities and stochastic independence
  • Law of large numbers and central limit theorem, Poisson's limit theorem
  • Measurable functions and general measure integral, application in stochastics
  • Treatment of selected problems of statistics, stochastic processes, insurance mathematics
  • Problems of stochastic modelling
Literature
  • K. Behnen und G. Neuhaus (2003). Grundkurs Stochastik (4. Aufl.). PD-Verlag
  • P. Billingsley (1995). Probability and Measure (3. ed.). Wiley.
  • H. Dehling und B. Haupt (2003). Einführung in die Wahrscheinlichkeitstheorie und Statistik. Springer.
  • C. Hesse (2003). Angewandte Wahrscheinlichkeitstheorie. Vieweg Verlag.
  • U. Krengel (2000). Einführung in die Wahrscheinlichkeitstheorie und Statistik. Vieweg.
Course L1393: Mathematical Stochastics
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1074: Higher Analysis

Courses
Title Typ Hrs/wk CP
Higher Analysis (L1355) Lecture 4 6
Higher Analysis (L1356) Recitation Section (small) 2 3
Module Responsible Prof. Vicente Cortés
Admission Requirements None
Recommended Previous Knowledge
  • Analysis
  • Linear Algebra
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Higher Analysis such as submanifolds, tangential bundles, Lebesgue integration theory, fundamentals of funktional analysis, the Hilbert space L2, Fourier analysis, Lp spaces, classical inequalities and fundamentals of general measure and integration theory. They are able to explain them using appropriate examples. 
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Higher Analysis with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Written exam
Examination duration and scale 120 minutes
Assignment for the Following Curricula Technomathematics: Core qualification: Compulsory
Course L1355: Higher Analysis
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content
  • Submanifolds of Rn
  • Tangential bundles
    • Differential of differentiable mappings
    • Integral theorems for submanifolds (in general form)
  • Lebesgue integration theory
  • Fundamentals of funktional analysis
  • Hilbert space L2 and Fourier analysis
  • Lp spaces
  • Classical inequalities
  • Fundamentals of general measure and integration theory
Literature

a) Vektoranalysis - Differentialformen in Analysis, Geometrie und Physik

  • Autoren: Ilka Agricola, Thomas Friedrich
  • Vieweg + Teubner Verlag, 2. Auflage, 2010
  • Sprache: Deutsch
  • ISBN-10: 3834810169
  • ISBN-13: 978-3834810168


b) Analysis 3: Maß- und Integrationstheorie, Integralsätze im IRn und Anwendungen (Aufbaukurs Mathematik)

  • Autor: Otto Forster
  • Vieweg+Teubner Verlag; Auflage: 7., überarb. Aufl. 2012
  • Sprache: Deutsch
  •  ISBN-10: 3834823732
  • ISBN-13: 978-3834823731

  

c) Höhere Analysis, 

  • Autor: R. Lauterbach

    (Skript, WS 09/10, verfügbar auf http://www.math.uni-hamburg.de/home/lauterbach/analysis3_WS0910.html#skript)      


d) Real and complex analysis

  • Autor: Walter Rudin
  • Verlag: Oldenbourg Wissenschaftsverlag (25. August 1999)
  • Sprache: Deutsch
  • ISBN-10: 3486247891
  • ISBN-13: 978-3486247893

oder

    Real and complex analysis

  • Autor: Walter Rudin
  • McGraw-Hill, 1987 , 3. illustrierte Neuauflage
  • Sprache: Englisch
  • Digitalisiert: 2. Febr. 2010
  • ISBN: 0070542341, 9780070542341

e) An Introduction to Measure Theory (Graduate Studies in Mathematics)

  • Autor: Terence Tao
  • Verlag: American Mathematical Society (15. September 2011)
  • Sprache: Englisch
  • ISBN-10: 0821869191
  • ISBN-13: 978-0821869192


f) Maß- und Integrationstheorie

  • Autor: Heinz Bauer
  • Verlag: de Gruyter; Auflage: 2., überarb. A. (1. Juli 1992)
  • Sprache: Englisch
  • ISBN-10: 3110136252
  • ISBN-13: 978-3110136258

      

g) Maß- und Integrationstheorie

  • Autor: Jürgen Elstrodt
  • Springer, 2004
  • ISBN-10: 3540213902
  • ISBN-13: 9783540213901
Course L1356: Higher Analysis
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0829: Foundations of Management

Courses
Title Typ Hrs/wk CP
Management Tutorial (L0882) Recitation Section (large) 2 3
Introduction to Management (L0880) Lecture 3 3
Module Responsible Prof. Christoph Ihl
Admission Requirements None
Recommended Previous Knowledge Basic Knowledge of Mathematics and Business
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

After taking this module, students know the important basics of many different areas in Business and Management, from Planning and Organisation to Marketing and Innovation, and also to Investment and Controlling. In particular they are able to

  • explain the differences between Economics and Management and the sub-disciplines in Management and to name important definitions from the field of Management
  • explain the most important aspects of and goals in Management and name the most important aspects of entreprneurial projects 
  • describe and explain basic business functions as production, procurement and sourcing, supply chain management, organization and human ressource management, information management, innovation management and marketing 
  • explain the relevance of planning and decision making in Business, esp. in situations under multiple objectives and uncertainty, and explain some basic methods from mathematical Finance 
  • state basics from accounting and costing and selected controlling methods.
Skills

Students are able to analyse business units with respect to different criteria (organization, objectives, strategies etc.) and to carry out an Entrepreneurship project in a team. In particular, they are able to

  • analyse Management goals and structure them appropriately
  • analyse organisational and staff structures of companies
  • apply methods for decision making under multiple objectives, under uncertainty and under risk
  • analyse production and procurement systems and Business information systems
  • analyse and apply basic methods of marketing
  • select and apply basic methods from mathematical finance to predefined problems
  • apply basic methods from accounting, costing and controlling to predefined problems

Personal Competence
Social Competence

Students are able to

  • work successfully in a team of students
  • to apply their knowledge from the lecture to an entrepreneurship project and write a coherent report on the project
  • to communicate appropriately and
  • to cooperate respectfully with their fellow students. 
Autonomy

Students are able to

  • work in a team and to organize the team themselves
  • to write a report on their project.
Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Studienleistung None
Examination Subject theoretical and practical work
Examination duration and scale several written exams during the semester
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Electrical Engineering: Compulsory
General Engineering Science (German program): Specialisation Computer Science: Compulsory
General Engineering Science (German program): Specialisation Process Engineering: Compulsory
General Engineering Science (German program): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (German program): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (German program): Specialisation Civil- and Enviromental Engeneering: Compulsory
General Engineering Science (German program): Specialisation Mechanical Engineering: Compulsory
General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program): Specialisation Naval Architecture: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Process Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Naval Architecture: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Civil Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Aircraft Systems Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Product Development and Production: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory
Civil- and Environmental Engineering: Core qualification: Compulsory
Bioprocess Engineering: Core qualification: Compulsory
Computer Science: Core qualification: Compulsory
Electrical Engineering: Core qualification: Compulsory
Energy and Environmental Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Civil- and Enviromental Engeneering: Compulsory
General Engineering Science (English program): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (English program): Specialisation Electrical Engineering: Compulsory
General Engineering Science (English program): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (English program): Specialisation Computer Science: Compulsory
General Engineering Science (English program): Specialisation Mechanical Engineering: Compulsory
General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program): Specialisation Naval Architecture: Compulsory
General Engineering Science (English program): Specialisation Process Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Process Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Naval Architecture: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Civil Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Aircraft Systems Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Product Development and Production: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Logistics and Mobility: Core qualification: Compulsory
Mechanical Engineering: Core qualification: Compulsory
Mechatronics: Core qualification: Compulsory
Naval Architecture: Core qualification: Compulsory
Technomathematics: Core qualification: Compulsory
Process Engineering: Core qualification: Compulsory
Course L0882: Management Tutorial
Typ Recitation Section (large)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Christoph Ihl, Katharina Roedelius, Tobias Vlcek
Language DE
Cycle WiSe/SoSe
Content

In the management tutorial, the contents of the lecture will be deepened by practical examples and the application of the discussed tools.

If there is adequate demand, a problem-oriented tutorial will be offered in parallel, which students can choose alternatively. Here, students work in groups on self-selected projects that focus on the elaboration of an innovative business idea from the point of view of an established company or a startup. Again, the business knowledge from the lecture should come to practical use. The group projects are guided by a mentor.


Literature Relevante Literatur aus der korrespondierenden Vorlesung.
Course L0880: Introduction to Management
Typ Lecture
Hrs/wk 3
CP 3
Workload in Hours Independent Study Time 48, Study Time in Lecture 42
Lecturer Prof. Christoph Ihl, Prof. Thorsten Blecker, Prof. Christian Lüthje, Prof. Christian Ringle, Prof. Kathrin Fischer, Prof. Cornelius Herstatt, Prof. Wolfgang Kersten, Prof. Matthias Meyer, Prof. Thomas Wrona
Language DE
Cycle WiSe/SoSe
Content
  • Introduction to Business and Management, Business versus Economics, relevant areas in Business and Management
  • Important definitions from Management, 
  • Developing Objectives for Business, and their relation to important Business functions
  • Business Functions: Functions of the Value Chain, e.g. Production and Procurement, Supply Chain Management, Innovation Management, Marketing and Sales
    Cross-sectional Functions, e.g. Organisation, Human Ressource Management, Supply Chain Management, Information Management
  • Definitions as information, information systems, aspects of data security and strategic information systems
  • Definition and Relevance of innovations, e.g. innovation opporunities, risks etc.
  • Relevance of marketing, B2B vs. B2C-Marketing
  • different techniques from the field of marketing (e.g. scenario technique), pricing strategies
  • important organizational structures
  • basics of human ressource management
  • Introduction to Business Planning and the steps of a planning process
  • Decision Analysis: Elements of decision problems and methods for solving decision problems
  • Selected Planning Tasks, e.g. Investment and Financial Decisions
  • Introduction to Accounting: Accounting, Balance-Sheets, Costing
  • Relevance of Controlling and selected Controlling methods
  • Important aspects of Entrepreneurship projects



Literature

Bamberg, G., Coenenberg, A.: Betriebswirtschaftliche Entscheidungslehre, 14. Aufl., München 2008

Eisenführ, F., Weber, M.: Rationales Entscheiden, 4. Aufl., Berlin et al. 2003

Heinhold, M.: Buchführung in Fallbeispielen, 10. Aufl., Stuttgart 2006.

Kruschwitz, L.: Finanzmathematik. 3. Auflage, München 2001.

Pellens, B., Fülbier, R. U., Gassen, J., Sellhorn, T.: Internationale Rechnungslegung, 7. Aufl., Stuttgart 2008.

Schweitzer, M.: Planung und Steuerung, in: Bea/Friedl/Schweitzer: Allgemeine Betriebswirtschaftslehre, Bd. 2: Führung, 9. Aufl., Stuttgart 2005.

Weber, J., Schäffer, U. : Einführung in das Controlling, 12. Auflage, Stuttgart 2008.

Weber, J./Weißenberger, B.: Einführung in das Rechnungswesen, 7. Auflage, Stuttgart 2006. 


Module M1114: Seminar Technomathematics

Courses
Title Typ Hrs/wk CP
Seminar: Technomathematics (L0920) Seminar 2 4
Module Responsible Prof. Anusch Taraz
Admission Requirements None
Recommended Previous Knowledge
  • Analysis & Linear Algebra I + II for Technomathematicians

or

  • Mathematik I + II (for Engineering Students - German or English lecture series), and
  • an advanced course by the lecturer who is responsible for the seminar
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students acquire a deep understanding of the mathematical subject under consideration.

Skills

Students are able to

  • understand, analyze, classify and work on an advanced mathematical topic,
  • thoroughly study the recommended (and further) literature,
  • write down and present their results in a mathematically correct and comprehensible way.
Personal Competence
Social Competence

Students are able to present their results in an appropriate way to the group.

Autonomy

Students are able to prepare a written scientific report on their own; in particular to

  • find and critically check relevant literature,
  • make and incorporate their own thoughts,
  • finish in time.
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Credit points 4
Studienleistung
Compulsory Bonus Form Description
Yes 0 % Written elaboration
Examination Presentation
Examination duration and scale 60 Minutes
Assignment for the Following Curricula Technomathematics: Core qualification: Compulsory
Course L0920: Seminar: Technomathematics
Typ Seminar
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Dr. Christian Seifert, Prof. Sabine Le Borne, Prof. Marko Lindner, Dr. Christian Seifert, Dr. Jens-Peter Zemke, Dozenten des Fachbereiches Mathematik der UHH
Language DE
Cycle WiSe/SoSe
Content

Selected topics from the fields

  • Applied Analysis
  • Computational mathematics
  • Discrete mathematics
Literature wird in der Lehrveranstaltung bekannt gegeben

Specialization I. Mathematics

Module M1429: Complex Functions

Courses
Title Typ Hrs/wk CP
Complex Functions (L1038) Lecture 2 1
Complex Functions (L1042) Recitation Section (large) 1 1
Complex Functions (L1041) Recitation Section (small) 1 1
Module Responsible Prof. Timo Reis
Admission Requirements None
Recommended Previous Knowledge Analysis, Higher Analysis, Linear Algebra
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
Skills
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 34, Study Time in Lecture 56
Credit points 3
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1038: Complex Functions
Typ Lecture
Hrs/wk 2
CP 1
Workload in Hours Independent Study Time 2, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE
Cycle SoSe
Content

Main features of complex analysis 

  • Functions of one complex variable
  • Complex differentiation
  • Conformal mappings
  • Complex integration
  • Cauchy's integral theorem
  • Cauchy's integral formula
  • Taylor and Laurent series expansion
  • Singularities and residuals
  • Integral transformations: Fourier and Laplace transformation
Literature
  • http://www.math.uni-hamburg.de/teaching/export/tuhh/index.html


Course L1042: Complex Functions
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course
Course L1041: Complex Functions
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1052: Algebra

Courses
Title Typ Hrs/wk CP
Algebra (L1317) Lecture 4 6
Algebra (L1318) Recitation Section (small) 2 3
Module Responsible Prof. Christoph Schweigert
Admission Requirements None
Recommended Previous Knowledge

Linear Algebra

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can name the basic concepts in Algebra such as groups, rings and modules. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Algebra with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1317: Algebra
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content
Literature
  • Jantzen, Schwermer, "Algebra" (Springer)
  • Artin, "Algebra" (Birkhäuser)
  • Bosch, "Algebra" (Springer)
  • Lang, "Algebra" (Springer)
Course L1318: Algebra
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1056: Functional Analysis

Courses
Title Typ Hrs/wk CP
Functional Analysis (L1327) Lecture 4 6
Functional Analysis (L1328) Recitation Section (small) 2 3
Module Responsible Prof. Reiner Lauterbach
Admission Requirements None
Recommended Previous Knowledge
  • Linear Algebra
  • Analysis
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can name basic concepts in Functional Analysis such as Banach and Hilbert spaces, Baire's category theorem, Linear operators, dual spaces, classical function spaces, the Hahn-Banach theorem, (non-)compactness, the Spectrum and compact operators. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Functional Analysis with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1327: Functional Analysis
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content
  • Normed, Banach and Hilbert spaces
  • Baire's category theorem and implications (fundamental principles)
  • Linear operators, dual spaces
  • classical function spaces
  • Hahn-Banach theorem, (non-)compactness
  • Spectrum, compact operators
Literature
  • Alt, Lineare Funktionalanalysis -Eine anwendungsorientierte Einführung, Springer, 2012
  • Werner, Funktionalanalysis, Springer, 2011
  • Rudin, Functional analysis, McGraw-Hill, 1973
  • Adams, Sobolev spaces, Academic press, 1975
Course L1328: Functional Analysis
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0715: Solvers for Sparse Linear Systems

Courses
Title Typ Hrs/wk CP
Solvers for Sparse Linear Systems (L0583) Lecture 2 3
Solvers for Sparse Linear Systems (L0584) Recitation Section (small) 2 3
Module Responsible Prof. Sabine Le Borne
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics I + II for Engineering students or Analysis & Lineare Algebra I + II for Technomathematicians
  • Programming experience in C
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can

  • list classical and modern iteration methods and their interrelationships,
  • repeat convergence statements for iteration methods,
  • explain aspects regarding the efficient implementation of iteration methods.
Skills

Students are able to

  • implement, test, and compare iterative methods,
  • analyse the convergence behaviour of iterative methods and, if applicable, compute congergence rates.
Personal Competence
Social Competence

Students are able to

  • work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge), explain theoretical foundations and support each other with practical aspects regarding the implementation of algorithms.
Autonomy

Students are capable

  • to assess whether the supporting theoretical and practical excercises are better solved individually or in a team,
  • to work on complex problems over an extended period of time,
  • to assess their individual progess and, if necessary, to ask questions and seek help.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Oral exam
Examination duration and scale 20 min
Assignment for the Following Curricula Computer Science: Specialisation Computational Mathematics: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Mathematics & Engineering Science: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L0583: Solvers for Sparse Linear Systems
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne
Language DE/EN
Cycle SoSe
Content
  1. Sparse systems: Orderings and storage formats, direct solvers
  2. Classical methods: basic notions, convergence
  3. Projection methods
  4. Krylov space methods
  5. Preconditioning (e.g. ILU)
  6. Multigrid methods
Literature
  1. Y. Saad, Iterative methods for sparse linear systems
Course L0584: Solvers for Sparse Linear Systems
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1062: Mathematical Statistics

Courses
Title Typ Hrs/wk CP
Mathematical Statistics (L1339) Lecture 3 4
Mathematical Statistics (L1340) Recitation Section (small) 1 2
Module Responsible Prof. Natalie Neumeyer
Admission Requirements None
Recommended Previous Knowledge

Mathematical Stochastics

Measure Theory and Stochastics
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Mathematical Statistics such as the substitution and Maximum-Likelihood methods for construction of estimators, optimal unfalsified estimators, optimal tests for parametric probability distributions,  sufficiency and completeness and their application to estimation and test problems, tests in normal distribution and confidence domains and test families. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Mathematical Statistics with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 120 minutes
Assignment for the Following Curricula General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computer Science: Specialisation Computational Mathematics: Elective Compulsory
General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1339: Mathematical Statistics
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content
  • Substitution and Maximum-Likelihood methods for construction of estimators
  • Optimal unfalsified estimators
  • Optimal tests for parametric probability distributions (Neymann-Pearson theory)
  • Sufficiency and completeness and their application to estimation and test problems
  • Tests in normal distribution (e.g. Student's test)
  • Confidence domains and test families
Literature
  • V. K. Rohatgi and A. K. Ehsanes Saleh (2001). An introduction to probability and statistics. Wiley.
  • L. Wasserman (2010). All of statistics : A concise course in statistical inference. Springer.
  • H. Witting (1985). Mathematische Statistik: Parametrische Verfahren bei festem Stichprobenumfang. Teubner.
Course L1340: Mathematical Statistics
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0692: Approximation and Stability

Courses
Title Typ Hrs/wk CP
Approximation and Stability (L0487) Lecture 3 4
Approximation and Stability (L0488) Recitation Section (small) 1 2
Module Responsible Prof. Marko Lindner
Admission Requirements None
Recommended Previous Knowledge
  • Linear Algebra: systems of linear equations, least squares problems, eigenvalues, singular values
  • Analysis: sequences, series, differentiation, integration
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  • sketch and interrelate basic concepts of functional analysis (Hilbert space, operators),
  • name and understand concrete approximation methods,
  • name and explain basic stability theorems,
  • discuss spectral quantities, conditions numbers and methods of regularisation

Skills

Students are able to

  • apply basic results from functional analysis,
  • apply approximation methods,
  • apply stability theorems,
  • compute spectral quantities,
  • apply regularisation methods.
Personal Competence
Social Competence

Students are able to solve specific problems in groups and to present their results appropriately (e.g. as a seminar presentation).

Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung
Compulsory Bonus Form Description
Yes None Presentation
Examination Oral exam
Examination duration and scale 20 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Mathematical Modelling in Engineering: Theory, Numerics, Applications: Specialisation l. Numerics (TUHH): Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0487: Approximation and Stability
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Marko Lindner
Language DE/EN
Cycle SoSe
Content

This course is about solving the following basic problems of Linear Algebra,

  • systems of linear equations,
  • least squares problems,
  • eigenvalue problems

but now in function spaces (i.e. vector spaces of infinite dimension) by a stable approximation of the problem in a space of finite dimension.

Contents:

  • crash course on Hilbert spaces: metric, norm, scalar product, completeness
  • crash course on operators: boundedness, norm, compactness, projections
  • uniform vs. strong convergence, approximation methods
  • applicability and stability of approximation methods, Polski's theorem
  • Galerkin methods, collocation, spline interpolation, truncation
  • convolution and Toeplitz operators
  • crash course on C*-algebras
  • convergence of condition numbers
  • convergence of spectral quantities: spectrum, eigen values, singular values, pseudospectra
  • regularisation methods (truncated SVD, Tichonov)
Literature
  • R. Hagen, S. Roch, B. Silbermann: C*-Algebras in Numerical Analysis
  • H. W. Alt: Lineare Funktionalanalysis
  • M. Lindner: Infinite matrices and their finite sections
Course L0488: Approximation and Stability
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Marko Lindner
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1079: Differential Geometry

Courses
Title Typ Hrs/wk CP
Differential Geometry (L1365) Lecture 4 6
Differential Geometry (L1366) Recitation Section (small) 2 3
Module Responsible Prof. Vicente Cortés
Admission Requirements None
Recommended Previous Knowledge
  • Analysis
  • Higher Analysis
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Differential Geometry such as curves in Euclidean space, differentiable manifolds, hyperplanes in Euclidean space, surfaces, geodesy in Riemannian manifolds and Riemannian manifolds with constant curvature. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Differential Geometry with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1365: Differential Geometry
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content
  • Curves in the Euclidean space
  • Introduction to differentiable manifolds
  • Hyperplanes in the Euclidean space
  • Surfaces
  • Geodesy in Riemannian manifolds
  • Riemannian manifolds with constant curvature
Literature

Manfredo Perdigão do Carmo: Riemannian geometry, Birkhäuser, 1992.
Takashi Sakai, Riemannian geometry, AMS, 1996.
Frank Warner, Foundations of differentiable manifolds and Lie groups, Springer, 1983.

Course L1366: Differential Geometry
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1080: Ordinary Differential Equations and Dynamical Systems

Courses
Title Typ Hrs/wk CP
Ordinary Differential Equations and Dynamical Systems (L1367) Lecture 4 6
Ordinary Differential Equations and Dynamical Systems (L1368) Recitation Section (small) 2 3
Module Responsible Prof. Reiner Lauterbach
Admission Requirements None
Recommended Previous Knowledge
  • Analysis
  • Higher Analysis
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts such as modelling with dynamical system, ordinary differential equations as dynamical systems, long time behavior of orbits, hyperbolic systems, linear differential equations and linearisations, structural stability and bifurcations, symbolic dynamic, Hamilton systems and ergodic systems. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Ordinary differential aquations and dynamical systems with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1367: Ordinary Differential Equations and Dynamical Systems
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content
  • Modelling with dynamical systems
  • Ordinary differential equations as dynamical systems (existence, uniqueness)
  • Long time behavior of orbits (predictibility, periodicity, stability, limit sets, attractors)
  • Hyperbolic systems, linear differential equations and linearisations
  • Structural stability and bifurcations
  • Symbolic dynamics
  • Hamilton systems, ergodic systems
Literature
  • H. Amann, Gewöhnliche Differentialgleichungen, de Gruyter 1995
  • C. Chicone, Ordinary Differential Equations with Applications, Springer 2006.
  • H. Heuser, Gewöhnliche Differentialgleichungen, Teubner 2009.
  • M. Hirsch, S. Smale, R. Devaney, Differential equations, dynamical systems, and an introduction to chaos, Elsevier 2004.
  • W. Walter, Gewöhnliche Differentialgleichungen, Springer 2000.


Course L1368: Ordinary Differential Equations and Dynamical Systems
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1060: Optimization

Courses
Title Typ Hrs/wk CP
Optimization (L1333) Lecture 4 6
Optimization (L1334) Recitation Section (small) 2 3
Module Responsible Prof. Michael Hinze
Admission Requirements None
Recommended Previous Knowledge

Linear Algebra

Analysis

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Optimization such as conditions for optimality, globally convergent descent methods, locally fast convergent methods, locally and globally fast convergent methods, numerical methods and duality. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Optimization with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1333: Optimization
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content
  • real world Examples
  • non-restricted optimization
    • necessary and sufficient conditions for optimality
    • globally convergent descent methods, (e.g gradient methods, Trust-Region-methods)
    • locally fast convergentmethods (e.g. Newton and quasi-Newton-methods)
    • locally and globally fast convergent methods (e.g. globalised Newton-method)
  • restricted optimization
    • necessary and sufficient conditions for optimality
    • numerical methods (e.g. Penalty-method, SQP-method)
    • Selected topics (e.g. convex optimization, duality, parametric optimization)
Literature
  • Ulbrich, M. and Ulbrich, S., Nichtlineare Optimierung, Verlag Birkhäuser Basel 2012    
  • C. Geiger and C. Kanzow, Numerische Verfahren zur Lösung unrestringierter Optimierungsaufgaben, Verlag Springer Berlin Heidelberg, 1999
  • C. Geiger and C. Kanzow, Theorie und Numerik restringierter Optimierungsaufgaben, Verlag Springer Berlin Heidelberg, 2002
  • J. Nocedal and S. J. Wright, Numerical Optimization, Verlag: Springer, 1999
  • D. P. Bertsekas, Nonlinear Programming,  Publisher: Athena Scientific,1999, 2nd Edition


 

Course L1334: Optimization
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0852: Graph Theory and Optimization

Courses
Title Typ Hrs/wk CP
Graph Theory and Optimization (L1046) Lecture 2 3
Graph Theory and Optimization (L1047) Recitation Section (small) 2 3
Module Responsible Prof. Anusch Taraz
Admission Requirements None
Recommended Previous Knowledge
  • Discrete Algebraic Structures
  • Mathematics I
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can name the basic concepts in Graph Theory and Optimization. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.
Skills
  • Students can model problems in Graph Theory and Optimization with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 120 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Computer Science: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory
Computer Science: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Computer Science: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Logistics and Mobility: Specialisation Engineering Science: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1046: Graph Theory and Optimization
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Anusch Taraz
Language DE
Cycle SoSe
Content
  • Graphs, search algorithms for graphs, trees
  • planar graphs
  • shortest paths
  • minimum spanning trees
  • maximum flow and minimum cut
  • theorems of Menger, König-Egervary, Hall
  • NP-complete problems
  • backtracking and heuristics
  • linear programming
  • duality
  • integer linear programming

Literature
  • M. Aigner: Diskrete Mathematik, Vieweg, 2004
  • J. Matousek und J. Nesetril: Diskrete Mathematik, Springer, 2007
  • A. Steger: Diskrete Strukturen (Band 1), Springer, 2001
  • A. Taraz: Diskrete Mathematik, Birkhäuser, 2012
  • V. Turau: Algorithmische Graphentheorie, Oldenbourg, 2009
  • K.-H. Zimmermann: Diskrete Mathematik, BoD, 2006
Course L1047: Graph Theory and Optimization
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Anusch Taraz
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1061: Measure Theory and Stochastics

Courses
Title Typ Hrs/wk CP
Measure Theory and Stochastics (L1335) Lecture 3 4
Measure Theory and Stochastics (L1338) Recitation Section (small) 1 2
Module Responsible Prof. Holger Drees
Admission Requirements None
Recommended Previous Knowledge

Mathematical Stochastics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Stochastics auch as general densities, conditional expectation, martingals in discrete time, convergence of probability measures and integral transformations. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Stochastics with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Computational Mathematics: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1335: Measure Theory and Stochastics
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content
  • General densities, Radon-Nikodym theorem
  • Conditional expectation, Markov kernels
  • Martingals in discrete time
  • Convergence of probability measures
  • Integral transformations (e.g. generating functions, Fourier transformation, Laplace transformation)
Literature
  • H. Bauer, Maß- und Integrationstheorie, de Gruyter Lehrbuch, Auflage: 2., überarb. A. (1. Juli 1992)
  • H. Bauer, Wahrscheinlichkeitstheorie, de Gruyter Lehrbuch, Verlag: de Gruyter; Auflage: 5. durchges. und verb. (2002)
  • J. Estrodt, Maß- und Integrationstheorie, Springer, 7., korrigierte und aktualisierte Auflage 2011
Course L1338: Measure Theory and Stochastics
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0714: Numerical Treatment of Ordinary Differential Equations

Courses
Title Typ Hrs/wk CP
Numerical Treatment of Ordinary Differential Equations (L0576) Lecture 2 3
Numerical Treatment of Ordinary Differential Equations (L0582) Recitation Section (small) 2 3
Module Responsible Prof. Sabine Le Borne
Admission Requirements None
Recommended Previous Knowledge
  • Mathematik I, II, III für Ingenieurstudierende (deutsch oder englisch) oder Analysis & Lineare Algebra I + II sowie Analysis III für Technomathematiker
  • Basic MATLAB knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  • list numerical methods for the solution of ordinary differential equations and explain their core ideas,
  • repeat convergence statements for the treated numerical methods (including the prerequisites tied to the underlying problem),
  • explain aspects regarding the practical execution of a method.
  • select the appropriate numerical method for concrete problems, implement the numerical algorithms efficiently and interpret the numerical results
Skills

Students are able to

  • implement (MATLAB), apply and compare numerical methods for the solution of ordinary differential equations,
  • to justify the convergence behaviour of numerical methods with respect to the posed problem and selected algorithm,
  • for a given problem, develop a suitable solution approach, if necessary by the composition of several algorithms, to execute this approach and to critically evaluate the results.


Personal Competence
Social Competence

Students are able to

  • work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge), explain theoretical foundations and support each other with practical aspects regarding the implementation of algorithms.
Autonomy

Students are capable

  • to assess whether the supporting theoretical and practical excercises are better solved individually or in a team,
  • to assess their individual progress and, if necessary, to ask questions and seek help.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory
Chemical and Bioprocess Engineering: Specialisation Chemical Process Engineering: Elective Compulsory
Chemical and Bioprocess Engineering: Specialisation General Process Engineering: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Energy Systems: Core qualification: Elective Compulsory
Aircraft Systems Engineering: Specialisation Aircraft Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Mathematical Modelling in Engineering: Theory, Numerics, Applications: Specialisation l. Numerics (TUHH): Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Core qualification: Compulsory
Process Engineering: Specialisation Chemical Process Engineering: Elective Compulsory
Process Engineering: Specialisation Process Engineering: Elective Compulsory
Course L0576: Numerical Treatment of Ordinary Differential Equations
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne, Dr. Patricio Farrell
Language DE/EN
Cycle SoSe
Content

Numerical methods for Initial Value Problems

  • single step methods
  • multistep methods
  • stiff problems
  • differential algebraic equations (DAE) of index 1

Numerical methods for Boundary Value Problems

  • multiple shooting method
  • difference methods
  • variational methods


Literature
  • E. Hairer, S. Noersett, G. Wanner: Solving Ordinary Differential Equations I: Nonstiff Problems
  • E. Hairer, G. Wanner: Solving Ordinary Differential Equations II: Stiff and Differential-Algebraic Problems
Course L0582: Numerical Treatment of Ordinary Differential Equations
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne, Dr. Patricio Farrell
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1083: Discrete Mathematics

Courses
Title Typ Hrs/wk CP
Discrete Mathematics (L1379) Lecture 4 6
Discrete Mathematics (L1380) Recitation Section (small) 2 3
Module Responsible Prof. Matthias Schacht
Admission Requirements None
Recommended Previous Knowledge

Linear Algebra

Geometry

Analysis
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Discrete Mathematics such as elementary combinatorics and counting coefficients, sorting algorithms, graphs and network algorithms, complexity, asymptotic analysis, discrete probability distributions, generating functions, the principle of inclusion and exclusion, ordered sets, counting of trees and patterns and fundamentals in coding theory or cryptography.
  • They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Combinatorics with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course. 
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1379: Discrete Mathematics
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content
  • Introduction to discrete mathematics
  • Topics:
    • Combinatorial problems and counting coefficients
    • Sorting algorithms
    • Fundamentals of graph theory
    • Graph and Network algorithms
    • Complexity
    • Asymptotic analysiy
    • Diskrete probability distributions
    • Generating functions (ring of formal power series)
    • Inclusion and exklusion principle
    • oredered sets (Möbius inversion)
    • Counting of trees and patterns
    • Fundamentals in coding theory or cryptography
Literature
  • M. Aigner: Diskrete Mathematik, Vieweg, 6., korr. Aufl. 2006
  • L. Lovász, J. Pelikan & K. Vesztergombi Diskrete Mathematik, Springer, 2005
  • J. Matoušek & J. Nešetřil: Diskrete Mathematik - Eine Entdeckungsreise, Springer, 2007
  • A. Steger: Diskrete Strukturen - Band 1: Kombinatorik, Graphentheorie, Algebra, Springer, 2. Aufl. 2007
  • A. Taraz: Diskrete Mathematik - Grundlagen und Methoden, Birkhäuser, 2012
Course L1380: Discrete Mathematics
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0561: Discrete Algebraic Structures

Courses
Title Typ Hrs/wk CP
Discrete Algebraic Structures (L0164) Lecture 2 3
Discrete Algebraic Structures (L0165) Recitation Section (small) 2 3
Module Responsible Prof. Karl-Heinz Zimmermann
Admission Requirements None
Recommended Previous Knowledge Mathematics from High School.
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students know the important basics of discrete algebraic structures including elementary combinatorial structures, monoids, groups, rings, fields, finite fields, and vector spaces. They also know specific structures like sub-. sum-, and quotient structures and homomorphisms. 

Skills

Students are able to formalize and analyze basic discrete algebraic structures.

Personal Competence
Social Competence

Students are able to solve specific problems alone or in a group and to present the results accordingly.

Autonomy

Students are able to acquire new knowledge from specific standard books and to associate the acquired knowledge to other classes.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 120 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Computer Science: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory
Computer Science: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Computer Science: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L0164: Discrete Algebraic Structures
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Karl-Heinz Zimmermann
Language DE
Cycle WiSe
Content
Literature
Course L0165: Discrete Algebraic Structures
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Karl-Heinz Zimmermann
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0716: Hierarchical Algorithms

Courses
Title Typ Hrs/wk CP
Hierarchical Algorithms (L0585) Lecture 2 3
Hierarchical Algorithms (L0586) Recitation Section (small) 2 3
Module Responsible Prof. Sabine Le Borne
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics I, II, III for Engineering students (german or english) or Analysis & Linear Algebra I + II as well as Analysis III for Technomathematicians
  • Programming experience in C
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  • name representatives of hierarchical algorithms and list their characteristics,
  • explain construction techniques for hierarchical algorithms,
  • discuss aspects regarding the efficient implementation of hierarchical algorithms.
Skills

Students are able to

  • implement the hierarchical algorithms discussed in the lecture,
  • analyse the storage and computational complexities of the algorithms,
  • adapt algorithms to problem settings of various applications and thus develop problem adapted variants.
Personal Competence
Social Competence

Students are able to

  • work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge), explain theoretical foundations and support each other with practical aspects regarding the implementation of algorithms.
Autonomy

Students are capable

  • to assess whether the supporting theoretical and practical excercises are better solved individually or in a team,
  • to work on complex problems over an extended period of time,
  • to assess their individual progess and, if necessary, to ask questions and seek help.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Oral exam
Examination duration and scale 20 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Computational Science and Engineering: Specialisation Kernfächer Mathematik (2 Kurse): Elective Compulsory
Mathematical Modelling in Engineering: Theory, Numerics, Applications: Specialisation ll. Modelling and Simulation of Complex Systems (TUHH): Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0585: Hierarchical Algorithms
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne
Language DE/EN
Cycle WiSe
Content
  • Low rank matrices
  • Separable expansions
  • Hierarchical matrix partitions
  • Hierarchical matrices
  • Formatted matrix operations
  • Applications
  • Additional topics (e.g. H2 matrices, matrix functions, tensor products)
Literature W. Hackbusch: Hierarchische Matrizen: Algorithmen und Analysis
Course L0586: Hierarchical Algorithms
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1020: Numerics of Partial Differential Equations

Courses
Title Typ Hrs/wk CP
Numerics of Partial Differential Equations (L1247) Lecture 2 3
Numerics of Partial Differential Equations (L1248) Recitation Section (small) 2 3
Module Responsible Prof. Sabine Le Borne
Admission Requirements None
Recommended Previous Knowledge
  • Mathematik I - IV (for Engineering Students) or Analysis & Linear Algebra I + II for Technomathematicians
  • Numerical mathematics 1
  • Numerical treatment of ordinary differential equations
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can classify partial differential equations according to the three basic types.
  • For each type, students know suitable numerical approaches.
  • Students know the theoretical convergence results for these approaches.
Skills Students are capable to formulate solution strategies for given problems involving partial differential equations, to comment on theoretical properties concerning convergence and to implement and test these methods in practice.
Personal Competence
Social Competence

Students are able to work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge) and to explain theoretical foundations.

Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Oral exam
Examination duration and scale 25 min
Assignment for the Following Curricula Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Course L1247: Numerics of Partial Differential Equations
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne, Dr. Patricio Farrell
Language DE/EN
Cycle WiSe
Content

Elementary Theory and Numerics of PDEs

  • types of PDEs
  • well posed problems
  • finite differences
  • finite elements
  • finite volumes
  • applications
Literature

Dietrich Braess: Finite Elemente: Theorie, schnelle Löser und Anwendungen in der Elastizitätstheorie, Berlin u.a., Springer 2007

Susanne Brenner, Ridgway Scott: The Mathematical Theory of Finite Element Methods, Springer, 2008

Peter Deuflhard, Martin Weiser: Numerische Mathematik 3
Course L1248: Numerics of Partial Differential Equations
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne, Dr. Patricio Farrell
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1063: Stochastic Processes

Courses
Title Typ Hrs/wk CP
Stochastic Processes (L1343) Lecture 3 4
Stochastic Processes (L1344) Recitation Section (small) 1 2
Module Responsible Prof. Holger Drees
Admission Requirements None
Recommended Previous Knowledge

Mathematical Stochastics

Measure Theory and Stochastics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts such as the classification and construction of stochastic processes, Markov processes with discrete state space in discrete and continuous time, renewal theory, general Markov processes and Markov semigroups, Poisson processes and Brownian motion. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Stochastic Processes with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1343: Stochastic Processes
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content
  • Classification and construction of stochastic processes, existence theorems
  • Markov processes with discrete state space in discrete and continuous time
  • Renewal theory
  • General Markov processes and Markov semigroups
  • Poisson processes, Brownian motion
Literature
  • Asmussen, S.: Applied Probability and Queues, 2.ed., Springer, New York 2003
  • Chung, K.L.: Markov Chains, 2.ed., Springer Berlin 1967
  • Grimmett, G.; Stirzaker, D.R.: Probability and Random Processes, 3.ed., Oxford University Press, Oxford 2009
  • Karlin, S.; Taylor, H.M.: A First Course in Stochastic Processes, 2.ed., Academic Press, New York 1975
  • Resnick, S.I.: Adventures in Stochastic Processes, 2.pr., Birkhäuser, Boston 1994
  • Stroock, D.W.: An Introduction to Markov Processes, Springer, New York 2005
Course L1344: Stochastic Processes
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0881: Mathematical Image Processing

Courses
Title Typ Hrs/wk CP
Mathematical Image Processing (L0991) Lecture 3 4
Mathematical Image Processing (L0992) Recitation Section (small) 1 2
Module Responsible Prof. Marko Lindner
Admission Requirements None
Recommended Previous Knowledge
  • Analysis: partial derivatives, gradient, directional derivative
  • Linear Algebra: eigenvalues, least squares solution of a linear system
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to 

  • characterize and compare diffusion equations
  • explain elementary methods of image processing
  • explain methods of image segmentation and registration
  • sketch and interrelate basic concepts of functional analysis 
Skills

Students are able to 

  • implement and apply elementary methods of image processing  
  • explain and apply modern methods of image processing
Personal Competence
Social Competence

Students are able to work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge) and to explain theoretical foundations.

Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Oral exam
Examination duration and scale 20 min
Assignment for the Following Curricula Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Computational Science and Engineering: Specialisation Kernfächer Mathematik (2 Kurse): Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Process Engineering: Specialisation Process Engineering: Elective Compulsory
Course L0991: Mathematical Image Processing
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Marko Lindner
Language DE/EN
Cycle WiSe
Content
  • basic methods of image processing
  • smoothing filters
  • the diffusion / heat equation
  • variational formulations in image processing
  • edge detection
  • image segmentation
  • image registration
Literature Bredies/Lorenz: Mathematische Bildverarbeitung
Course L0992: Mathematical Image Processing
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Marko Lindner
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1059: Approximation

Courses
Title Typ Hrs/wk CP
Approximation (L1331) Lecture 4 6
Approximation (L1332) Recitation Section (small) 2 3
Module Responsible Prof. Armin Iske
Admission Requirements None
Recommended Previous Knowledge

Linear Algebra

Analysis

Introduction to Numerical Analysis
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Approximation such as L2 approximation, Tschebychev approximation and Remez methods, approximation of periodic functions, Fourier series, splines, representation of curves and surfaces, and wavelets and radial basis function. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Approximation with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1331: Approximation
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content
  • L2 approximation
  • Tschebychev approximation and Remez methods
  • Approximation of periodic functions, Fourier series
  • Interpolation and approximation by splines
  • Representation of curves and surfaces
  • Wavelets and radial basis functions
Literature
  • DeVore, Ronald A. und Lorentz, George G.: Constructive Approximation, Springer, 1993.
  • Powell, Michael J. D.: Approximation theory and methods, Cambridge University Press, 1981.
  • Cheney, Elliot W. und Light, William A.: A course in approximation theory, Brooks/Cole Publishing, 2000.
Course L1332: Approximation
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1058: Introduction to Mathematical Modeling

Courses
Title Typ Hrs/wk CP
Introduction in Mathematical Modeling (L1329) Lecture 4 6
Introduction in Mathematical Modeling (L1330) Recitation Section (small) 2 3
Module Responsible Prof. Ingenuin Gasser
Admission Requirements None
Recommended Previous Knowledge
  • Analysis
  • Linear Algebra
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Mathematical Modeling such as he modelling process, deterministic and stochastic models, modelling of dynamic processes, and discrete and continuous models. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Mathematical Modeling with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1329: Introduction in Mathematical Modeling
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content
  • The modelling process
  • deterministic and stochastic models
  • modelling of dynamic processes
  • discrete and continuous models
Literature
  • C.P. Ortlieb, C. v. Dresky, I. Gasser, S. Günzel : Mathematische Modellierung - Eine Einführung in zwölf Fallstudien, 2. Auflage, Vieweg+Teubner (2012)
  • Richard Haberman : Mathematical Models: Mechanical Vibrations, Population Dynamics, and Traffic Flow. Classics in Mathematics 21, SIAM (1998).
  • C. C. Lin und L. A. Segal: Mathematics Applied to Deterministic Problems in the natural Sciences, SIAM (1988)
  • C. Eck, H. Garcke, P. Knabner: Mathematische Modellierung. Springer (2008)
Course L1330: Introduction in Mathematical Modeling
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1078: Geometry

Courses
Title Typ Hrs/wk CP
Geometry (L1363) Lecture 4 6
Geometry (L1364) Recitation Section (small) 2 3
Module Responsible Prof. Alexander Kreuzer
Admission Requirements None
Recommended Previous Knowledge

Linear Algebra

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Geometry such as affine and projective planes and spaces, coordinatisation, collineations, fundamental theorems and applications of geometry. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Geometry with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Course L1363: Geometry
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content
  • Affine and projective planes and spaces
  • Coordinatisation
  • Collineations
  • Fundamental theorems
  • Applications of geometry
Literature
  1. M. Berger, Geometry I, Verlag: Springer, 1987
  2. A. Beutelspacher und U. Rosenbaum, Projektive Geometrie, Verlag Vieweg, 1992
  3. H. Brauner, Geometrie projektiver Räume I, II,  BI, 1976
  4. F. Buckenhout (Hrsg.), Handbook of Incidence Geometry, Verlag: Elsevier, 1995
  5. R. Casse, Projective Geometry: An Introduction, Verlag: Oxford University Press, 2009
  6. A. Herzer, Geometrie I,II, Skript, Universität Mainz, 1991/92
  7. A. Holme, Geometry: Our Cultural Heritage, Verlag: Springer, 2002
  8. D.R. Hughes und F.C. Piper, Projective Planes, Verlag: Springer, 1973
  9. G.A. Jennings, Modern Geometry with Applications, Verlag: Springer, 1994
  10. L. Kadison und M.T. Kromann, Projective Geometry and Modern Algebra, Verlag: Birkhäuser , 1996
  11. H. Karzel und H.-J. Kroll, Geschichte der Geometrie seit Hilbert, Verlag: Wiss. Buchgesellschaft, 1988
  12. H. Karzel, K. Sörensen und D. Windelberg, Einführung in die Geometrie, Verlag: Vandenhoeck und Rupprecht, 1973
  13. H. Lenz, Vorlesungen über projektive Geometrie, Akad. Verl.-Ges., 1965
  14. R. Lingenberg, Grundlagen der Geometrie, BI, 1978
  15. E.M. Schröder, Vorlesungen über Geometrie, II, BI., 1991
  16. C.J. Scriba und P. Schreiber, 5000 Jahre Geometrie, Verlag: Springer, 2001
  17. J. Ueberberg, Foundations of Incidence Geometry: Projective and Polar Spaches, Verlag: Springer, 2011
Course L1364: Geometry
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1129: Mathematical Systems Theory

Courses
Title Typ Hrs/wk CP
Mathematical Systems Theory (L1463) Lecture 2 3
Mathematical Systems Theory (L1465) Seminar 1 2
Mathematical Systems Theory (L1464) Recitation Section (small) 1 1
Module Responsible Prof. Timo Reis
Admission Requirements None
Recommended Previous Knowledge Analysis, Higher Analysis, Functional Analysis
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Mathematical Systems Theory such as controllability, stabilization by feedback, obervability, observer and controller design and linear-quadratic optimal control. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.
Skills
  • Students can model problems in Mathematical Systems Theor with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.
Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language. 
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.
Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Core qualification: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1463: Mathematical Systems Theory
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language EN
Cycle WiSe
Content

Systems Theory treats the mathematical background and foundations of the engineering discipline 'Cybernetics'. Thereby one wants to exert influence on a dynamical system (which is usually given by an ordinary differential equation (ODE)), such that a desired behavior is achieved.
For instance, in classical mechanics, the motion of a mass point is determined by acting forces. In 'Systems and Control Theory', one wonders how these forces have to be chosen such that a prescribed movement of the mass point is accomplished.

  • Introduction and motivation  
  • Controllability
  • Stabilization by feedback  
  • Obervability  
  • Observer and controller design  
  • Linear-quadratic optimal control     
Literature
  • E.D. Sontag, Mathematical Control Theory: Deterministic Finite Dimensional Systems. Second Edition, Springer, New York, 1998
  • T. Kailath, Linear Systems. Prentice-Hall, Englewood Cliffs, 1980
  • H.W. Knobloch, H. Kwakernaak. Lineare Kontrolltheorie. Springer-Verlag, Berlin, 1985
  • K. Zhou, J.C. Doyle, K. Glover. Robust and Optimal Control. Prentice Hall, Upper Saddle River, NJ, 1996 
Course L1465: Mathematical Systems Theory
Typ Seminar
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L1464: Mathematical Systems Theory
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0941: Combinatorial Structures and Algorithms

Courses
Title Typ Hrs/wk CP
Combinatorial Structures and Algorithms (L1100) Lecture 3 4
Combinatorial Structures and Algorithms (L1101) Recitation Section (small) 1 2
Module Responsible Prof. Anusch Taraz
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics I + II
  • Discrete Algebraic Structures
  • Graph Theory and Optimization
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can name the basic concepts in Combinatorics and Algorithms. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Combinatorics and Algorithms with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Computational Mathematics: Elective Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Mathematics & Engineering Science: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1100: Combinatorial Structures and Algorithms
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Anusch Taraz
Language DE/EN
Cycle WiSe
Content
  • Counting
  • Structural Graph Theory
  • Analysis of Algorithms
  • Extremal Combinatorics
  • Random discrete structures
Literature
  • M. Aigner: Diskrete Mathematik, Vieweg, 6. Aufl., 2006
  • J. Matoušek & J. Nešetřil: Diskrete Mathematik - Eine Entdeckungsreise, Springer, 2007
  • A. Steger: Diskrete Strukturen - Band 1: Kombinatorik, Graphentheorie, Algebra, Springer, 2. Aufl. 2007
  • A. Taraz: Diskrete Mathematik, Birkhäuser, 2012.
Course L1101: Combinatorial Structures and Algorithms
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Anusch Taraz
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1055: Complex Analysis

Courses
Title Typ Hrs/wk CP
Complex Analysis (L1325) Lecture 4 6
Complex Analysis (L1326) Recitation Section (small) 2 3
Module Responsible Prof. Bernd Siebert
Admission Requirements None
Recommended Previous Knowledge
  • Analysis
  • Higher Analysis


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Complex Analysis such as holomorphic functions, Cauchy's integral theorem and formula, the residue theorem, conformal maps, homology and homotopy versions of the residue theorem, analytic functions, Fourier series, harmonic functions, elliptic functions and integrals and the Gamma function. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Complex Analysis with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1325: Complex Analysis
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content
  • complex numbers, sequences and series of complex numbers (recapitulation)
  • real and complex differentiation of complex-valued functions, Wirtinger calculus
  • holomorphic functions
  • Cauchy's integral theorem, Cauchy's integral formula, residue theorem
  • determination of improper (real) integrals via complex methods
  • conformal maps
  • homology and homotopy versions of the residue theorem
  • Maximum principle
  • Counting of zeros and poles
  • Proofs of the fundamental theorem of algebra
  • analytic functions
  • Fourier series
  • harmonic functions
  • The Mittag-Leffler theorem and the Weierstraß factorization theorem
  • Elliptic funktions and integrals
  • Gamma function
Literature
  • W. Fischer, I. Lieb, Einführung in die komplexe Analysis, Verlag: Vieweg+Teubner Verlag; Auflage: 2010
  • Dietmar A. Salamon, Funktionentheorie, Verlag: Springer Basel; Auflage: 2012
  • K. Fritzsche,  Grundkurs Funktionentheorie, Verlag: Spektrum Akademischer Verlag; Auflage: 2009
  • E. Freitag, R. Busam, Funktionentheorie 1,  Verlag: Springer Berlin Heidelberg, 2002 
  • R. Remmert, G. Schumacher,   Funktionentheorie 1, Verlag: Springer Berlin Heidelberg, 2002
  • L.V. Ahlfors, Complex Analysis, Publisher: McGraw-Hill Science/Engineering/Math; 3 edition (January 1, 1979)
  • J.B. Conway, Functions of one complex variable, Springer, 1978


Course L1326: Complex Analysis
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1050: Graph Theory

Courses
Title Typ Hrs/wk CP
Graph Theory (L1311) Lecture 4 6
Graph Theory (L1314) Recitation Section (small) 2 3
Module Responsible Prof. Reinhard Diestel
Admission Requirements None
Recommended Previous Knowledge Linear Algebra
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Graph Theory such as connectivity, matchings, planarity, colourings, infinite graphs, spanning structures and Ramsey theory. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Graph Theory with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.  For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Course L1311: Graph Theory
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content

Fundamentals of Graph Theory, important invariants and their relations
Topics:

  •  Matchings
  • Connectivity
  • Planar graphs
  • Graph coloring
  • Subgraphs and infinite Graphs
  • Ramsey theory
  • Hamilton cycles
  • Random graphs
Literature
  • R.Diestel, Graphentheorie (4. Auflage), Springer 2010
  • R.Diestel, Graph Theory (4th ed'n), GTM 173, Springer 2010/12
Course L1314: Graph Theory
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1051: Combinatorial Optimization

Courses
Title Typ Hrs/wk CP
Combinatorial Optimization (L1315) Lecture 4 6
Combinatorial Optimization (L1316) Recitation Section (small) 2 3
Module Responsible Prof. Matthias Schacht
Admission Requirements None
Recommended Previous Knowledge

Linear Algebra, Discrete Mathematics



Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Combinatorial Optimization such as network algorithms, linear programming and duality, polyhedral combinatorics and NP-complexity theory  They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Combinatorial Optimization with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1315: Combinatorial Optimization
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe/SoSe
Content

Introduction to combinatorial optimization
Topics:

  • Linear optimization: Polyhedra and LP Duality
  • Complexity of algorithms
  • polynomial algorithms for
    • minimal spanning trees
    • shortest paths
    • maximum flows and minimum cost flows
    • maximum matching and linear programs
    • polyhedral combinatorics for NP-hard problems (Knapsack, TSP, Clique Partioning)
Literature
  • William J. Cook, William H. Cunningham, William R. Pulleyblank, Alexander Schrijver: Combinatorial Optimization. John Wiley & Sons, 1997
  • Christos H. Papadimitriou, Kenneth Steiglitz: Combinatorial Optimization: Algorithms and Complexity. Dover Publications, 1998
  • Eugene Lawler: Combinatorial Optimization: Networks and Matroids, Oxford University Press 1995
Course L1316: Combinatorial Optimization
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe/SoSe
Content See interlocking course
Literature See interlocking course

Module M0720: Matrix Algorithms

Courses
Title Typ Hrs/wk CP
Matrix Algorithms (L0984) Lecture 2 3
Matrix Algorithms (L0985) Recitation Section (small) 2 3
Module Responsible Dr. Jens-Peter Zemke
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics I - III
  • Numerical Mathematics 1/ Numerics
  • Basic knowledge of the programming languages Matlab and C
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  1. name, state and classify state-of-the-art Krylov subspace  methods for the solution of the core problems of the engineering sciences, namely, eigenvalue problems, solution of linear systems, and model reduction;
  2. state approaches for the solution of matrix equations (Sylvester, Lyapunov, Riccati).
Skills

Students are capable to

  1. implement and assess basic Krylov subspace methods for the solution of eigenvalue problems, linear systems, and model reduction;
  2. assess methods used in modern software with respect to computing time, stability, and domain of applicability;
  3. adapt the approaches learned to new, unknown types of problem.
Personal Competence
Social Competence

Students can

  • develop and document joint solutions in small teams;
  • form groups to further develop the ideas and transfer them to other areas of applicability;
  • form a team to develop, build, and advance a software library.
Autonomy

Students are able to

  • correctly assess the time and effort of self-defined work;
  • assess whether the supporting theoretical and practical excercises are better solved individually or in a team;
  • define test problems for testing and expanding the methods;
  • assess their individual progess and, if necessary, to ask questions and seek help.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Mathematical Modelling in Engineering: Theory, Numerics, Applications: Specialisation ll. Modelling and Simulation of Complex Systems (TUHH): Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Course L0984: Matrix Algorithms
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Jens-Peter Zemke
Language DE
Cycle WiSe
Content
  • Part A: Krylov Subspace Methods:
    • Basics (derivation, basis, Ritz, OR, MR)
    • Arnoldi-based methods (Arnoldi, GMRes)
    • Lanczos-based methods (Lanczos, CG, BiCG, QMR, SymmLQ, PvL)
    • Sonneveld-based methods (IDR, BiCGStab, TFQMR, IDR(s))
  • Part B: Matrix Equations:
    • Sylvester Equation
    • Lyapunov Equation
    • Algebraic Riccati Equation
Literature Skript
Course L0985: Matrix Algorithms
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Jens-Peter Zemke
Language DE
Cycle WiSe
Content
Literature Siehe korrespondierende Vorlesung

Module M1310: Discrete Differential Geometry

Courses
Title Typ Hrs/wk CP
Discrete Differential Geometry (L1808) Lecture 4 6
Module Responsible Prof. Karl-Heinz Zimmermann
Admission Requirements None
Recommended Previous Knowledge Linear Algebra, Multivariate Calculus 
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

These lectures are on geometrical aspects of the solutions of differential equations and their treatment on the computer. The required basics from linear algebra and analysis are reviewed at the beginning. Applications are to curved surfaces in space, to mechanics and mechatronics, to different types of field equations, and to the tranfer of mathematical constructions to data types, compiler functions, programming languages, and special compute circuits.

- basic prerequisites from linear algebra, tensors, exterior algebra, Clifford algebras

- basic prerequisites from coordinate-free analysis, vector fields and differential forms, integration, discretization

- local differential geometry: connections, symplectic geometry and Hamiltonian systems, Riemannian geometry, discretization

- global differential geometry: manifolds, Lie groups, fiber bundles, random processes, space and time


Skills
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Oral exam
Examination duration and scale 25 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L1808: Discrete Differential Geometry
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Prof. Georg Friedrich Mayer-Lindenberg
Language DE/EN
Cycle SoSe
Content

These lectures deal with geometric aspects of differential equations and with their treatment on the computer. The prerequisites from linear algebra and analysis are reviewed at the beginning. Applications are to curved surfaces, to classical mechanics and mechatronics, to various field equations, to computer graphics and to transferring mathematical constructions to data types, compiler functions, programming languages, and special hardware. Keywords:

Basics from linear algebra, tensors, exterior algebra, Clifford algebras, tuple types

Basics of coordinate-free analysis, vector fields and differential forms, integration, discrete exterior calculus

Local differential geometry: connections, symplectic geometry, Riemannian geometry, discrete mechanics and connections

Global differential geometry: manifolds, Lie groups, fibre bundles, Fourier decompositions, random processes, space and time


Literature

Agricola, Friedrich,  Vektoranalysis,  Vieweg/Teubner 2010

A.C. Da Silva,  Lectures on Symplectic Geometry, Springer L.N. Math. 1764

J. Snygg, Differential Geometry using Clifford's Algebra, Birkhäuser 2010

T. Frankel, The Geometry of Physics, Cambridge U. P. 2012

M.Desbrun et al., Discrete exterior calculus, arXiv:math/0508341v2

J.Marsden  et al., Discrete Mechanics and Variational Integrators, Acta numerica. 2001

Module M0711: Numerical Mathematics II

Courses
Title Typ Hrs/wk CP
Numerical Mathematics II (L0568) Lecture 2 3
Numerical Mathematics II (L0569) Recitation Section (small) 2 3
Module Responsible Prof. Sabine Le Borne
Admission Requirements None
Recommended Previous Knowledge
  • Numerical Mathematics I
  • MATLAB knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  • name advanced numerical methods for interpolation, integration, linear least squares problems, eigenvalue problems, nonlinear root finding problems and explain their core ideas,
  • repeat convergence statements for the numerical methods,
  • sketch convergence proofs,
  • explain practical aspects of numerical methods concerning runtime and storage needs


    explain aspects regarding the practical implementation of numerical methods with respect to computational and storage complexity.


Skills

Students are able to

  • implement, apply and compare advanced numerical methods in MATLAB,
  • justify the convergence behaviour of numerical methods with respect to the problem and solution algorithm and to transfer it to related problems,
  • for a given problem, develop a suitable solution approach, if necessary through composition of several algorithms, to execute this approach and to critically evaluate the results


Personal Competence
Social Competence

Students are able to

  • work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge), explain theoretical foundations and support each other with practical aspects regarding the implementation of algorithms.
Autonomy

Students are capable

  • to assess whether the supporting theoretical and practical excercises are better solved individually or in a team,
  • to assess their individual progess and, if necessary, to ask questions and seek help.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Oral exam
Examination duration and scale 25 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Computational Science and Engineering: Specialisation Information and Communication Technology: Elective Compulsory
Computational Science and Engineering: Specialisation Kernfächer Mathematik (2 Kurse): Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0568: Numerical Mathematics II
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne, Dr. Patricio Farrell
Language DE/EN
Cycle SoSe
Content
  1. Error and stability: Notions and estimates
  2. Interpolation: Rational and trigonometric interpolation
  3. Quadrature: Gaussian quadrature, orthogonal polynomials
  4. Linear systems: Perturbation theory of decompositions, structured matrices
  5. Eigenvalue problems: LR-, QD-, QR-Algorithmus
  6. Krylov space methods: Arnoldi-, Lanczos methods
Literature
  • Stoer/Bulirsch: Numerische Mathematik 1, Springer
  • Dahmen, Reusken: Numerik für Ingenieure und Naturwissenschaftler, Springer
Course L0569: Numerical Mathematics II
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne, Dr. Patricio Farrell
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1053: Introductory Number Theory

Courses
Title Typ Hrs/wk CP
Number Theory (L1319) Lecture 4 6
Number Theory (L1320) Recitation Section (small) 2 3
Module Responsible Prof. Ulf Kühn
Admission Requirements None
Recommended Previous Knowledge

Linear Algebra

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Number Theory such as congruences,  quadratic remainders, ring of integers and diophantic problems. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Number Theory with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Course L1319: Number Theory
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe/SoSe
Content
  • Congruences (chinese remainder theorem, Fermat's little problem, application to asymmetric cryptography)
  • Quadratic Remainders (Legendre symbol, quadratic reciprocity)
  • Properties of the ring of integers (units, ideals, classes of ideals)
  • Application to diophantic problems
Literature
  • A. Beutelspacher, M.-A. Zschiegner: Diskrete Mathematik für Einsteiger. Vieweg
  • F. Ischebeck: Einladung zur Zahlentheorie. BI
  • J. Kramer: Zahlen für Einsteiger. Vieweg
  • K. Reiss, G. Schmieder: Basiswissen Zahlentheorie. Springer
Course L1320: Number Theory
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe/SoSe
Content See interlocking course
Literature See interlocking course

Module M1054: Topology

Courses
Title Typ Hrs/wk CP
Topology (L1322) Lecture 4 6
Topology (L1323) Recitation Section (small) 2 3
Module Responsible Prof. Birgit Richter
Admission Requirements None
Recommended Previous Knowledge
  • Linear Algebra
  • Analysis
  • Higher Analysis
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can name basic concepts in Topology auch as metric and topological spaces, separation axioms, subspace, quotient and product topologies, connecticity and compactnes, homotopy, fundamental groups and covering spaces. They are able to explain them using appropriate examples. 
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Topology with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course. 
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 186, Study Time in Lecture 84
Credit points 9
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Course L1322: Topology
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content
  • set theoretic topology
    • metric and topological spaces
    • separation axiom
    • subspace, quotient and product topologies
    • connecticity
    • compactness
  • algebraic topology
    • homotopy
    • fundamental groups
    • covering spaces
Literature
  • J. Munkres, Topology - a first course, Publisher: Prentice Hall College Div (June 1974)
  • B. v. Querenburg, Mengentheoretische Topologie, Verlag: Springer; Auflage: 3 (4. Oktober 2013)
  • G. Laures, M. Szymik,  Grundkurs Topologie, Verlag: Spektrum Akademischer Verlag; Auflage: 2009
  • K. Jänich,  Topologie,Verlag: Springer; Auflage: 8. Aufl. 2005. 4., korr. Nachdruck 2008
  • L.A. Steen, J.A. Seebach, Jr.,  Counterexamples in Topology, Publisher: Dover Publications (September 22, 1995)
  • O. Viro, O. Ivanov, N. Netsvetaev, V. Kharlamov, Elementary Topology - Problem Textbook, Publisher: American Mathematical Society (September 17, 2008)
  • A. Hatcher, Algebraic Topology, Verlag: Cambridge University Press (2002)


Course L1323: Topology
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1077: Foundations of Mathematical Logic

Courses
Title Typ Hrs/wk CP
Foundations of Mathematical Logic (L1361) Lecture 2 3
Foundations of Mathematical Logic (L1362) Recitation Section (small) 1 2
Module Responsible Prof. Benedikt Loewe
Admission Requirements None
Recommended Previous Knowledge

Linear Algebra

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Mathematical Logic such as formal languages, predicate logic, the completeness theorem, the compactness theorem and the Löwenheim-Skolem theorems. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Mathematical Logic with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 108, Study Time in Lecture 42
Credit points 5
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Course L1361: Foundations of Mathematical Logic
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe/SoSe
Content
Literature
  • J.L. Bell & A.B. Slomson. Models and ultraproducts: an introduction. Dover Publ. 2006 (republication of the third printing 1974 by North-Holland Publ. Co.). Im Internet Buchhandel für ca. 15 € erhältlich.
  • S. Burris and H.P. Sankappanavar. A course in universal algebra.
  • http://www.math.uwaterloo.ca/~snburris/htdocs/UALG/univ-algebra.pdf
Course L1362: Foundations of Mathematical Logic
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe/SoSe
Content See interlocking course
Literature See interlocking course

Module M1076: Set Theory

Courses
Title Typ Hrs/wk CP
Set Theory (L1359) Lecture 2 3
Set Theory (L1360) Recitation Section (small) 1 2
Module Responsible Prof. Benedikt Loewe
Admission Requirements None
Recommended Previous Knowledge Linear Algebra
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Set Theory such as Zermelo-Fraenkel axioms, Ordinal and Cardinal numbers and the Axiom of choice. 
  • They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Set Theory ith the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language.
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 108, Study Time in Lecture 42
Credit points 5
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Course L1359: Set Theory
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe/SoSe
Content
  • Fundamentals of naive set theory
  • Zermelo-Fraenkel axioms
  • Ordinal numbers
  • Cardinal numbers
  • Axiom of choice
Literature

Heinz-Dieter Ebbinghaus, Einfuehrung in die Mengenlehre.

Course L1360: Set Theory
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe/SoSe
Content See interlocking course
Literature See interlocking course

Module M1086: Practical Statistics

Courses
Title Typ Hrs/wk CP
Practical Statistics (L1394) Lecture 2 3
Practical Statistics (L1395) Recitation Section (small) 1 2
Module Responsible Prof. Natalie Neumeyer
Admission Requirements None
Recommended Previous Knowledge
  • Mathematical Stochastics
  • Mathematical Statistics
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can describe basic concepts in Practical Statistics such as nonparametric methods, linear models and multivariate methods. They are able to explain them using appropriate examples.
  • Students can discuss logical connections between these concepts.  They are capable of illustrating these connections with the help of examples.
  • They know proof strategies and can reproduce them.


Skills
  • Students can model problems in Practical Statistics with the help of the concepts studied in this course. Moreover, they are capable of solving them by applying established methods.
  • Students are able to discover and verify further logical connections between the concepts studied in the course.
  • For a given problem, the students can develop and execute a suitable approach, and are able to critically evaluate the results.


Personal Competence
Social Competence
  • Students are able to work together in teams. They are capable to use mathematics as a common language. 
  • In doing so, they can communicate new concepts according to the needs of their cooperating partners. Moreover, they can design examples to check and deepen the understanding of their peers.


Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.


Workload in Hours Independent Study Time 108, Study Time in Lecture 42
Credit points 5
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Course L1394: Practical Statistics
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe/SoSe
Content
  • Nonparametric methods
  • Linear models
  • Multivariate methods
Literature
  • P. Dalgaard, Introductory Statistics with R, Springer
  • J. Verzani, Using R for introductory statistics, Chapman & Hall
  • U. Ligges, Programmieren mit R, Springer
Course L1395: Practical Statistics
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE/EN
Cycle WiSe/SoSe
Content See interlocking course
Literature See interlocking course

Specialization II. Informatics

Module M0732: Software Engineering

Courses
Title Typ Hrs/wk CP
Software Engineering (L0627) Lecture 2 3
Software Engineering (L0628) Recitation Section (small) 2 3
Module Responsible Prof. Sibylle Schupp
Admission Requirements None
Recommended Previous Knowledge
  • Automata theory and formal languages
  • Procedural programming or Functional programming
  • Object-oriented programming, algorithms, and data structures
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students explain the phases of the software life cycle, describe the fundamental terminology and concepts of software engineering, and paraphrase the principles of structured software development. They give examples of software-engineering tasks of existing large-scale systems. They write test cases for different test strategies and devise specifications or models using different notations, and critique both. They explain simple design patterns and the major activities in requirements analysis, maintenance, and project planning.

Skills

For a given task in the software life cycle, students identify the corresponding phase and select an appropriate method. They choose the proper approach for quality assurance. They design tests for realistic systems, assess the quality of the tests, and find errors at different levels. They apply and modify non-executable artifacts. They integrate components based on interface specifications.

Personal Competence
Social Competence

Students practice peer programming. They explain problems and solutions to their peer. They communicate in English. 

Autonomy

Using on-line quizzes and accompanying material for self study, students can assess their level of knowledge continuously and adjust it appropriately.  Working on exercise problems, they receive additional feedback.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung
Compulsory Bonus Form Description
Yes 15 % Excercises
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computer Science: Core qualification: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Course L0627: Software Engineering
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sibylle Schupp
Language EN
Cycle SoSe
Content


  • Software Life Cycle Models (Waterfall, V-Model, Evolutionary Models, IncrementalModels, Iterative Models, Agile Processes)
  • Requirements (Elicitation Techniques, UML Use Case Diagrams, Functional and Non-Functional Requirements)
  • Specification (Finite State Machines, Extended FSMs, Petri Nets, Behavioral UML Diagrams, Data Modeling)
  • Design (Design Concepts, Modules, (Agile) Design Principles)
  • Object-Oriented Analysis and Design (Object Identification, UML Interaction Diagrams, UML Class Diagrams, Architectural Patterns)
  • Testing (Blackbox Testing, Whitebox Testing, Control-Flow Testing, Data-Flow Testing, Testing in the Large)
  • Maintenance and Evolution (Regression Testing, Reverse Engineering, Reengineering)
  • Project Management (Blackbox Estimation Techniques, Whitebox Estimation Techniques, Project Plans, Gantt Charts, PERT Charts)
Literature

Kassem A. Saleh, Software Engineering, J. Ross Publishing 2009.

Course L0628: Software Engineering
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sibylle Schupp
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0624: Automata Theory and Formal Languages

Courses
Title Typ Hrs/wk CP
Automata Theory and Formal Languages (L0332) Lecture 2 4
Automata Theory and Formal Languages (L0507) Recitation Section (small) 2 2
Module Responsible Prof. Tobias Knopp
Admission Requirements None
Recommended Previous Knowledge

Participating students should be able to

- specify algorithms for simple data structures (such as, e.g., arrays) to solve computational problems 

- apply propositional logic and predicate logic for specifying and understanding mathematical proofs

- apply the knowledge and skills taught in the module Discrete Algebraic Structures

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain syntax, semantics, and decision problems of propositional logic, and they are able to give algorithms for solving decision problems. Students can show correspondences to Boolean algebra. Students can describe which application problems are hard to represent with propositional logic, and therefore, the students can motivate predicate logic, and define syntax, semantics, and decision problems for this representation formalism. Students can explain unification and resolution for solving the predicate logic SAT decision problem. Students can also describe syntax, semantics, and decision problems for various kinds of temporal logic, and identify their application areas. The participants of the course can define various kinds of finite automata and can identify relationships to logic and formal grammars. The spectrum that students can explain ranges from deterministic and nondeterministic finite automata and pushdown automata to Turing machines. Students can name those formalism for which nondeterminism is more expressive than determinism. They are also able to demonstrate which decision problems require which expressivity, and, in addition, students can transform decision problems w.r.t. one formalism into decision problems w.r.t. other formalisms. They understand that some formalisms easily induce algorithms whereas others are best suited for specifying systems and their properties. Students can describe the relationships between formalisms such as logic, automata, or grammars.



Skills

Students can apply propositional logic as well as predicate logic resolution to a given set of formulas. Students analyze application problems in order to derive propositional logic, predicate logic, or temporal logic formulas to represent them. They can evaluate which formalism is best suited for a particular application problem, and they can demonstrate the application of algorithms for decision problems to specific formulas. Students can also transform nondeterministic automata into deterministic ones, or derive grammars from automata and vice versa. They can show how parsers work, and they can apply algorithms for the language emptiness problem in case of infinite words.

Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Computer Science: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computer Science: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Computer Science: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Course L0332: Automata Theory and Formal Languages
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Tobias Knopp
Language EN
Cycle SoSe
Content
  1. Propositional logic, Boolean algebra, propositional resolution, SAT-2KNF
  2. Predicate logic, unification, predicate logic resolution
  3. Temporal Logics (LTL, CTL)
  4. Deterministic finite automata, definition and construction
  5. Regular languages, closure properties, word problem, string matching
  6. Nondeterministic automata: 
    Rabin-Scott transformation of nondeterministic into deterministic automata
  7. Epsilon automata, minimization of automata,
    elimination of e-edges, uniqueness of the minimal automaton (modulo renaming of states)
  8. Myhill-Nerode Theorem: 
    Correctness of the minimization procedure, equivalence classes of strings induced by automata
  9. Pumping Lemma for regular languages:
    provision of a tool which, in some cases, can be used to show that a finite automaton principally cannot be expressive enough to solve a word problem for some given language
  10. Regular expressions vs. finite automata:
    Equivalence of formalisms, systematic transformation of representations, reductions
  11. Pushdown automata and context-free grammars:
    Definition of pushdown automata, definition of context-free grammars, derivations, parse trees, ambiguities, pumping lemma for context-free grammars, transformation of formalisms (from pushdown automata to context-free grammars and back)
  12. Chomsky normal form
  13. CYK algorithm for deciding the word problem for context-free grammrs
  14. Deterministic pushdown automata
  15. Deterministic vs. nondeterministic pushdown automata:
    Application for parsing, LL(k) or LR(k) grammars and parsers vs. deterministic pushdown automata, compiler compiler
  16. Regular grammars
  17. Outlook: Turing machines and linear bounded automata vs general and context-sensitive grammars
  18. Chomsky hierarchy
  19. Mealy- and Moore automata:
    Automata with output (w/o accepting states), infinite state sequences, automata networks
  20. Omega automata: Automata for infinite input words, Büchi automata, representation of state transition systems, verification w.r.t. temporal logic specifications (in particular LTL)
  21. LTL safety conditions and model checking with Büchi automata, relationships between automata and logic
  22. Fixed points, propositional mu-calculus
  23. Characterization of regular languages by monadic second-order logic (MSO)
Literature
  1. Logik für Informatiker Uwe Schöning, Spektrum, 5. Aufl.
  2. Logik für Informatiker Martin Kreuzer, Stefan Kühling, Pearson Studium, 2006
  3. Grundkurs Theoretische Informatik, Gottfried Vossen, Kurt-Ulrich Witt, Vieweg-Verlag, 2010.
  4. Principles of Model Checking, Christel Baier, Joost-Pieter Katoen, The MIT Press, 2007

Course L0507: Automata Theory and Formal Languages
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Tobias Knopp
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0731: Functional Programming

Courses
Title Typ Hrs/wk CP
Functional Programming (L0624) Lecture 2 2
Functional Programming (L0625) Recitation Section (large) 2 2
Functional Programming (L0626) Recitation Section (small) 2 2
Module Responsible Prof. Sibylle Schupp
Admission Requirements None
Recommended Previous Knowledge Discrete mathematics at high-school level 
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students apply the principles, constructs, and simple design techniques of functional programming. They demonstrate their ability to read Haskell programs and to explain Haskell syntax as well as Haskell's read-eval-print loop. They interpret warnings and find errors in programs. They apply the fundamental data structures, data types, and type constructors. They employ strategies for unit tests of functions and simple proof techniques for partial and total correctness. They distinguish laziness from other evaluation strategies. 

Skills

Students break a natural-language description down in parts amenable to a formal specification and develop a functional program in a structured way. They assess different language constructs, make conscious selections both at specification and implementations level, and justify their choice. They analyze given programs and rewrite them in a controlled way. They design and implement unit tests and can assess the quality of their tests. They argue for the correctness of their program.

Personal Competence
Social Competence

Students practice peer programming with varying peers. They explain problems and solutions to their peer. They defend their programs orally. They communicate in English.

Autonomy

In programming labs, students learn  under supervision (a.k.a. "Betreutes Programmieren") the mechanics of programming. In exercises, they develop solutions individually and independently, and receive feedback. 

Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Credit points 6
Studienleistung
Compulsory Bonus Form Description
Yes 15 % Excercises
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Computer Science: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computer Science: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Computer Science: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Course L0624: Functional Programming
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Sibylle Schupp
Language EN
Cycle WiSe
Content
  • Functions, Currying, Recursive Functions, Polymorphic Functions, Higher-Order Functions
  • Conditional Expressions, Guarded Expressions, Pattern Matching, Lambda Expressions
  • Types (simple, composite), Type Classes, Recursive Types, Algebraic Data Type
  • Type Constructors: Tuples, Lists, Trees, Associative Lists (Dictionaries, Maps)
  • Modules
  • Interactive Programming
  • Lazy Evaluation, Call-by-Value, Strictness
  • Design Recipes
  • Testing (axiom-based, invariant-based, against reference implementation)
  • Reasoning about Programs (equation-based, inductive)
  • Idioms of Functional Programming
  • Haskell Syntax and Semantics
Literature

Graham Hutton, Programming in Haskell, Cambridge University Press 2007.

Course L0625: Functional Programming
Typ Recitation Section (large)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Sibylle Schupp
Language EN
Cycle WiSe
Content
  • Functions, Currying, Recursive Functions, Polymorphic Functions, Higher-Order Functions
  • Conditional Expressions, Guarded Expressions, Pattern Matching, Lambda Expressions

  • Types (simple, composite), Type Classes, Recursive Types, Algebraic Data Type
  • Type Constructors: Tuples, Lists, Trees, Associative Lists (Dictionaries, Maps)
  • Modules
  • Interactive Programming
  • Lazy Evaluation, Call-by-Value, Strictness
  • Design Recipes
  • Testing (axiom-based, invariant-based, against reference implementation)
  • Reasoning about Programs (equation-based, inductive)
  • Idioms of Functional Programming
  • Haskell Syntax and Semantics

Literature

Graham Hutton, Programming in Haskell, Cambridge University Press 2007.

Course L0626: Functional Programming
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Sibylle Schupp
Language EN
Cycle WiSe
Content
  • Functions, Currying, Recursive Functions, Polymorphic Functions, Higher-Order Functions
  • Conditional Expressions, Guarded Expressions, Pattern Matching, Lambda Expressions

  • Types (simple, composite), Type Classes, Recursive Types, Algebraic Data Type
  • Type Constructors: Tuples, Lists, Trees, Associative Lists (Dictionaries, Maps)
  • Modules
  • Interactive Programming
  • Lazy Evaluation, Call-by-Value, Strictness
  • Design Recipes
  • Testing (axiom-based, invariant-based, against reference implementation)
  • Reasoning about Programs (equation-based, inductive)
  • Idioms of Functional Programming
  • Haskell Syntax and Semantics

Literature

Graham Hutton, Programming in Haskell, Cambridge University Press 2007.

Module M0953: Introduction to Information Security

Courses
Title Typ Hrs/wk CP
Introduction to Information Security (L1114) Lecture 3 3
Introduction to Information Security (L1115) Recitation Section (small) 2 3
Module Responsible Prof. Dieter Gollmann
Admission Requirements None
Recommended Previous Knowledge Basics of Computer Science
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can 

  • name the main security risks when using Information and Communication Systems and name the fundamental security mechanisms, 
  • describe commonly used methods for risk and security analysis,  
  • name the fundamental principles of data protection.
Skills

Students can

  • evaluate the strenghts and weaknesses of the fundamental security mechanisms and of the commonly used methods for risk and security analysis, 

  • apply the fundamental principles of data protection to concrete cases.

Personal Competence
Social Competence Students are capable of appreciating the impact of security problems on  those affected and of the potential responsibilities for their resolution. 
Autonomy None
Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 120 minutes
Assignment for the Following Curricula Computer Science: Core qualification: Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Course L1114: Introduction to Information Security
Typ Lecture
Hrs/wk 3
CP 3
Workload in Hours Independent Study Time 48, Study Time in Lecture 42
Lecturer Prof. Dieter Gollmann
Language EN
Cycle WiSe
Content
  • Fundamental concepts
  • Passwords & biometrics
  • Introduction to cryptography
  • Sessions, SSL/TLS
  • Certificates, electronic signatures
  • Public key infrastructures
  • Side-channel analysis
  • Access control
  • Privacy
  • Software security basics
  • Security management & risk analysis
  • Security evaluation: Common Criteria




Literature

D. Gollmann: Computer Security, Wiley & Sons, third edition, 2011

Ross Anderson: Security Engineering, Wiley & Sons, second edition, 2008


Course L1115: Introduction to Information Security
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Dieter Gollmann
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0972: Distributed Systems

Courses
Title Typ Hrs/wk CP
Distributed Systems (L1155) Lecture 2 3
Distributed Systems (L1156) Recitation Section (small) 2 3
Module Responsible Prof. Volker Turau
Admission Requirements None
Recommended Previous Knowledge
  • Procedural programming
  • Object-oriented programming with Java
  • Networks
  • Socket programming
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students explain the main abstractions of Distributed Systems (Marshalling, proxy, service, address, Remote procedure call, synchron/asynchron system). They describe the pros and cons of different types of interprocess communication. They give examples of existing middleware solutions. The participants of the course know the main architectural variants of distributed systems, including their pros and cons. Students can describe at least three different synchronization mechanisms.

Skills

Students can realize distributed systems using at least three different techniques:

  • Proprietary protocol realized with TCP
  • HTTP as a remote procedure call
  • RMI as a middleware
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 120 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Course L1155: Distributed Systems
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Volker Turau
Language DE
Cycle WiSe
Content
  • Architectures for distributed systems
  • HTTP: Simple remote procedure call
  • Client-Server Architectures
  • Remote procedure call
  • Remote Method Invocation (RMI)
  • Synchronization
  • Distributed Caching
  • Name servers
  • Distributed File systems
Literature
  • Verteilte Systeme – Prinzipien und Paradigmen, Andrew S. Tanenbaum, Maarten van Steen,  Pearson Studium
  • Verteilte Systeme,  G. Coulouris, J. Dollimore, T. Kindberg, 2005, Pearson Studium
Course L1156: Distributed Systems
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Volker Turau
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0549: Scientific Computing and Accuracy

Courses
Title Typ Hrs/wk CP
Verification Methods (L0122) Lecture 2 3
Verification Methods (L1208) Recitation Section (small) 2 3
Module Responsible Prof. Siegfried Rump
Admission Requirements None
Recommended Previous Knowledge

Basic knowledge in numerics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students have deeper knowledge of numerical and semi-numerical methods with the goal to compute principally exact and accurate error bounds. For several fundamental problems they know algorithms with the verification of the correctness of the computed result.

Skills

The students can devise algorithms for several basic problems which compute rigorous error bounds for the solution and analyze the sensitivity with respect to variation of the input data as well.

Personal Competence
Social Competence

The students have the skills to solve problems together in small groups and to present the achieved results in an appropriate manner.

Autonomy

The students are able to retrieve necessary informations from the given literature and to combine them with the topics of the lecture. Throughout the lecture they can check their abilities and knowledge on the basis of given exercises and test questions providing an aid to optimize their learning process.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Process Engineering: Specialisation Process Engineering: Elective Compulsory
Process Engineering: Specialisation Chemical Process Engineering: Elective Compulsory
Course L0122: Verification Methods
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe
Content
  • Fast and accurate interval arithmetic

  • Error-free transformations

  • Verification methods for linear and nonlinear systems

  • Verification methods for finite integrals

  • Treatment of multiple zeros

  • Automatic differentiation

  • Implementation in Matlab/INTLAB

  • Practical applications

Literature

Neumaier: Interval Methods for Systems of Equations. In: Encyclopedia of Mathematics and its  Applications. Cambridge University Press, 1990

S.M. Rump. Verification methods: Rigorous results using floating-point arithmetic. Acta Numerica, 19:287-449, 2010.
Course L1208: Verification Methods
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0625: Databases

Courses
Title Typ Hrs/wk CP
Databases (L0337) Lecture 4 5
Databases (L1150) Project-/problem-based Learning 1 1
Module Responsible NN
Admission Requirements None
Recommended Previous Knowledge

Students should habe basic knowledge in the following areas:

  • Discrete Algebraic Structures
  • Procedural Programming
  • Logic, Automata, and Formal Languages
  • Object-Oriented Programming, Algorithms and Data Structures
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the general architecture of an application system that is based on a database. They describe the syntax and semantics of the Entity Relationship conceptual modeling languages, and they can enumerate basic decision problems and know which features of a domain model can be captured with ER and which features cannot be represented. Furthermore, students can summarize the features of the relational data model, and can describe how ER models can be systematically transformed into the relational data model. Student are able to discuss dependency theory using the operators of relational algebra, and they know how to use relational algebra as a query language. In addition, they can sketch the main modules of the architecture of a database system from an implementation point of view. Storage and index structures as well as query answering and optimization techniques can be explained. The role of transactions can be described in terms of ACID conditions and common recovery mechanisms can be characterized. The students can recall why recursion is important for query languages and describe how Datalog can be used and implemented.They demonstrate how Datalog can be used for information integration. For solving ER decision problems the students can explain description logics with their syntax and semantics, they describe description logic decision problems and explain how these problems can be mapped onto each other. They can sketch the idea of ontology-based data access and can name the main complexity measure in database theory. Last but not least, the students can describe the main features of XML and can explain XPath and XQuery as query languages.

Skills

Students can apply ER for describing domains for which they receive a textual description, and students can transform relational schemata with a given set of functional dependencies into third normal form or even Boyce-Codd normal form. They can also apply relational algebra, SQL, or Datalog to specify queries. Using specific datasets, they can explain how index structures work (e.g., B-trees) and how index structures change while data is added or deleted. They can rewrite queries for better performance of query evaluation. Students can analyse which query language expressivity is required for which application problem. Description logics can be applied for domain modeling, and students can transform ER diagrams into description logics in order to check for consistency and implicit subsumption relations.  They solve data integration problems using Datalog and LAV or GAV rules. Students can apply XPath and Xquery to retrieve certain patterns in XML data.

Personal Competence
Social Competence Students develop an understanding of social structures in a company used for developing real-world products. They know the responsibilities of data analysts, programmers, and managers in the overall production process.
Autonomy
Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Course L0337: Databases
Typ Lecture
Hrs/wk 4
CP 5
Workload in Hours Independent Study Time 94, Study Time in Lecture 56
Lecturer NN
Language EN
Cycle WiSe
Content
  • Architecture of database systems, conceptual data modeling with the Entity Relationship (ER) modeling language
  • Relational data model, referential integrity, keys, foreign keys, functional dependencies (FDs), canonical mapping of entity types and relationship into the relational data model, anomalies
  • Relational algebra as a simple query language
  • Dependency theory, FD closure, canonical cover of FD set, decomposition of relational schemata, multivalued dependencies, normalization, inclusion dependencies
  • Practical query languages and integrity constraints w/o considering a conceptual domain model: SQL 
  • Storage structures, database implementation architecture
  • Index structures
  • Query processing
  • Query optimization
  • Transactions and recovery
  • Query languages with recursion and consideration of a simple conceptual domain model: Datalog
  • Semi-naive evaluation strategy, magic sets transformation
  • Information integration, declarative schema transformation (LAV, GAV), distributed database systems
  • Description logics, syntax, semantics, decision problems, decision algorithms for Abox satisfiability
  • Ontology based data access (OBDA), DL-Lite for formalizing ER diagramms
  • Complexity measure: Data complexity
  • Semistructured databases and query languages: XML and XQuery
Literature
  1. A. Kemper, A. Eickler, Datenbanksysteme - n. Auflage, Oldenbourg, 2010
  2. S. Abiteboul, R. Hull, V. Vianu, Foundations of Databases, Addison-Wesley, 1995
  3. Database Systems, An Application Oriented Approach, Pearson International Edition, 2005
  4. H. Garcia-Molina, J.D. Ullman, J. Widom, Database Systems: The Complete Book, Prentice Hall, 2002

Course L1150: Databases
Typ Project-/problem-based Learning
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer NN
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0863: Numerics and Computer Algebra

Courses
Title Typ Hrs/wk CP
Numerical Mathematics and Computer Algebra (L0115) Lecture 2 3
Numerics and Computer Algebra (L1060) Seminar 2 2
Numerical Mathematics and Computer Algebra (L0117) Recitation Section (small) 1 1
Module Responsible Prof. Siegfried Rump
Admission Requirements None
Recommended Previous Knowledge

Basic knowledge in numerics and discrete mathematics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students know the difference between precision and accuracy. For several basic problems they know how to solve them approximatively and exactly. They can distinguish between efficiently, not efficiently and principally unsolvable problems.

Skills

The students are able to analyze complex problems in mathematics and computer science. In particular they can analyze the sensitivity of the solution. For several problems they can derive best possible algorithms with respect to the accuracy of the computed result.

Personal Competence
Social Competence

The students have the skills to solve problems together in small groups and to present the achieved results in an appropriate manner.

Autonomy

The students are able to retrieve necessary informations from the given literature and to combine them with the topics of the lecture. Throughout the lecture they can check their abilities and knowledge on the basis of given exercises and test questions providing an aid to optimize their learning process.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Computational Mathematics: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Course L0115: Numerical Mathematics and Computer Algebra
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe
Content
  • Basic knowledge in numerical algorithms
  • Algorithms
  • Floating-point arithmetic, IEEE 754
  • Arithmetic by Sunage (Avizienis), Olver, Matula
  • continued fractions

·        Basic Linear Algebra Subroutines (BLAS)

  • Computer Algebra methods
  • Matlab and operator concept
  • Turing machines and computability
  • Church's Axiom
  • Busy Beaver function
  • NP classes
  • Travelling salesman problem
Literature

Higham, N.J.: Accuracy and stability of numerical algorithms, SIAM Publications, Philadelphia, 2nd edition, 2002

Golub, G.H. and Van Loan, Ch.: Matrix Computations, John Hopkins University Press, 3rd edition, 1996

Knuth, D.E.:  The Art of Computer Programming: Seminumerical Algorithms, Vol. 2. Addison Wesley, Reading, Massachusetts, 1969

Course L1060: Numerics and Computer Algebra
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe
Content Seminar accompanying the lectures (q.v. lecture contents)
Literature

Higham, N.J.: Accuracy and stability of numerical algorithms, SIAM Publications, Philadelphia, 2nd edition, 2002

Golub, G.H. and Van Loan, Ch.: Matrix Computations, John Hopkins University Press, 3rd edition, 1996

Knuth, D.E.:  The Art of Computer Programming: Seminumerical Algorithms, Vol. 2. Addison Wesley, Reading, Massachusetts, 1969

Course L0117: Numerical Mathematics and Computer Algebra
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0730: Computer Engineering

Courses
Title Typ Hrs/wk CP
Computer Engineering (L0321) Lecture 3 4
Computer Engineering (L0324) Recitation Section (small) 1 2
Module Responsible Prof. Heiko Falk
Admission Requirements None
Recommended Previous Knowledge

Basic knowledge in electrical engineering

The successful completion of the labs will be honored during the evaluation of the module's examination according to the following rules:

  1. Upon a passed module examination, the student is granted a bonus on the examination's marks due to the successful labs, such that the examination's marks are lifted by 0,3 or 0,4, respectively, up to the next-better grade.
  2. The improvement of the grade 5,0 up to 4,3 and of 4,3 up to 4,0 is not possible.
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

This module deals with the foundations of the functionality of computing systems. It covers the layers from the assembly-level programming down to gates. The module includes the following topics:

  • Introduction
  • Combinational logic: Gates, Boolean algebra, Boolean functions, hardware synthesis, combinational networks
  • Sequential logic: Flip-flops, automata, systematic hardware design
  • Technological foundations
  • Computer arithmetic: Integer addition, subtraction, multiplication and division
  • Basics of computer architecture: Programming models, MIPS single-cycle architecture, pipelining
  • Memories: Memory hierarchies, SRAM, DRAM, caches
  • Input/output: I/O from the perspective of the CPU, principles of passing data, point-to-point connections, busses
Skills

The students perceive computer systems from the architect's perspective, i.e., they identify the internal structure and the physical composition of computer systems. The students can analyze, how highly specific and individual computers can be built based on a collection of few and simple components. They are able to distinguish between and to explain the different abstraction layers of today's computing systems - from gates and circuits up to complete processors.

After successful completion of the module, the students are able to judge the interdependencies between a physical computer system and the software executed on it. In particular, they shall understand the consequences that the execution of software has on the hardware-centric abstraction layers from the assembly language down to gates. This way, they will be enabled to evaluate the impact that these low abstraction levels have on an entire system's performance and to propose feasible options.

Personal Competence
Social Competence

Students are able to solve similar problems alone or in a group and to present the results accordingly.

Autonomy

Students are able to acquire new knowledge from specific literature and to associate this knowledge with other classes.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung
Compulsory Bonus Form Description
Yes 10 % Excercises
Examination Written exam
Examination duration and scale 90 minutes, contents of course and labs
Assignment for the Following Curricula General Engineering Science (German program): Core qualification: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Naval Architecture: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Civil Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Process Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Aircraft Systems Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Product Development and Production: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory
Computer Science: Core qualification: Compulsory
Electrical Engineering: Core qualification: Compulsory
General Engineering Science (English program): Core qualification: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Naval Architecture: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Civil Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Process Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Aircraft Systems Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Product Development and Production: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Mechatronics: Core qualification: Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Course L0321: Computer Engineering
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Heiko Falk
Language DE
Cycle WiSe
Content
  • Introduction
  • Combinational Logic
  • Sequential Logic
  • Technological Foundations
  • Representations of Numbers, Computer Arithmetics
  • Foundations of Computer Architecture
  • Memories
  • Input/Output
Literature
  • A. Clements. The Principles of Computer Hardware. 3. Auflage, Oxford University Press, 2000.
  • A. Tanenbaum, J. Goodman. Computerarchitektur. Pearson, 2001.
  • D. Patterson, J. Hennessy. Rechnerorganisation und -entwurf. Elsevier, 2005.
Course L0324: Computer Engineering
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Heiko Falk
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0834: Computernetworks and Internet Security

Courses
Title Typ Hrs/wk CP
Computer Networks and Internet Security (L1098) Lecture 3 5
Computer Networks and Internet Security (L1099) Recitation Section (small) 1 1
Module Responsible Prof. Andreas Timm-Giel
Admission Requirements None
Recommended Previous Knowledge

Basics of Computer Science

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to explain important and common Internet protocols in detail and classify them, in order to be able to analyse and develop networked systems in further studies and job.

Skills

Students are able to analyse common Internet protocols and evaluate the use of them in different domains.

Personal Competence
Social Competence


Autonomy

Students can select relevant parts out of high amount of professional knowledge and can independently learn and understand it.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 120 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Computer Science: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computer Science: Core qualification: Compulsory
Electrical Engineering: Core qualification: Elective Compulsory
General Engineering Science (English program): Specialisation Computer Science: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Course L1098: Computer Networks and Internet Security
Typ Lecture
Hrs/wk 3
CP 5
Workload in Hours Independent Study Time 108, Study Time in Lecture 42
Lecturer Prof. Andreas Timm-Giel, Prof. Dieter Gollmann
Language EN
Cycle WiSe
Content

In this class an introduction to computer networks with focus on the Internet and its security is given. Basic functionality of complex protocols are introduced. Students learn to understand these and identify common principles. In the exercises these basic principles and an introduction to performance modelling are addressed using computing tasks and (virtual) labs.

In the second part of the lecture an introduction to Internet security is given.

This class comprises:

  • Application layer protocols (HTTP, FTP, DNS)
  • Transport layer protocols (TCP, UDP)
  • Network Layer (Internet Protocol, routing in the Internet)
  • Data link layer with media access at the example of Ethernet
  • Multimedia applications in the Internet
  • Network management
  • Internet security: IPSec
  • Internet security: Firewalls
Literature


  • Kurose, Ross, Computer Networking - A Top-Down Approach, 6th Edition, Addison-Wesley
  • Kurose, Ross, Computernetzwerke - Der Top-Down-Ansatz, Pearson Studium; Auflage: 6. Auflage
  • W. Stallings: Cryptography and Network Security: Principles and Practice, 6th edition



Further literature is announced at the beginning of the lecture.


Course L1099: Computer Networks and Internet Security
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Andreas Timm-Giel, Prof. Dieter Gollmann
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0754: Compiler Construction

Courses
Title Typ Hrs/wk CP
Compiler Construction (L0703) Lecture 2 2
Compiler Construction (L0704) Recitation Section (small) 2 4
Module Responsible Prof. Sibylle Schupp
Admission Requirements None
Recommended Previous Knowledge
  • Practical programming experience
  • Automata theory and formal languages
  • Functional programming or procedural programming
  • Object-oriented programming, algorithms, and data structures
  • Basic knowledge of software engineering
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students explain the workings of a compiler and break down a compilation task in different phases. They apply and modify the major algorithms for compiler construction and code improvement. They can re-write those algorithms in a programming language, run and test them. They choose appropriate internal languages and representations and justify their choice. They explain and modify implementations of existing compiler frameworks and experiment with frameworks and tools. 

Skills

Students design and implement arbitrary compilation phases. They integrate their code in existing compiler frameworks. They organize their compiler code properly as a software project. They generalize algorithms for compiler construction to algorithms that analyze or synthesize software. 

Personal Competence
Social Competence

Students develop the software in a team. They explain problems and solutions to their team members. They present and defend their software in class. They communicate in English.

Autonomy

Students develop their software independently and define milestones by themselves. They receive feedback throughout the entire project. They organize the software project so that they can assess their progress themselves.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Subject theoretical and practical work
Examination duration and scale Software (Compiler)
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Course L0703: Compiler Construction
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Sibylle Schupp
Language EN
Cycle SoSe
Content
  • Lexical and syntactic analysis 

  • Semantic analysis
  • High-level optimization 

  • Intermediate languages and code generation
  • Compilation pipeline
Literature

Alfred Aho, Jeffrey Ullman, Ravi Sethi, and Monica S. Lam, Compilers: Principles, Techniques, and Tools, 2nd edition

Aarne Ranta, Implementing Programming Languages, An Introduction to Compilers and Interpreters, with an appendix coauthored by Markus Forsberg, College Publications, London, 2012

Course L0704: Compiler Construction
Typ Recitation Section (small)
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Sibylle Schupp
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0971: Operating Systems

Courses
Title Typ Hrs/wk CP
Operating Systems (L1153) Lecture 2 3
Operating Systems (L1154) Recitation Section (small) 2 3
Module Responsible Prof. Volker Turau
Admission Requirements None
Recommended Previous Knowledge
  • Object-oriented programming, algorithms, and data structures
  • Procedural programming
  • Experience in using tools related to operating systems such as editors, linkers, compilers
  • Experience in using C-libraries
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students explain the main abstractions process, virtual memory, deadlock, lifelock, and file of operations systems, describe the process states and their transitions, and paraphrase the architectural variants of operating systems. They give examples of existing operating systems and explain their architectures. The participants of the course write concurrent programs using threads, conditional variables and semaphores. Students can describe the variants of realizing a file system. Students explain at least three different scheduling algorithms.

Skills

Students are able to use the POSIX libraries for concurrent programming in a correct and efficient way. They are able to judge the efficiency of a scheduling algorithm for a given scheduling task in a given environment.

Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Computer Science: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computer Science: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Computer Science: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Course L1153: Operating Systems
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Volker Turau
Language DE
Cycle SoSe
Content
  • Architectures for Operating Systems
  • Processes
  • Concurrency
  • Deadlocks
  • Memory organization
  • Scheduling
  • File systems
Literature
  1. Operating Systems, William Stallings, Pearson International Edition
  2. Moderne Betriebssysteme, Andrew Tanenbaum, Pearson Studium


Course L1154: Operating Systems
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Volker Turau
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0562: Computability and Complexity Theory

Courses
Title Typ Hrs/wk CP
Computability and Complexity Theory (L0166) Lecture 2 3
Computability and Complexity Theory (L0167) Recitation Section (small) 2 3
Module Responsible Prof. Karl-Heinz Zimmermann
Admission Requirements None
Recommended Previous Knowledge Discrete Algebraic Structures, Automata Theory, Logic, and Formal Language Theory.
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students known the important machine models of computability, the class of partial recursive functions, universal computability, Gödel numbering of computations, the theorems of Kleene, Rice, and Rice-Shapiro, the concept of decidable and undecidable sets, the word problems for semi-Thue systems, Thue systems, semi-groups, and Post correspondence systems, Hilbert's 10-th problem, and the basic concepts of complexity theory.

Skills

Students are able to investigate the computability of sets and functions and to analyze the complexity of computable functions.

Personal Competence
Social Competence

Students are able to solve specific problems alone or in a group and to present the results accordingly.

Autonomy

Students are able to acquire new knowledge from newer literature and to associate the acquired knowledge with other classes.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Oral exam
Examination duration and scale 20 min
Assignment for the Following Curricula General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computer Science: Core qualification: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Course L0166: Computability and Complexity Theory
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Karl-Heinz Zimmermann
Language DE/EN
Cycle SoSe
Content
Literature
Course L0167: Computability and Complexity Theory
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Karl-Heinz Zimmermann
Language DE/EN
Cycle SoSe
Content
Literature

Module M0758: Application Security

Courses
Title Typ Hrs/wk CP
Application Security (L0726) Lecture 3 3
Application Security (L0729) Recitation Section (small) 2 3
Module Responsible Prof. Dieter Gollmann
Admission Requirements None
Recommended Previous Knowledge Familiarity with Information security, fundamentals of cryptography, Web protocols and the architecture of the Web
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge Students can name current approaches for securing selected applications, in particular of web applications
Skills

Students are capable of

  • performing a security analysis
  • developing security solutions for distributed applications
  • recognizing the limitations of existing standard solutions  




Personal Competence
Social Competence Students are capable of appreciating the impact of security problems on  those affected and of the potential responsibilities for their resolution. 
Autonomy Students are capable of acquiring knowledge independently from professional publications, technical  standards, and other sources, and are capable of applying newly acquired knowledge to new problems. 
Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 120 minutes
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation Information and Communication Technology: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Software: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems: Elective Compulsory
International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Course L0726: Application Security
Typ Lecture
Hrs/wk 3
CP 3
Workload in Hours Independent Study Time 48, Study Time in Lecture 42
Lecturer Prof. Dieter Gollmann
Language EN
Cycle SoSe
Content
  • Email security 
  • Web Services security
  • Security in Web applications
  • Access control
  • Trust Management
  • Trusted Computing
  • Digital Rights Management
  • Security Solutions for selected applications
Literature

Webseiten der OMG, W3C, OASIS, WS-Security, OECD, TCG

D. Gollmann: Computer Security, 3rd edition, Wiley (2011)

R. Anderson: Security Engineering, 2nd edition, Wiley (2008)

U. Lang: CORBA Security, Artech House, 2002

Course L0729: Application Security
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Dieter Gollmann
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0668: Algebra and Control

Courses
Title Typ Hrs/wk CP
Algebra and Control (L0428) Lecture 2 4
Algebra and Control (L0429) Recitation Section (small) 2 2
Module Responsible Dr. Prashant Batra
Admission Requirements None
Recommended Previous Knowledge

Basics of Real Analysis and Linear Algebra of Vector Spaces

and either of:

Introduction to Control Theory

or:

Discrete Mathematics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can

  • Describe input-output systems polynomially
  • Explain factorization approaches to transfer functions
  • Name stabilization conditions for systems in coprime stable factorization.


Skills

Students are able to

  • Undertake a synthesis of stable control loops
  • Apply suitable methods of analysis and synthesis to describe all stable control loops
  • Ensure the fulfillment of specified performance measurements.


Personal Competence
Social Competence After completing the module, students are able to solve subject-related tasks and to present the results.
Autonomy Students are provided with tasks which are exam-related so that they can examine their learning progress and reflect on it.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Computational Mathematics: Elective Compulsory
Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Course L0428: Algebra and Control
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Dr. Prashant Batra
Language DE/EN
Cycle SoSe
Content

- Algebraic control methods, polynomial and fractional approach
-Single input - single output (SISO) control systems synthesis by algebraic methods,


- Simultaneous stabilization

- Parametrization of all stabilizing controllers

- Selected methods of pole assignment.

- Filtering and sensitivity minimization
- Polynomial matrices, left and right polynomial fractions.

- Euclidean algorithm, diophantine equations over rings

- Smith-McMillan normal form
- Multiple input - multiple output control system synthesis by polynomial methods, condition of
stability.

Literature
  • Vidyasagar, M.: Control system synthesis: a factorization approach.
    The MIT Press,Cambridge/Mass. - London, 1985.
  • Vardulakis, A.I.G.: Linear multivariable control. Algebraic analysis and synthesis
    methods, John Wiley & Sons,Chichester,UK,1991.
  • Chen, Chi-Tsong: Analog and digital control system design. Transfer-function, state-space, and  
    algebraic methods. Oxford Univ. Press,1995.
  • Kučera, V.: Analysis and Design of Discrete Linear Control Systems. Praha: Academia, 1991.
Course L0429: Algebra and Control
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Dr. Prashant Batra
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Specialization III. Engineering Science

Module M0536: Fundamentals of Fluid Mechanics

Courses
Title Typ Hrs/wk CP
Fundamentals of Fluid Mechanics (L0091) Lecture 2 4
Fluid Mechanics for Process Engineering (L0092) Recitation Section (large) 2 2
Module Responsible Prof. Michael Schlüter
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics I+II+III
  • Technical Mechanics I+II
  • Technical Thermodynamics I+II
  • Working with force balances
  • Simplification and solving of partial differential equations
  • Integration
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to:

  • explain the difference between different types of flow
  • give an overview for different applications of the Reynolds Transport-Theorem in process engineering
  • explain simplifications of the Continuity- and Navier-Stokes-Equation by using physical boundary conditions
Skills

The students are able to

  • describe and model incompressible flows mathematically
  • reduce the governing equations of fluid mechanics by simplifications to archive quantitative solutions e.g. by integration
  • notice the dependency between theory and technical applications
  • use the learned basics for fluid dynamical applications in fields of process engineering 
Personal Competence
Social Competence

The students

  • are capable to gather information from subject related, professional publications and relate that information to the context of the lecture and
  • able to work together on subject related tasks in small groups. They are able to present their results effectively in English (e.g. during small group exercises)
  • are able to work out solutions for exercises by themselves, to discuss the solutions orally and to present the results.
Autonomy

The students are able to

  • search further literature for each topic and to expand their knowledge with this literature,
  • work on their exercises by their own and to evaluate their actual knowledge with the feedback.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung
Compulsory Bonus Form Description
Yes 5 % Midterm
Examination Written exam
Examination duration and scale 3 hours
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Process Engineering: Compulsory
General Engineering Science (German program): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (German program): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Process Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory
Bioprocess Engineering: Core qualification: Compulsory
Energy and Environmental Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (English program): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (English program): Specialisation Process Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Process Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Process Engineering: Core qualification: Compulsory
Course L0091: Fundamentals of Fluid Mechanics
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Michael Schlüter
Language DE
Cycle SoSe
Content
  • fluid properties
  • hydrostatic
  • overall balances - theory of streamline
  • overall balances- conservation equations
  • differential balances - Navier Stokes equations
  • irrotational flows - Potenzialströmungen
  • flow around bodies - theory of physical similarity
  • turbulent flows
  • compressible flows
Literature
  1. Crowe, C. T.: Engineering fluid mechanics. Wiley, New York, 2009.
  2. Durst, F.: Strömungsmechanik: Einführung in die Theorie der Strömungen von Fluiden. Springer-Verlag, Berlin, Heidelberg, 2006.
  3. Fox, R.W.; et al.: Introduction to Fluid Mechanics. J. Wiley & Sons, 1994
  4. Herwig, H.: Strömungsmechanik: Eine Einführung in die Physik und die mathematische Modellierung von Strömungen. Springer Verlag, Berlin, Heidelberg, New York, 2006
  5. Herwig, H.: Strömungsmechanik: Einführung in die Physik von technischen Strömungen: Vieweg+Teubner Verlag / GWV Fachverlage GmbH, Wiesbaden, 2008
  6. Kuhlmann, H.C.:  Strömungsmechanik. München, Pearson Studium, 2007
  7. Oertl, H.: Strömungsmechanik: Grundlagen, Grundgleichungen, Lösungsmethoden, Softwarebeispiele. Vieweg+ Teubner Verlag / GWV Fachverlage GmbH, Wiesbaden, 2009
  8. Schade, H.; Kunz, E.: Strömungslehre. Verlag de Gruyter, Berlin, New York, 2007
  9. Truckenbrodt, E.: Fluidmechanik 1: Grundlagen und elementare Strömungsvorgänge dichtebeständiger Fluide. Springer-Verlag, Berlin, Heidelberg, 2008
  10. Schlichting, H. : Grenzschicht-Theorie. Springer-Verlag, Berlin, 2006
  11. van Dyke, M.: An Album of Fluid Motion. The Parabolic Press, Stanford California, 1882.
  12. White, F.: Fluid Mechanics, Mcgraw-Hill, ISBN-10: 0071311211, ISBN-13: 978-0071311212, 2011
Course L0092: Fluid Mechanics for Process Engineering
Typ Recitation Section (large)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Michael Schlüter
Language DE
Cycle SoSe
Content

In the exercise-lecture the topics from the main lecture are discussed intensively and transferred into application. For that, the students receive example tasks for download. The students solve these problems based on the lecture material either independently or in small groups. The solution is discussed with the students under scientific supervision and parts of the solutions are presented on the chalk board. At the end of each exercise-lecture, the correct solution is presented on the chalk board. Parallel to the exercise-lecture tutorials are held where the student solve exam questions under a set time-frame in small groups and discuss the solutions afterwards.

  

Literature
  1. Crowe, C. T.: Engineering fluid mechanics. Wiley, New York, 2009.
  2. Durst, F.: Strömungsmechanik: Einführung in die Theorie der Strömungen von Fluiden. Springer-Verlag, Berlin, Heidelberg, 2006.
  3. Fox, R.W.; et al.: Introduction to Fluid Mechanics. J. Wiley & Sons, 1994
  4. Herwig, H.: Strömungsmechanik: Eine Einführung in die Physik und die mathematische Modellierung von Strömungen. Springer Verlag, Berlin, Heidelberg, New York, 2006
  5. Herwig, H.: Strömungsmechanik: Einführung in die Physik von technischen Strömungen: Vieweg+Teubner Verlag / GWV Fachverlage GmbH, Wiesbaden, 2008
  6. Kuhlmann, H.C.:  Strömungsmechanik. München, Pearson Studium, 2007
  7. Oertl, H.: Strömungsmechanik: Grundlagen, Grundgleichungen, Lösungsmethoden, Softwarebeispiele. Vieweg+ Teubner Verlag / GWV Fachverlage GmbH, Wiesbaden, 2009
  8. Schade, H.; Kunz, E.: Strömungslehre. Verlag de Gruyter, Berlin, New York, 2007
  9. Truckenbrodt, E.: Fluidmechanik 1: Grundlagen und elementare Strömungsvorgänge dichtebeständiger Fluide. Springer-Verlag, Berlin, Heidelberg, 2008
  10. Schlichting, H. : Grenzschicht-Theorie. Springer-Verlag, Berlin, 2006
  11. van Dyke, M.: An Album of Fluid Motion. The Parabolic Press, Stanford California, 1882.
  12. White, F.: Fluid Mechanics, Mcgraw-Hill, ISBN-10: 0071311211, ISBN-13: 978-0071311212, 2011

Module M0634: Introduction into Medical Technology and Systems

Courses
Title Typ Hrs/wk CP
Introduction into Medical Technology and Systems (L0342) Lecture 2 3
Introduction into Medical Technology and Systems (L0343) Project Seminar 2 2
Introduction into Medical Technology and Systems (L1876) Recitation Section (large) 1 1
Module Responsible Prof. Alexander Schlaefer
Admission Requirements None
Recommended Previous Knowledge

principles of math (algebra, analysis/calculus)
principles of  stochastics
principles of programming, R/Matlab

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students can explain principles of medical technology, including imaging systems, computer aided surgery, and medical information systems. They are able to give an overview of regulatory affairs and standards in medical technology.

Skills

The students are able to evaluate systems and medical devices in the context of clinical applications.

Personal Competence
Social Competence

The students describe a problem in medical technology as a project, and define tasks that are solved in a joint effort.

Autonomy

The students can reflect their knowledge and document the results of their work. They can present the results in an appropriate manner.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Studienleistung
Compulsory Bonus Form Description
Yes 10 % Written elaboration
Yes 10 % Presentation
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Core qualification: Elective Compulsory
General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory
Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Mathematics & Engineering Science: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0342: Introduction into Medical Technology and Systems
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language DE
Cycle SoSe
Content

- imaging systems
- computer aided surgery
- medical sensor systems
- medical information systems
- regulatory affairs
- standard in medical technology
The students will work in groups to apply the methods introduced during the lecture using problem based learning.


Literature

Wird in der Veranstaltung bekannt gegeben.

Course L0343: Introduction into Medical Technology and Systems
Typ Project Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course
Course L1876: Introduction into Medical Technology and Systems
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Alexander Schlaefer
Language DE
Cycle SoSe
Content

- imaging systems
- computer aided surgery
- medical sensor systems
- medical information systems
- regulatory affairs
- standard in medical technology
The students will work in groups to apply the methods introduced during the lecture using problem based learning.

Literature

Wird in der Veranstaltung bekannt gegeben.

Module M0680: Fluid Dynamics

Courses
Title Typ Hrs/wk CP
Fluid Mechanics (L0454) Lecture 3 4
Fluid Mechanics (L0455) Recitation Section (large) 2 2
Module Responsible Prof. Thomas Rung
Admission Requirements None
Recommended Previous Knowledge

Sound knowledge of engineering mathematics, engineering mechanics and thermodynamics.

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students will have the required sound knowledge to explain the general principles of fluid engineering and physics of fluids. Students can scientifically outline the rationale of flow physics using mathematical models and are familiar with methods for the performance analysis and the prediciton of fluid engineering devices.

Skills

Students are able to apply fluid-engineering principles and flow-physics models for the analysis of technical systems. The lecture enables the student to carry out all necessary theoretical calculations for the fluid dynamic design of engineering devices on a scientific level.

Personal Competence
Social Competence

The students are able to discuss problems and jointly develop solution strategies.


Autonomy

The students are able to develop solution strategies for complex problems self-consistent and crtically analyse results.


Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 180 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Mechanical Engineering: Compulsory
General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program): Specialisation Naval Architecture: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Naval Architecture: Compulsory
General Engineering Science (English program): Specialisation Mechanical Engineering: Compulsory
General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program): Specialisation Naval Architecture: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Naval Architecture: Compulsory
Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory
Mechanical Engineering: Core qualification: Compulsory
Naval Architecture: Core qualification: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0454: Fluid Mechanics
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Thomas Rung
Language DE
Cycle SoSe
Content
  • Overview
  • Physical/mathematical modelling
  • Special phenomena
  • Basic equations of fluid dynamics
  • The turbulence problem
  • One dimensional theory for inkompressibel flows
  • One dimensional theory for kompressibel flows
  • Flow over contours without friction
  • Flow over contours with friction
  • Flow through channels
  • Simplified equations for three dimensional flow
  • Special aspects of the numerical solution for complex flows
Literature
  • Herwig, H.: Strömungsmechanik, 2. Auflage, Springer- Verlag, Berlin, Heidelberg, 2006
  • Herwig, H.: Strömungsmechanik von A-Z, Vieweg Verlag, Wiesbaden, 2004
Course L0455: Fluid Mechanics
Typ Recitation Section (large)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Thomas Rung
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0757: Biochemistry and Microbiology

Courses
Title Typ Hrs/wk CP
Biochemistry (L0351) Lecture 2 2
Biochemistry (L0728) Project-/problem-based Learning 1 1
Microbiology (L0881) Lecture 2 2
Microbiology (L0888) Project-/problem-based Learning 1 1
Module Responsible Dr. Paul Bubenheim
Admission Requirements None
Recommended Previous Knowledge none
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

At the end of this module the students can:

- explain the methods of biological and biochemical research to determine the properties of biomolecules

- name the basic components of a living organism

- explain the principles of metabolism

- describe the structure of living cells


Skills
Personal Competence
Social Competence

The students are able,

- to gather knowledge in groups of about 10 students

- to introduce their own knowledge and to argue their view in discussions in teams

- to divide a complex task into subtasks, solve these and to present the combined results 

Autonomy

The students are able to present the results of their subtasks in a written report

Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
Bioprocess Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0351: Biochemistry
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Dr. Paul Bubenheim
Language DE
Cycle SoSe
Content
  1. The molecular logic of Life
  2. Biomolecules:
    1. Amino acids, peptides, proteins
    2. Carbohydrates
    3. Lipids
  3. Protein functions, Enzymes:
    1. Michaelis-Menten kinetics
    2. Enzyme regulation
    3. Enzyme nomenclature
  4. Cofactors and cosubstrates, vitamines
  5. Metabolism:
    1. Basic principles
    2. Photosynthesis
    3. Glycolysis
    4. Citric acid cycle
    5. Respiration
    6. Anaerobic respirations
    7. Fatty acid metabolism
    8. Amino acid metabolism
Literature

Biochemie, H. Robert Horton, Laurence A. Moran, K. Gray Scrimeour, Marc D. Perry, J. David Rawn, Pearson Studium, München

Prinzipien der Biochemie, A. L. Lehninger, de Gruyter Verlag Berlin

Course L0728: Biochemistry
Typ Project-/problem-based Learning
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dr. Paul Bubenheim
Language DE
Cycle SoSe
Content
  1. The molecular logic of Life
  2. Biomolecules:
    1. Amino acids, peptides, proteins
    2. Carbohydrates
    3. Lipids
  3. Protein functions, Enzymes:
    1. Michaelis-Menten kinetics
    2. Enzyme regulation
    3. Enzyme nomenclature
  4. Cofactors and cosubstrates, vitamines
  5. Metabolism:
    1. Basic principles
    2. Photosynthesis
    3. Glycolysis
    4. Citric acid cycle
    5. Respiration
    6. Anaerobic respirations
    7. Fatty acid metabolism
    8. Amino acid metabolism
Literature

Biochemie, H. Robert Horton, Laurence A. Moran, K. Gray Scrimeour, Marc D. Perry, J. David Rawn, Pearson Studium, München

Prinzipien der Biochemie, A. L. Lehninger, de Gruyter Verlag Berlin

Course L0881: Microbiology
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Dr. Christian Schäfers
Language DE
Cycle SoSe
Content

1. The procaryotic cell

  • evolution
  • taxonomy and specific properties of Archaea, Bacteria, and viruses
  • structure and properties of the cell
  • growth

2. Metabolism

  • fermentation and anaerobic respiration
  • methanogenesis and the anaerobic food chain
  • degradation of polymers
  • chemolithotrophy

3. Microorganisms in relation to the environment

  • chemotaxis and motility
  • Elemental cycle of carbon, nitrogen and sulfur
  • biofilms
  • symbiotic relationships
  • extremophiles
  • biotechnology

Literature

Allgemeine Mikrobiologie, 8. Aufl., 2007,  Fuchs, G. (Hrsg.), Thieme Verlag (54,95 €)

Mikrobiologie, 13 Aufl., 2013, Madigan, M., Martinko, J. M., Stahl, D. A., Clark, D. P. (Hrsg.), ehemals „Brock“, Pearson Verlag (89,95 €)

• Taschenlehrbuch Biologie Mikrobiologie, 2008, Munk, K. (Hrsg.), Thieme Verlag

Grundlagen der Mikrobiologie, 4. Aufl., 2010, Cypionka, H., Springer Verlag (29,95 €), http://www.grundlagen-der-mikrobiologie.icbm.de/

Course L0888: Microbiology
Typ Project-/problem-based Learning
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dr. Christian Schäfers
Language DE
Cycle SoSe
Content

1. The procaryotic cell

  • evolution
  • taxonomy and specific properties of Archaea, Bacteria, and viruses
  • structure and properties of the cell
  • growth

2. Metabolism

  • fermentation and anaerobic respiration
  • methanogenesis and the anaerobic food chain
  • degradation of polymers
  • chemolithotrophy

3. Microorganisms in relation to the environment

  • chemotaxis and motility
  • Elemental cycle of carbon, nitrogen and sulfur
  • biofilms
  • symbiotic relationships
  • extremophiles
  • biotechnology

Literature

Allgemeine Mikrobiologie, 8. Aufl., 2007,  Fuchs, G. (Hrsg.), Thieme Verlag (54,95 €)

Mikrobiologie, 13 Aufl., 2013, Madigan, M., Martinko, J. M., Stahl, D. A., Clark, D. P. (Hrsg.), ehemals „Brock“, Pearson Verlag (89,95 €)

• Taschenlehrbuch Biologie Mikrobiologie, 2008, Munk, K. (Hrsg.), Thieme Verlag

Grundlagen der Mikrobiologie, 4. Aufl., 2010, Cypionka, H., Springer Verlag (29,95 €), http://www.grundlagen-der-mikrobiologie.icbm.de/

Module M1277: MED I: Introduction to Anatomy

Courses
Title Typ Hrs/wk CP
Introduction to Anatomy (L0384) Lecture 2 3
Module Responsible Prof. Udo Schumacher
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students can describe basal structures and functions of internal organs and the musculoskeletal system.

The students can describe the basic macroscopy and microscopy of those systems.

Skills

The students can recognize the relationship between given anatomical facts and the development of some common diseases; they can explain the relevance of structures and their functions in the context of widespread diseases.

Personal Competence
Social Competence

The students can participate in current discussions in biomedical research and medicine on a professional level.

Autonomy

The students are able to access anatomical knowledge by themselves, can participate in conversations on the topic and acquire the relevant knowledge themselves.

Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Credit points 3
Studienleistung None
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
General Engineering Science (English program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory
Mechanical Engineering: Specialisation Biomechanics: Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0384: Introduction to Anatomy
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Tobias Lange
Language DE
Cycle SoSe
Content

General Anatomy

1st week:             The Eucaryote Cell

2nd week:             The Tissues

3rd week:             Cell Cycle, Basics in Development

4th week:             Musculoskeletal System

5th week:             Cardiovascular System

6th week:             Respiratory System   

7th week:             Genito-urinary System

8th week:             Immune system

9th week:             Digestive System I

10th week:           Digestive System II

11th week:           Endocrine System

12th week:           Nervous System

13th week:           Exam



Literature

Adolf Faller/Michael Schünke, Der Körper des Menschen, 16. Auflage, Thieme Verlag Stuttgart, 2012

Module M0938: Bioprocess Engineering - Fundamentals

Courses
Title Typ Hrs/wk CP
Bioprocess Engineering - Fundamentals (L0841) Lecture 2 3
Bioprocess Engineering- Fundamentals (L0842) Recitation Section (large) 2 1
Bioprocess Engineering - Fundamental Practical Course (L0843) Practical Course 2 2
Module Responsible Prof. Andreas Liese
Admission Requirements None
Recommended Previous Knowledge none, module "organic chemistry", module "fundamentals for process engineering"
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to describe the basic concepts of bioprocess engineering. They are able to classify different types of kinetics for enzymes and microorganisms, as well as to differentiate different types of inhibition. The parameters of stoichiometry and rheology can be named and mass transport processes in bioreactors can be explained. The students are capable to explain fundamental bioprocess management, sterilization technology and downstream processing in detail. 

Skills

After successful completion of this module, students should be able to

  • describe different kinetic approaches for growth and substrate-uptake and to calculate the corresponding parameters
  • predict qualitatively the influence of energy generation, regeneration of redox equivalents and growth inhibition on the fermentation process
  • analyze bioprocesses on basis of stoichiometry and to set up / solve metabolic flux equations
  • distinguish between scale-up criteria for different bioreactors and bioprocesses (anaerobic, aerobic as well as microaerobic) to compare them as well as to apply them to current biotechnical problem
  • propose solutions to complicated biotechnological problems and to deduce the corresponding models 
  • to explore new knowledge resources and to apply the newly gained contents
  • identify scientific problems with concrete industrial use and to formulate solutions.
  • to document and discuss their procedures as well as results in a scientific manner


Personal Competence
Social Competence

After completion of this module participants should be able to debate technical questions in small teams to enhance the ability to take position to their own opinions and increase their capacity for teamwork in engineering and scientific environments. 

Autonomy

After completion of this module participants will be able to solve a technical problem in a team independently by organizing their workflow and to  present their results in a plenum.

Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Credit points 6
Studienleistung
Compulsory Bonus Form Description
Yes None Subject theoretical and practical work
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Process Engineering: Compulsory
General Engineering Science (German program): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Process Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
Bioprocess Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (English program): Specialisation Process Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Process Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Process Engineering: Core qualification: Compulsory
Course L0841: Bioprocess Engineering - Fundamentals
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Andreas Liese, Prof. An-Ping Zeng
Language DE
Cycle SoSe
Content
  • Introduction: state-of-the-art and development trends in the biotechnology, introduction to the lecture  
  • Enzyme kinetics: Michaelis-Menten, differnt types of enzyme inhibition, linearization, conversion, yield, selectivity (Prof. Liese)
  • Stoichiometry:  coefficient of respiration, electron balance, degree of reduction, coefficient of yield, theoretical oxygen demand (Prof. Liese)
  • Microbial growth kinetic: batch- and chemostat culture (Prof. Zeng)
  • Kinetic of subtrate consumption and product formation (Prof. Zeng)
  • Rheology: non-newtonian fluids, viscosity, agitators, energy input (Prof. Liese)
  • Transport process in a bioreactor (Prof. Zeng)
  • Technology of sterilization (Prof. Zeng)
  • Fundamentals of bioprocess management: bioreactors and calculation of batch, fed-batch and continuouse bioprocesses
    (Prof. Zeng/Prof. Liese)
  • Downstream technology in biotechnology: cell breakdown, zentrifugation, filtration, aqueous two phase systems (Prof. Liese)
Literature

K. Buchholz, V. Kasche, U. Bornscheuer: Biocatalysts and Enzyme Technology, 2. Aufl. Wiley-VCH, 2012

H. Chmiel: Bioprozeßtechnik, Elsevier, 2006

R.H. Balz et al.: Manual of Industrial Microbiology and Biotechnology, 3. edition, ASM Press, 2010 

H.W. Blanch, D. Clark: Biochemical Engineering, Taylor & Francis, 1997 

P. M. Doran: Bioprocess Engineering Principles, 2. edition, Academic Press, 2013

Course L0842: Bioprocess Engineering- Fundamentals
Typ Recitation Section (large)
Hrs/wk 2
CP 1
Workload in Hours Independent Study Time 2, Study Time in Lecture 28
Lecturer Prof. Andreas Liese, Prof. An-Ping Zeng
Language DE
Cycle SoSe
Content

1. Introduction (Prof. Liese, Prof. Zeng)

2. Enzymatic kinetics (Prof. Liese)

3. Stoichiometry I + II (Prof. Liese)

4. Microbial Kinetics I+II (Prof. Zeng)

5. Rheology (Prof. Liese)

6. Mass transfer in bioprocess (Prof. Zeng)

7. Continuous culture (Chemostat) (Prof. Zeng)

8. Sterilisation (Prof. Zeng)

9. Downstream processing (Prof. Liese)

10. Repetition (Reserve) (Prof. Liese, Prof. Zeng)
Literature siehe Vorlesung
Course L0843: Bioprocess Engineering - Fundamental Practical Course
Typ Practical Course
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Andreas Liese, Prof. An-Ping Zeng
Language DE
Cycle SoSe
Content

In this course fermentation and downstream technologies on the example of the production of an enzyme by means of a recombinant microorganism is learned. Detailed characterization and simulation of enzyme kinetics as well as application of the enzyme in a bioreactor is carried out.

The students document their experiments and results in a protocol. 


Literature Skript

Module M1278: MED I: Introduction to Radiology and Radiation Therapy

Courses
Title Typ Hrs/wk CP
Introduction to Radiology and Radiation Therapy (L0383) Lecture 2 3
Module Responsible Prof. Ulrich Carl
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge Therapy

The students can distinguish different types of currently used equipment with respect to its use in radiation therapy.

The students can explain treatment plans used in radiation therapy in interdisciplinary contexts (e.g. surgery, internal medicine).

The students can describe the patients' passage from their initial admittance through to follow-up care.

Diagnostics

The students can illustrate the technical base concepts of projection radiography, including angiography and mammography, as well as sectional imaging techniques (CT, MRT, US).

The students can explain the diagnostic as well as therapeutic use of imaging techniques, as well as the technical basis for those techniques.

The students can choose the right treatment method depending on the patient's clinical history and needs.

The student can explain the influence of technical errors on the imaging techniques.

The student can draw the right conclusions based on the images' diagnostic findings or the error protocol.

Skills Therapy

The students can distinguish curative and palliative situations and motivate why they came to that conclusion.

The students can develop adequate therapy concepts and relate it to the radiation biological aspects.

The students can use the therapeutic principle (effects vs adverse effects)

The students can distinguish different kinds of radiation, can choose the best one depending on the situation (location of the tumor) and choose the energy needed in that situation (irradiation planning).

The student can assess what an individual psychosocial service should look like (e.g. follow-up treatment, sports, social help groups, self-help groups, social services, psycho-oncology).

Diagnostics

The students can suggest solutions for repairs of imaging instrumentation after having done error analyses.

The students can classify results of imaging techniques according to different groups of diseases based on their knowledge of anatomy, pathology and pathophysiology.

Personal Competence
Social Competence The students can assess the special social situation of tumor patients and interact with them in a professional way.

The students are aware of the special, often fear-dominated behavior of sick people caused by diagnostic and therapeutic measures and can meet them appropriately.

Autonomy The students can apply their new knowledge and skills to a concrete therapy case.

The students can introduce younger students to the clinical daily routine.

The students are able to access anatomical knowledge by themselves, can participate competently in conversations on the topic and acquire the relevant knowledge themselves.

Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Credit points 3
Studienleistung None
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
General Engineering Science (English program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory
Mechanical Engineering: Specialisation Biomechanics: Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0383: Introduction to Radiology and Radiation Therapy
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Ulrich Carl, Prof. Thomas Vestring
Language DE
Cycle SoSe
Content

The students will be given an understanding of the technological possibilities in the field of medical imaging, interventional radiology and radiation therapy/radiation oncology. It is assumed, that students in the beginning of the course have heard the word “X-ray” at best. It will be distinguished between the two arms of diagnostic (Prof. Dr. med. Thomas Vestring) and therapeutic (Prof. Dr. med. Ulrich Carl) use of X-rays. Both arms depend on special big units, which determine a predefined sequence in their respective departments



Literature
  • "Technik der medizinischen Radiologie"  von T. + J. Laubenberg –

    7. Auflage – Deutscher Ärzteverlag –  erschienen 1999

  • "Klinische Strahlenbiologie" von Th. Herrmann, M. Baumann und W. Dörr –

    4. Auflage - Verlag Urban & Fischer –  erschienen 02.03.2006

    ISBN: 978-3-437-23960-1

  • "Strahlentherapie und Onkologie für MTA-R" von R. Sauer –

             5. Auflage 2003 - Verlag Urban & Schwarzenberg – erschienen 08.12.2009

             ISBN: 978-3-437-47501-6

  • "Taschenatlas der Physiologie" von S. Silbernagel und A. Despopoulus‑                

    8. Auflage – Georg Thieme Verlag - erschienen 19.09.2012

    ISBN: 978-3-13-567708-8

  • "Der Körper des Menschen " von A. Faller  u. M. Schünke -

    16. Auflage 2004 – Georg Thieme Verlag –  erschienen 18.07.2012

    ISBN: 978-3-13-329716-5

  • „Praxismanual Strahlentherapie“ von Stöver / Feyer –

    1. Auflage - Springer-Verlag GmbH –  erschienen 02.06.2000



Module M0671: Technical Thermodynamics I

Courses
Title Typ Hrs/wk CP
Technical Thermodynamics I (L0437) Lecture 2 4
Technical Thermodynamics I (L0439) Recitation Section (large) 1 1
Technical Thermodynamics I (L0441) Recitation Section (small) 1 1
Module Responsible Prof. Gerhard Schmitz
Admission Requirements None
Recommended Previous Knowledge Elementary knowledge in Mathematics and Mechanics
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are familiar with the laws of Thermodynamics. They know the relation of the kinds of energy according to 1st law of Thermodynamics and are aware about the limits of energy conversions according to 2nd law of Thermodynamics. They are able to distinguish between state variables and process variables and know the meaning of different state variables like temperature, enthalpy, entropy and also the meaning of exergy and anergy. They are able to draw the Carnot cycle in a Thermodynamics related diagram. They know the physical difference between an ideal and a real gas and are able to use the related equations of state. They know the meaning of a fundamental state of equation and know the basics of two phase Thermodynamics.


Skills

Students are able to calculate the internal energy, the enthalpy, the kinetic and the potential energy as well as work and heat for simple change of states and to use this calculations for the Carnot cycle. They are able to calculate state variables for an ideal and for a real gas from measured thermal state variables.


Personal Competence
Social Competence The students are able to discuss in small groups and develop an approach.
Autonomy

Students are able to define independently tasks, to get new knowledge from existing knowledge as well as to find ways to use the knowledge in practice.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program): Core qualification: Compulsory
General Engineering Science (German program, 7 semester): Core qualification: Compulsory
Bioprocess Engineering: Core qualification: Compulsory
Energy and Environmental Engineering: Core qualification: Compulsory
General Engineering Science (English program): Core qualification: Compulsory
General Engineering Science (English program, 7 semester): Core qualification: Compulsory
Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory
Mechanical Engineering: Core qualification: Compulsory
Mechatronics: Core qualification: Compulsory
Naval Architecture: Core qualification: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Process Engineering: Core qualification: Compulsory
Course L0437: Technical Thermodynamics I
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Gerhard Schmitz
Language DE
Cycle SoSe
Content
  1. Introduction
  2. Fundamental terms
  3. Thermal Equilibrium and temperature
    3.1 Thermal equation of state
  4. First law
    4.1 Heat and work
    4.2 First law for closed systems
    4.3 First law for open systems
    4.4 Examples
  5. Equations of state and changes of state
    5.1 Changes of state
    5.2 Cycle processes
  6. Second law
    6.1 Carnot process
    6.2 Entropy
    6.3 Examples
    6.4 Exergy
  7. Thermodynamic properties of pure fluids
    7.1 Fundamental equations of Thermodynamics
    7.2 Thermodynamic potentials
    7.3 Calorific state variables for arbritary fluids
    7.4 state equations (van der Waals u.a.)

Literature
  • Schmitz, G.: Technische Thermodynamik, TuTech Verlag, Hamburg, 2009
  • Baehr, H.D.; Kabelac, S.: Thermodynamik, 15. Auflage, Springer Verlag, Berlin 2012

  • Potter, M.; Somerton, C.: Thermodynamics for Engineers, Mc GrawHill, 1993



Course L0439: Technical Thermodynamics I
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Gerhard Schmitz
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course
Course L0441: Technical Thermodynamics I
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Gerhard Schmitz
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0567: Theoretical Electrical Engineering I: Time-Independent Fields

Courses
Title Typ Hrs/wk CP
Theoretical Electrical Engineering I: Time-Independent Fields (L0180) Lecture 3 5
Theoretical Electrical Engineering I: Time-Independent Fields (L0181) Recitation Section (small) 2 1
Module Responsible Prof. Christian Schuster
Admission Requirements None
Recommended Previous Knowledge

Basic principles of electrical engineering and advanced mathematics


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the fundamental formulas, relations, and methods of the theory of time-independent electromagnetic fields. They can explicate the principal behavior of electrostatic, magnetostatic, and current density fields with regard to respective sources. They can describe the properties of complex electromagnetic fields by means of superposition of solutions for simple fields. The students are aware of applications for the theory of time-independent electromagnetic fields and are able to explicate these.


Skills

Students can apply Maxwell’s Equations in integral notation in order to solve highly symmetrical, time-independent, electromagnetic field problems. Furthermore, they are capable of applying a variety of methods that require solving Maxwell’s Equations for more general problems. The students can assess the principal effects of given time-independent sources of fields and analyze these quantitatively. They can deduce meaningful quantities for the characterization of electrostatic, magnetostatic, and electrical flow fields (capacitances, inductances, resistances, etc.) from given fields and dimension them for practical applications.


Personal Competence
Social Competence

Students are able to work together on subject related tasks in small groups. They are able to present their results effectively (e.g. during exercise sessions).


Autonomy

Students are capable to gather necessary information from provided references and relate this information to the lecture. They are able to continually reflect their knowledge by means of activities that accompany the lecture, such as short oral quizzes during the lectures and exercises that are related to the exam. Based on respective feedback, students are expected to adjust their individual learning process. They are able to draw connections between their knowledge obtained in this lecture and the content of other lectures (e.g. Electrical Engineering I, Linear Algebra, and Analysis).


Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 90-150 minutes
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Electrical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Compulsory
Electrical Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Electrical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory
Computational Science and Engineering: Specialisation Mathematics & Engineering Science: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0180: Theoretical Electrical Engineering I: Time-Independent Fields
Typ Lecture
Hrs/wk 3
CP 5
Workload in Hours Independent Study Time 108, Study Time in Lecture 42
Lecturer Prof. Christian Schuster
Language DE
Cycle SoSe
Content

- Maxwell’s Equations in integral and differential notation

- Boundary conditions

- Laws of conservation for energy and charge

- Classification of electromagnetic field properties

- Integral characteristics of time-independent fields (R, L, C)

- Generic approaches to solving Poisson’s Equation

- Electrostatic fields and specific methods of solving

- Magnetostatic fields and specific methods of solving

- Fields of electrical current density and specific methods of solving

- Action of force within time-independent fields

- Numerical methods for solving time-independent problems


Literature

- G. Lehner, "Elektromagnetische Feldtheorie: Für Ingenieure und Physiker", Springer (2010)

- H. Henke, "Elektromagnetische Felder: Theorie und Anwendung", Springer (2011)

- W. Nolting, "Grundkurs Theoretische Physik 3: Elektrodynamik", Springer (2011)

- D. Griffiths, "Introduction to Electrodynamics", Pearson (2012)

- J. Edminister, " Schaum's Outline of Electromagnetics", Mcgraw-Hill (2013)

- Richard Feynman, "Feynman Lectures on Physics: Volume 2", Basic Books (2011)


Course L0181: Theoretical Electrical Engineering I: Time-Independent Fields
Typ Recitation Section (small)
Hrs/wk 2
CP 1
Workload in Hours Independent Study Time 2, Study Time in Lecture 28
Lecturer Prof. Christian Schuster
Language DE
Cycle SoSe
Content

- Maxwell’s Equations in integral and differential notation

- Boundary conditions

- Laws of conservation for energy and charge

- Classification of electromagnetic field properties

- Integral characteristics of time-independent fields (R, L, C)

- Generic approaches to solving Poisson’s Equation

- Electrostatic fields and specific methods of solving

- Magnetostatic fields and specific methods of solving

- Fields of electrical current density and specific methods of solving

- Action of force within time-independent fields

- Numerical methods for solving time-independent problems


Literature

- G. Lehner, "Elektromagnetische Feldtheorie: Für Ingenieure und Physiker", Springer (2010)

- H. Henke, "Elektromagnetische Felder: Theorie und Anwendung", Springer (2011)

- W. Nolting, "Grundkurs Theoretische Physik 3: Elektrodynamik", Springer (2011)

- D. Griffiths, "Introduction to Electrodynamics", Pearson (2012)

- J. Edminister, " Schaum's Outline of Electromagnetics", Mcgraw-Hill (2013)

- Richard Feynman, "Feynman Lectures on Physics: Volume 2", Basic Books (2011)


Module M0672: Signals and Systems

Courses
Title Typ Hrs/wk CP
Signals and Systems (L0432) Lecture 3 4
Signals and Systems (L0433) Recitation Section (small) 2 2
Module Responsible Prof. Gerhard Bauch
Admission Requirements None
Recommended Previous Knowledge

Mathematics 1-3

The modul is an introduction to the theory of signals and systems. Good knowledge in maths as covered by the moduls Mathematik 1-3 is expected. Further experience with spectral transformations (Fourier series, Fourier transform, Laplace transform) is useful but not required.

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students are able to classify and describe signals and linear time-invariant (LTI) systems using methods of signal and system theory. They are able to apply the fundamental transformations of continuous-time and discrete-time signals and systems. They can describe and analyse deterministic signals and systems mathematically in both time and image domain. In particular, they understand the effects in time domain and image domain which are caused by the transition of a continuous-time signal to a discrete-time signal.
Skills The students are able to describe and analyse deterministic signals and linear time-invariant systems using methods of signal and system theory. They can analyse and design basic systems regarding important properties such as magnitude and phase response, stability, linearity etc.. They can assess the impact of LTI systems on the signal properties in time and frequency domain.
Personal Competence
Social Competence The students can jointly solve specific problems.
Autonomy The students are able to acquire relevant information from appropriate literature sources. They can control their level of knowledge during the lecture period by solving tutorial problems, software tools, clicker system. 
Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Electrical Engineering: Compulsory
General Engineering Science (German program): Specialisation Computer Science: Compulsory
General Engineering Science (German program): Specialisation Process Engineering: Compulsory
General Engineering Science (German program): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (German program): Specialisation Civil- and Enviromental Engeneering: Compulsory
General Engineering Science (German program): Specialisation Mechanical Engineering: Compulsory
General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Process Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Aircraft Systems Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory
Computer Science: Core qualification: Compulsory
Electrical Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Civil- and Enviromental Engeneering: Compulsory
General Engineering Science (English program): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (English program): Specialisation Electrical Engineering: Compulsory
General Engineering Science (English program): Specialisation Computer Science: Compulsory
General Engineering Science (English program): Specialisation Mechanical Engineering: Compulsory
General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program): Specialisation Process Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Process Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Aircraft Systems Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Mechatronics: Core qualification: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0432: Signals and Systems
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Gerhard Bauch
Language DE/EN
Cycle SoSe
Content
  • Basic classification and description of continuous-time and discrete-time signals and systems

  • Concvolution

  • Power and energy of signals

  • Correlation functions of deterministic signals

  • Linear time-invariant (LTI) systems

  • Signal transformations:

    • Fourier-Series

    • Fourier Transform

    • Laplace Transform

    • Discrete-time Fourier Transform

    • Discrete Fourier Transform (DFT), Fast Fourier Transform (FFT)

    • Z-Transform

  • Analysis and design of LTI systems in time and frequency domain

  • Basic filter types

  • Sampling, sampling theorem

  • Fundamentals of recursive and non-recursive discrete-time filters

Literature
  • T. Frey , M. Bossert , Signal- und Systemtheorie, B.G. Teubner Verlag 2004

  • K. Kammeyer, K. Kroschel, Digitale Signalverarbeitung, Teubner Verlag.

  • B. Girod ,R. Rabensteiner , A. Stenger , Einführung in die Systemtheorie, B.G. Teubner, Stuttgart, 1997

  • J.R. Ohm, H.D. Lüke , Signalübertragung, Springer-Verlag 8. Auflage, 2002

  • S. Haykin, B. van Veen: Signals and systems. Wiley.

  • Oppenheim, A.S. Willsky: Signals and Systems. Pearson.

  • Oppenheim, R. W. Schafer: Discrete-time signal processing. Pearson.

Course L0433: Signals and Systems
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Gerhard Bauch
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0706: Geotechnics I

Courses
Title Typ Hrs/wk CP
Soil Mechanics (L0550) Lecture 2 2
Soil Mechanics (L0551) Recitation Section (large) 2 2
Soil Mechanics (L1493) Recitation Section (small) 2 2
Module Responsible Prof. Jürgen Grabe
Admission Requirements None
Recommended Previous Knowledge

Modules :

  • Mechanics I-II
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students know the basics of soil mechanics as the structure and characteristics of soil, stress distribution due to weight, water or structures, consolidation and settlement calculations, as well as failure of the soil due to ground- or slope failure.
Skills

After the successful completion of the module the students should be able to describe the mechanical properties and to evaluate them with the help of geotechnical standard tests. They can calculate stresses and deformation in the soils due to weight or influence of structures. They are are able to prove the usability (settlements) for shallow foundations.

Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Credit points 6
Studienleistung
Compulsory Bonus Form Description
No 20 % Attestation
Examination Written exam
Examination duration and scale 60 minutes
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Civil- and Enviromental Engeneering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Civil Engineering: Compulsory
Civil- and Environmental Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Civil- and Enviromental Engeneering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Civil Engineering: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0550: Soil Mechanics
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Jürgen Grabe
Language DE
Cycle SoSe
Content
  • Structure of the soil
  • Ground surveying
  • Compsitition and properties of the soil
  • Groundwater
  • One-dimensional compression
  • Spreading of stresses
  • Settlement calculation
  • Consolidation
  • Shear strength
  • Earth pressure
  • Slope failure
  • Ground failure
  • Suspension based earth tenches
Literature
  • Vorlesungsumdruck, s. ww.tu-harburg.de/gbt
  • Grabe, J. (2004): Bodenmechanik und Grundbau
  • Gudehus, G. (1981): Bodenmechanik
  • Kolymbas, D. (1998): Geotechnik - Bodenmechanik und Grundbau
  • Grundbau-Taschenbuch, Teil 1, aktuelle Auflage
Course L0551: Soil Mechanics
Typ Recitation Section (large)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Jürgen Grabe
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course
Course L1493: Soil Mechanics
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Jürgen Grabe
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0580: Principles of Building Materials and Building Physics

Courses
Title Typ Hrs/wk CP
Building Physics (L0217) Lecture 2 2
Building Physics (L0219) Recitation Section (large) 1 1
Building Physics (L0247) Recitation Section (small) 1 1
Principles of Building Materials (L0215) Lecture 2 2
Module Responsible Prof. Frank Schmidt-Döhl
Admission Requirements None
Recommended Previous Knowledge Knowledge of physics, chemistry and mathematics from school
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students are able to identify fundamental effects of action to materials and structures, to explain different types of mechanical behaviour, to describe the structure of building materials and the correlations between structure and other properties, to show methods of joining and of corrosion processes and to describe the most important regularities and properties of building materials and structures and their measurement in the field of protection against moisture, coldness, fire and noise.

Skills

The students are able to work with the most important standardized methods and regularities in the field of moisture protection, the German regulation for energy saving, fire protection and noise protection in the case of a small building.

Personal Competence
Social Competence

The students are able to support each other to learn the very extensive specialist knowledge.

Autonomy

The students are able to make the timing and the operation steps to learn the specialist knowledge of a very extensive field.


Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 2 h written exam
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Civil- and Enviromental Engeneering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Civil Engineering: Compulsory
Civil- and Environmental Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Civil- and Enviromental Engeneering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Civil Engineering: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0217: Building Physics
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Frank Schmidt-Döhl
Language DE
Cycle WiSe
Content Heat transport, thermal bridges, balances of energy consumption, German regulation for energy saving, heat protection in summer, moisture transport, condensation moisture, protection against mold, fire protection,
noise protection
Literature Fischer, H.-M. ; Freymuth, H.; Häupl, P.; Homann, M.; Jenisch, R.; Richter, E.; Stohrer, M.: Lehrbuch der Bauphysik. Vieweg und Teubner Verlag, Wiesbaden, ISBN 978-3-519-55014-3
Course L0219: Building Physics
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Frank Schmidt-Döhl
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0247: Building Physics
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Frank Schmidt-Döhl
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0215: Principles of Building Materials
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Frank Schmidt-Döhl
Language DE
Cycle WiSe
Content

Structure of building materials
Effects of action
Fundamentals of mechanical behaviour

Principles of metals

Joining methods

Corrosion


Literature

Wendehorst, R.: Baustoffkunde. ISBN 3-8351-0132-3

Scholz, W.:Baustoffkenntnis. ISBN 3-8041-4197-8


Module M0687: Chemistry

Courses
Title Typ Hrs/wk CP
Chemistry I (L0460) Lecture 2 2
Chemistry I (L0475) Recitation Section (large) 1 1
Chemistry II (L0465) Lecture 2 2
Chemistry II (L0476) Recitation Section (large) 1 1
Module Responsible Dr. Dorothea Rechtenbach
Admission Requirements None
Recommended Previous Knowledge none
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students are able to name and to describe basic principles and applications of general chemistry (structure of matter, periodic table, chemical bonds), physical chemistry (aggregate states, separating processes, thermodynamics, kinetics), inorganic chemistry (acid/base, pH-value, salts, solubility, redox, metals) and organic chemistry (aliphatic hydrocarbons, functional groups, carbonyl compounds, aromates, reaction mechanisms, natural products, synthetic polymers). Furthermore students are able to explain basic chemical terms.


Skills

After successful completion of this module students are able to describe substance groups and chemical compounds. On this basis, they are capable of explaining, choosing and applying specific methods and various reaction mechanisms.


Personal Competence
Social Competence

Students are able to take part in discussions on chemical issues and problems as a member of an interdisciplinary team. They can contribute to those discussion by their own statements.


Autonomy

After successful completion of this module students are able to solve chemical problems independently by defending proposed approaches with arguments. They can also document their approaches.


Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 120 min
Assignment for the Following Curricula General Engineering Science (German program): Core qualification: Compulsory
General Engineering Science (German program, 7 semester): Core qualification: Compulsory
Civil- and Environmental Engineering: Core qualification: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0460: Chemistry I
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Dr. Christoph Wutz
Language DE
Cycle WiSe
Content

- Structure of matter

- Periodic table

- Electronegativity

- Chemical bonds

- Solid compounds and solutions

- Chemistry of water

- Chemical reactions and equilibria

- Acid-base reactions

- Redox reactions

Literature

 - Blumenthal, Linke, Vieth: Chemie - Grundwissen für Ingenieure

- Kickelbick: Chemie für Ingenieure (Pearson)

- Mortimer: Chemie. Basiswissen der Chemie.

- Brown, LeMay, Bursten: Chemie. Studieren kompakt.

Course L0475: Chemistry I
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dr. Dorothea Rechtenbach
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0465: Chemistry II
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Dr. Christoph Wutz
Language DE
Cycle WiSe
Content

- Simple compounds of carbon, aliphatic hydrocarbons, aromatic hydrocarbons,

- Alkohols, phenols, ether, aldehydes, ketones, carbonic acids, ester, amines, amino acids, fats, sugars

- Reaction mechanisms, radical reactions, nucleophilic substitution, elimination reactions, addition reaction

- Practical apllications and examples

Literature

 - Blumenthal, Linke, Vieth: Chemie - Grundwissen für Ingenieure

- Kickelbick: Chemie für Ingenieure (Pearson)
- Schmuck: Basisbuch Organische Chemie (Pearson)
Course L0476: Chemistry II
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dr. Dorothea Rechtenbach
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0740: Structural Analysis I

Courses
Title Typ Hrs/wk CP
Structural Analysis I (L0666) Lecture 2 3
Structural Analysis I (L0667) Recitation Section (large) 2 3
Module Responsible Prof. Uwe Starossek
Admission Requirements None
Recommended Previous Knowledge Mechanics I, Mathematics I
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

After successfully completing this module, students can express the basic aspects of linear frame analysis of statically determinate systems.

Skills

After successful completion of this module, the students are able to distinguish between statically determinate and indeterminate structures. They are able to analyze state variables and to construct influence lines of statically determinate plane and spatial frame and truss structures.


Personal Competence
Social Competence

Students can

  • participate in subject-specific and interdisciplinary discussions,
  • defend their own work results in front of others
  • promote the scientific development of colleagues
  • Furthermore, they can give and accept professional constructive criticism
Autonomy

The students are able work in-term homework assignments. Due to the in-term feedback, they are enabled to self-assess their learning progress during the lecture period, already.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung
Compulsory Bonus Form Description
No 10 % Written elaboration Hausübungen mit Testat, betreut durch Studentische Tutoren (Tutorium)
Examination Written exam
Examination duration and scale 90 Minuten
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Civil- and Enviromental Engeneering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Civil Engineering: Compulsory
Civil- and Environmental Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Civil- and Enviromental Engeneering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Civil Engineering: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0666: Structural Analysis I
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Uwe Starossek
Language DE
Cycle WiSe
Content

Statically determinate structural systems

  • basics: statically determinacy, equilibrium, method of sections
  • forces: determination of support reactions and internal forces
  • influence lines of forces
  • displacements: calculation of discrete displacements and rotations, calculation of deflection curves
  • principle of virtual displacements and virtual forces
  • work-engergy theorem
  • differential equation of beam


Literature

Krätzig, W.B., Harte, R., Meskouris, K., Wittek, U.: Tragwerke 1 - Theorie und Berechnungsmethoden statisch bestimmter Stabtragwerke. 4. Aufl., Springer, Berlin, 1999.

Course L0667: Structural Analysis I
Typ Recitation Section (large)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Uwe Starossek
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0933: Fundamentals of Materials Science

Courses
Title Typ Hrs/wk CP
Fundamentals of Materials Science I (L1085) Lecture 2 2
Fundamentals of Materials Science II (Advanced Ceramic Materials, Polymers and Composites) (L0506) Lecture 2 2
Physical and Chemical Basics of Materials Science (L1095) Lecture 2 2
Module Responsible Prof. Jörg Weißmüller
Admission Requirements None
Recommended Previous Knowledge

Highschool-level physics, chemistry und mathematics


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students have acquired a fundamental knowledge on metals, ceramics and polymers and can describe this knowledge comprehensively. Fundamental knowledge here means specifically the issues of atomic structure, microstructure, phase diagrams, phase transformations, corrosion and mechanical properties. The students know about the key aspects of characterization methods for materials and can identify relevant approaches for characterizing specific properties. They are able to trace materials phenomena back to the underlying physical and chemical laws of nature.



Skills

The students are able to trace materials phenomena back to the underlying physical and chemical laws of nature. Materials phenomena here refers to mechanical properties such as strength, ductility, and stiffness, chemical properties such as corrosion resistance, and to phase transformations such as solidification, precipitation, or melting. The students can explain the relation between processing conditions and the materials microstructure, and they can account for the impact of microstructure on the material’s behavior.


Personal Competence
Social Competence -
Autonomy -
Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 180 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (German program): Specialisation Mechanical Engineering: Compulsory
General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program): Specialisation Naval Architecture: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Naval Architecture: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory
Energy and Environmental Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (English program): Specialisation Mechanical Engineering: Compulsory
General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program): Specialisation Naval Architecture: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Naval Architecture: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory
Logistics and Mobility: Specialisation Engineering Science: Elective Compulsory
Mechanical Engineering: Core qualification: Compulsory
Mechatronics: Core qualification: Compulsory
Naval Architecture: Core qualification: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L1085: Fundamentals of Materials Science I
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Jörg Weißmüller
Language DE
Cycle WiSe
Content
Literature

Vorlesungsskript

W.D. Callister: Materials Science and Engineering - An Introduction. 5th ed., John Wiley & Sons, Inc., New York, 2000, ISBN 0-471-32013-7


Course L0506: Fundamentals of Materials Science II (Advanced Ceramic Materials, Polymers and Composites)
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Bodo Fiedler, Prof. Gerold Schneider
Language DE
Cycle SoSe
Content Chemische Bindungen und Aufbau von Festkörpern; Kristallaufbau; Werkstoffprüfung; Schweißbarkeit; Herstellung von Keramiken; Aufbau und Eigenschaften der Keramik; Herstellung, Aufbau und Eigenschaften von Gläsern; Polymerwerkstoffe, Makromolekularer Aufbau; Struktur und Eigenschaften der Polymere; Polymerverarbeitung; Verbundwerkstoffe     
Literature

Vorlesungsskript

W.D. Callister: Materials Science and Engineering -An Introduction-5th ed., John Wiley & Sons, Inc., New York, 2000, ISBN 0-471-32013-7

Course L1095: Physical and Chemical Basics of Materials Science
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Stefan Müller
Language DE
Cycle WiSe
Content
  • Motivation: „Atoms in Mechanical Engineering?“
  • Basics: Force and Energy
  • The electromagnetic Interaction
  • „Detour“: Mathematics (complex e-funktion etc.)
  • The atom: Bohr's model of the atom
  • Chemical bounds
  • The multi part problem: Solutions and strategies
  • Descriptions of using statistical thermodynamics
  • Elastic theory of atoms
  • Consequences of atomar properties on makroskopic Properties: Discussion of examples (metals, semiconductors, hybrid systems)
Literature

Für den Elektromagnetismus:

  • Bergmann-Schäfer: „Lehrbuch der Experimentalphysik“, Band 2: „Elektromagnetismus“, de Gruyter

Für die Atomphysik:

  • Haken, Wolf: „Atom- und Quantenphysik“, Springer

Für die Materialphysik und Elastizität:

  • Hornbogen, Warlimont: „Metallkunde“, Springer


Module M0808: Finite Elements Methods

Courses
Title Typ Hrs/wk CP
Finite Element Methods (L0291) Lecture 2 3
Finite Element Methods (L0804) Recitation Section (large) 2 3
Module Responsible Prof. Otto von Estorff
Admission Requirements None
Recommended Previous Knowledge

Mechanics I (Statics, Mechanics of Materials) and Mechanics II (Hydrostatics, Kinematics, Dynamics)
Mathematics I, II, III (in particular differential equations)

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students possess an in-depth knowledge regarding the derivation of the finite element method and are able to give an overview of the theoretical and methodical basis of the method.



Skills

The students are capable to handle engineering problems by formulating suitable finite elements, assembling the corresponding system matrices, and solving the resulting system of equations.



Personal Competence
Social Competence

Students can work in small groups on specific problems to arrive at joint solutions.

Autonomy

The students are able to independently solve challenging computational problems and develop own finite element routines. Problems can be identified and the results are critically scrutinized.



Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung
Compulsory Bonus Form Description
No 20 % Midterm
Examination Written exam
Examination duration and scale 120 min
Assignment for the Following Curricula Civil Engineering: Core qualification: Compulsory
Energy Systems: Core qualification: Elective Compulsory
Aircraft Systems Engineering: Specialisation Aircraft Systems: Elective Compulsory
Aircraft Systems Engineering: Specialisation Air Transportation Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory
International Management and Engineering: Specialisation II. Product Development and Production: Elective Compulsory
Mechatronics: Core qualification: Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Product Development, Materials and Production: Core qualification: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Theoretical Mechanical Engineering: Core qualification: Compulsory
Course L0291: Finite Element Methods
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Otto von Estorff
Language EN
Cycle WiSe
Content

- General overview on modern engineering
- Displacement method
- Hybrid formulation
- Isoparametric elements
- Numerical integration
- Solving systems of equations (statics, dynamics)
- Eigenvalue problems
- Non-linear systems
- Applications

- Programming of elements (Matlab, hands-on sessions)
- Applications

Literature

Bathe, K.-J. (2000): Finite-Elemente-Methoden. Springer Verlag, Berlin

Course L0804: Finite Element Methods
Typ Recitation Section (large)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Otto von Estorff
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0945: Bioprocess Engineering - Advanced

Courses
Title Typ Hrs/wk CP
Bioprocess Engineering - Advanced (L1107) Lecture 2 4
Bioprocess Engineering - Advanced (L1108) Recitation Section (small) 2 2
Module Responsible Prof. An-Ping Zeng
Admission Requirements None
Recommended Previous Knowledge Content of module "Biochemical Engineering I"
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

After successful completion of this module, students should be able to

  • describe and explain different kinetic approaches for growth and substrate-uptake 

  •  identification of scientific problems with concrete industrial use (cultivation of microorganisms and mammalian cells)

  • describe and explain  important downstreaming steps for proteins and their application as well as basic immobilization methods


Skills

After successful completion of this module, students should be able to

- to identifiy scientific questions or possible practical problems for concrete industrial applications (eg cultivation of microorganisms and animal cells ) and to formulate solutions ,

- To assess the application of scale-up criteria for different types of bioreactors and processes and to apply these criteria to given problems (anaerobic , aerobic or microaerobically)

- to formulate questions for the analysis and optimization of real biotechnological production processes appropriate solutions ,

- To describe the effects of the energy generation, the regeneration of reduction equivalents , and the growth inhibition of the behavior of microorganisms and to the total fermentation process qualitatively


- Establish material flow balance equations and solve them to determine the kinetic parameters of different approaches and to calculate immobilization and activity yields ,

- to select process control strategies (batch , fed-batch , continuity ) appropriately and to  calculate basic types and evaluate them.


Personal Competence
Social Competence

After completion of this module participants should be able to debate technical questions in small teams to enhance the ability to take position to their own opinions and increase their capacity for teamwork. 


Autonomy

After completion of this module participants are able to aquire new sources of knowledge and apply their knowledge to previously unknown issues and to present these.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
Bioprocess Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
Technomathematics: Core qualification: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L1107: Bioprocess Engineering - Advanced
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. An-Ping Zeng, Prof. Andreas Liese, Dr. Wael Sabra
Language DE
Cycle WiSe
Content
  • Introduction: state-of-the-art and development trends of microbial and biocatalytic bioprocesses, introduction to the lecture  
  • Enzymatic process I: reactor types and criteria for industrial biotransformations (Prof. Liese)
  • Enzymatic process II (Prof. Liese)
  • Immobilization technologies: basic methods for isoltaed enzymes/ cells (Prof. Liese) 
  • Anaerobic fermentation processes (Prof. Zeng)
  • Microaerobic bioprocesses: kinetics, energetics, optimal O2-supply and scale-up (Prof. Zeng) 
  • Fedbatch process and cultivation with high cell density (Prof. Zeng)
  • Downstream processing of protein bioproduction: basics of chromatography, membrane filtration (Prof. Liese)
  • Cell culture technology and continuous culture: basics, kinetics, media, reactors (Prof. Zeng)
  • Problem-based learning with selected bioprocesses (Prof. Liese, Prof. Zeng) 
Literature

K. Buchholz, V. Kasche, U. Bornscheuer: Biocatalysts and Enzyme Technology, 2. Aufl. Wiley-VCH, 2012

H. Chmiel: Bioprozeßtechnik, Elsevier, 2006

R.H. Balz et al.: Manual of Industrial Microbiology and Biotechnology, 3. edition, ASM Press, 2010 

H.W. Blanch, D. Clark: Biochemical Engineering, Taylor & Francis, 1997 

P. M. Doran: Bioprocess Engineering Principles, 2. edition, Academic Press, 2013


Skripte für die Vorlesung
Course L1108: Bioprocess Engineering - Advanced
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. An-Ping Zeng, Prof. Andreas Liese
Language DE
Cycle WiSe
Content
  • Introduction: state-of-the-art and development trends of microbial and biocatalytic bioprocesses, introduction to the lecture  
  • Enzymatic process I: reactor types and criteria for industrial biotransformations (Prof. Liese)
  • Enzymatic process II (Prof. Liese)
  • Immobilization technologies: basic methods for isoltaed enzymes/ cells (Prof. Liese) 
  • Anaerobic fermentation processes (Prof. Zeng)
  • Microaerobic bioprocesses: kinetics, energetics, optimal O2-supply and scale-up (Prof. Zeng) 
  • Fedbatch process and cultivation with high cell density (Prof. Zeng)
  • Downstream processing of protein bioproduction: basics of chromatography, membrane filtration (Prof. Liese)
  • Cell culture technology and continuous culture: basics, kinetics, media, reactors (Prof. Zeng)
  • Problem-based learning with selected bioprocesses (Prof. Liese, Prof. Zeng) 

The students present exercises and discuss them with their fellow students and faculty statt. In the PBL part of the class the students discuss scientific questions in teams. They acquire knowledge and apply it to unknown questions, present their results and argue their opinions.

Literature

K. Buchholz, V. Kasche, U. Bornscheuer: Biocatalysts and Enzyme Technology, 2. Aufl. Wiley-VCH, 2012

H. Chmiel: Bioprozeßtechnik, Elsevier, 2006

R.H. Balz et al.: Manual of Industrial Microbiology and Biotechnology, 3. edition, ASM Press, 2010 

H.W. Blanch, D. Clark: Biochemical Engineering, Taylor & Francis, 1997 

P. M. Doran: Bioprocess Engineering Principles, 2. edition, Academic Press, 2013


Skripte für die Vorlesung

Module M1279: MED II: Introduction to Biochemistry and Molecular Biology

Courses
Title Typ Hrs/wk CP
Introduction to Biochemistry and Molecular Biology (L0386) Lecture 2 3
Module Responsible Prof. Hans-Jürgen Kreienkamp
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students can
  • describe basic biomolecules;
  • explain how genetic information is coded in the DNA;
  • explain the connection between DNA and proteins;
Skills The students can
  • recognize the importance of molecular parameters for the course of a disease;
  • describe selected molecular-diagnostic procedures;
  • explain the relevance of these procedures for some diseases
Personal Competence
Social Competence

The students can participate in discussions in research and medicine on a technical level.

Autonomy

The students can develop understanding of topics from the course, using technical literature, by themselves.

Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Credit points 3
Studienleistung None
Examination Written exam
Examination duration and scale 60 minutes
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
General Engineering Science (English program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory
Mechanical Engineering: Specialisation Biomechanics: Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0386: Introduction to Biochemistry and Molecular Biology
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Hans-Jürgen Kreienkamp
Language DE
Cycle WiSe
Content
Literature

Müller-Esterl, Biochemie, Spektrum Verlag, 2010; 2. Auflage

Löffler, Basiswissen Biochemie, 7. Auflage, Springer, 2008




Module M0783: Measurements: Methods and Data Processing

Courses
Title Typ Hrs/wk CP
EE Experimental Lab (L0781) Practical Course 2 2
Measurements: Methods and Data Processing (L0779) Lecture 2 3
Measurements: Methods and Data Processing (L0780) Recitation Section (small) 1 1
Module Responsible Prof. Alexander Schlaefer
Admission Requirements None
Recommended Previous Knowledge

principles of mathematics
principles of electrical engineering 

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students are able to explain the purpose of metrology and the acquisition and processing of measurements. They can detail aspects of probability theory and errors, and explain the processing of stochastic signals. Students know methods to digitalize and describe measured signals.



Skills

The students are able to evaluate problems of metrology and to apply methods for describing and processing of measurements.


Personal Competence
Social Competence

The students solve problems in small groups.

Autonomy

The students can reflect their knowledge and discuss and evaluate their results.


Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Studienleistung
Compulsory Bonus Form Description
Yes 10 % Excercises
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Electrical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Elective Compulsory
Electrical Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Electrical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Course L0781: EE Experimental Lab
Typ Practical Course
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer, Prof. Christian Schuster, Prof. Thanh Trung Do, Prof. Rolf-Rainer Grigat, Prof. Arne Jacob, Prof. Herbert Werner, Dozenten des SD E, Prof. Heiko Falk
Language DE
Cycle WiSe
Content lab experiments: digital circuits, semiconductors, micro controllers, analog circuits, AC power, electrical machines
Literature Wird in der Lehrveranstaltung festgelegt
Course L0779: Measurements: Methods and Data Processing
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language DE
Cycle WiSe
Content

introduction, systems and errors in metrology, probability theory, measuring stochastic signals, describing measurements, acquisition of analog signals, applied metrology

Literature

Puente León, Kiencke: Messtechnik, Springer 2012
Lerch: Elektrische Messtechnik, Springer 2012

Weitere Literatur wird in der Veranstaltung bekanntgegeben.

Course L0780: Measurements: Methods and Data Processing
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Alexander Schlaefer
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0688: Technical Thermodynamics II

Courses
Title Typ Hrs/wk CP
Technical Thermodynamics II (L0449) Lecture 2 4
Technical Thermodynamics II (L0450) Recitation Section (large) 1 1
Technical Thermodynamics II (L0451) Recitation Section (small) 1 1
Module Responsible Prof. Gerhard Schmitz
Admission Requirements None
Recommended Previous Knowledge

Elementary knowledge in Mathematics, Mechanics and Technical Thermodynamics I

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are familiar with different cycle processes like Joule, Otto, Diesel, Stirling, Seiliger and Clausius-Rankine. They are able to derive energetic and exergetic efficiencies and know the influence different factors. They know the difference between anti clockwise and clockwise cycles (heat-power cycle, cooling cycle). They have increased knowledge of steam cycles and are able to draw the different cycles in Thermodynamics related diagrams. They know the laws of gas mixtures, especially of humid air processes and are able to perform simple combustion calculations. They are provided with basic knowledge in gas dynamics and know the definition of the speed of sound and know about a Laval nozzle.


Skills

Students are able to use thermodynamic laws for the design of technical processes. Especially they are able to formulate energy, exergy- and entropy balances and by this to optimise technical processes. They are able to perform simple safety calculations in regard to an outflowing gas from a tank. They are able to transform a verbal formulated message into an abstract formal procedure.



Personal Competence
Social Competence

The students are able to discuss in small groups and develop an approach.

Autonomy

Students are able to define independently tasks, to get new knowledge from existing knowledge as well as to find ways to use the knowledge in practice.



Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program): Core qualification: Compulsory
General Engineering Science (German program, 7 semester): Core qualification: Compulsory
Bioprocess Engineering: Core qualification: Compulsory
Energy and Environmental Engineering: Core qualification: Compulsory
General Engineering Science (English program): Core qualification: Compulsory
General Engineering Science (English program, 7 semester): Core qualification: Compulsory
Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory
Mechanical Engineering: Core qualification: Compulsory
Mechatronics: Core qualification: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Process Engineering: Core qualification: Compulsory
Course L0449: Technical Thermodynamics II
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Gerhard Schmitz
Language DE
Cycle WiSe
Content

8. Cycle processes

7. Gas - vapor - mixtures

10. Open sytems with constant flow rates

11. Combustion processes

12. Special fields of Thermodynamics

Literature
  • Schmitz, G.: Technische Thermodynamik, TuTech Verlag, Hamburg, 2009
  • Baehr, H.D.; Kabelac, S.: Thermodynamik, 15. Auflage, Springer Verlag, Berlin 2012

  • Potter, M.; Somerton, C.: Thermodynamics for Engineers, Mc GrawHill, 1993
Course L0450: Technical Thermodynamics II
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Gerhard Schmitz
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0451: Technical Thermodynamics II
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Gerhard Schmitz
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0568: Theoretical Electrical Engineering II: Time-Dependent Fields

Courses
Title Typ Hrs/wk CP
Theoretical Electrical Engineering II: Time-Dependent Fields (L0182) Lecture 3 5
Theoretical Electrical Engineering II: Time-Dependent Fields (L0183) Recitation Section (small) 2 1
Module Responsible Prof. Christian Schuster
Admission Requirements None
Recommended Previous Knowledge

Electrical Engineering I, Electrical Engineering II, Theoretical Electrical Engineering I

Mathematics I, Mathematics II, Mathematics III, Mathematics IV


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to explain fundamental formulas, relations, and methods related to the theory of time-dependent electromagnetic fields. They can assess the principal behavior and characteristics of quasistationary and fully dynamic fields with regard to respective sources. They can describe the properties of complex electromagnetic fields by means of superposition of solutions for simple fields. The students are aware of applications for the theory of time-dependent electromagnetic fields and are able to explicate these.


Skills

Students are able to apply a variety of procedures in order to solve the diffusion and the wave equation for general time-dependent field problems. They can assess the principal effects of given time-dependent sources of fields and analyze these quantitatively. They can deduce meaningful quantities for the characterization of fully dynamic fields (wave impedance, skin depth, Poynting-vector, radiation resistance, etc.) from given fields and interpret them with regard to practical applications.


Personal Competence
Social Competence

Students are able to work together on subject related tasks in small groups. They are able to present their results effectively (e.g. during exercise sessions).


Autonomy

Students are capable to gather necessary information from provided references and relate this information to the lecture. They are able to continually reflect their knowledge by means of activities that accompany the lecture, such as short oral quizzes during the lectures and exercises that are related to the exam. Based on respective feedback, students are expected to adjust their individual learning process. They are able to draw connections between acquired knowledge and ongoing research at the Hamburg University of Technology (TUHH), e.g. in the area of high frequency engineering and optics.


Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 90-150 minutes
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Electrical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Compulsory
Electrical Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Electrical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Course L0182: Theoretical Electrical Engineering II: Time-Dependent Fields
Typ Lecture
Hrs/wk 3
CP 5
Workload in Hours Independent Study Time 108, Study Time in Lecture 42
Lecturer Prof. Christian Schuster
Language DE
Cycle WiSe
Content

- Theory and principal characteristics of quasistationary electromagnetic fields

- Electromagnetic induction and law of induction

- Skin effect and eddy currents

- Shielding of time variable magnetic fields

- Theory and principal characteristics of fully dynamic electromagnetic fields

- Wave equations and properties of planar waves

- Polarization and superposition of planar waves

- Reflection and refraction of planar waves at boundary surfaces

- Waveguide theory

- Rectangular waveguide, planar optical waveguide

- Elektrical and magnetical dipol radiation

- Simple arrays of antennas


Literature

- G. Lehner, "Elektromagnetische Feldtheorie: Für Ingenieure und Physiker", Springer (2010)

- H. Henke, "Elektromagnetische Felder: Theorie und Anwendung", Springer (2011)

- W. Nolting, "Grundkurs Theoretische Physik 3: Elektrodynamik", Springer (2011)

- D. Griffiths, "Introduction to Electrodynamics", Pearson (2012)

- J. Edminister, "Schaum's Outline of Electromagnetics", Mcgraw-Hill (2013)

- Richard Feynman, "Feynman Lectures on Physics: Volume 2", Basic Books (2011)


Course L0183: Theoretical Electrical Engineering II: Time-Dependent Fields
Typ Recitation Section (small)
Hrs/wk 2
CP 1
Workload in Hours Independent Study Time 2, Study Time in Lecture 28
Lecturer Prof. Christian Schuster
Language DE
Cycle WiSe
Content

- Theory and principal characteristics of quasistationary electromagnetic fields

- Electromagnetic induction and law of induction

- Skin effect and eddy currents

- Shielding of time variable magnetic fields

- Theory and principal characteristics of fully dynamic electromagnetic fields

- Wave equations and properties of planar waves

- Polarization and superposition of planar waves

- Reflection and refraction of planar waves at boundary surfaces

- Waveguide theory

- Rectangular waveguide, planar optical waveguide

- Elektrical and magnetical dipol radiation

- Simple arrays of antennas


Literature

- G. Lehner, "Elektromagnetische Feldtheorie: Für Ingenieure und Physiker", Springer (2010)

- H. Henke, "Elektromagnetische Felder: Theorie und Anwendung", Springer (2011)

- W. Nolting, "Grundkurs Theoretische Physik 3: Elektrodynamik", Springer (2011)

- D. Griffiths, "Introduction to Electrodynamics", Pearson (2012)

- J. Edminister, "Schaum's Outline of Electromagnetics", Mcgraw-Hill (2013)

- Richard Feynman, "Feynman Lectures on Physics: Volume 2", Basic Books (2011)


Module M0538: Heat and Mass Transfer

Courses
Title Typ Hrs/wk CP
Heat and Mass Transfer (L0101) Lecture 2 2
Heat and Mass Transfer (L0102) Recitation Section (small) 1 2
Heat and Mass Transfer (L1868) Recitation Section (large) 1 2
Module Responsible Prof. Irina Smirnova
Admission Requirements None
Recommended Previous Knowledge

Basic knowledge: Technical Thermodynamics


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • The students are capable of explaining qualitative and determining quantitative heat transfer in procedural apparatus (e. g. heat exchanger, chemical reactors).
  • They are capable of distinguish and characterize different kinds of heat transfer mechanisms namely heat conduction, heat transfer and thermal radiation.
  • The students have the ability to explain the physical basis for mass transfer in detail and to describe mass transfer qualitative and quantitative by using suitable mass transfer theories.
  • They are able to depict the analogy between heat- and mass transfer and to describe complex linked processes in detail.



Skills
  • The students are able to set reasonable system boundaries for a given transport problem by using the gained knowledge and to balance the corresponding energy and mass flow, respectively.
  • They are capable to solve specific heat transfer problems (e.g. heated chemical reactors, temperature alteration in fluids) and to calculate the corresponding heat flows.
  • Using dimensionless quantities, the students can execute scaling up of technical processes or apparatus.
  • They are able to distinguish between diffusion, convective mass transition and mass transfer. They can use this knowledge for the description and design of apparatus (e.g. extraction column, rectification column).
  • In this context, the students are capable to choose and design fundamental types of heat and mass exchanger for a specific application considering their advantages and disadvantages, respectively.
  • In addition, they can calculate both, steady-state and non-steady-state processes in procedural apparatus.
  •  The students are capable to connect their knowledge obtained in this course  with knowlegde of other courses (In particular the courses thermodynamics, fluid mechanics and chemical process engineering) to solve concrete technical problems.


Personal Competence
Social Competence
  • The students are capable to work on subject-specific challenges in teams and to present the results orally in a reasonable manner to tutors and other students.


Autonomy
  • The students are able to find and evaluate necessary information from suitable sources
  • They are able to prove their level of knowledge during the course with accompanying procedure continuously (clicker-system, exam-like assignments) and on this basis they can control their learning processes.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 120 minutes; theoretical questions and calculations
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Process Engineering: Compulsory
General Engineering Science (German program): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (German program): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Process Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory
Bioprocess Engineering: Core qualification: Compulsory
Energy and Environmental Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (English program): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (English program): Specialisation Process Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Process Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Process Engineering: Core qualification: Compulsory
Course L0101: Heat and Mass Transfer
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Irina Smirnova
Language DE
Cycle WiSe
Content
  1. Heat transfer
    • Introduction, one-dimensional heat conduction
    • Convective heat transfer
    • Multidimensional heat conduction
    • Non-steady heat conduction
    • Thermal radiation
  2. Mass transfer
    • one-way diffusion, equimolar countercurrent diffusion
    • boundary layer theory, non-steady mass transfer
    • Heat and mass transfer single particle/ fixed bed
    • Mass transfer and chemical reactions

Literature
  1. H.D. Baehr und K. Stephan: Wärme- und Stoffübertragung, Springer
  2. VDI-Wärmeatlas



Course L0102: Heat and Mass Transfer
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Irina Smirnova
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L1868: Heat and Mass Transfer
Typ Recitation Section (large)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Irina Smirnova
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0675: Introduction to Communications and Random Processes

Courses
Title Typ Hrs/wk CP
Introduction to Communications and Random Processes (L0442) Lecture 3 4
Introduction to Communications and Random Processes (L0443) Recitation Section (large) 1 2
Module Responsible Prof. Gerhard Bauch
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics 1-3
  • Signals and Systems
  • Basic knowledge of probability theory
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students know and understand the fundamental building blocks of a communications system. They can describe and analyse the individual building blocks using knowledge of signal and system theory as well as the theory of stochastic processes. The are aware of the essential resources and evaluation criteria of information transmission and are able to design and evaluate a basic communications system. 
Skills The students are able to design and evaluate a basic communications system. In particular, they can estimate the required resources in terms of bandwidth and power. They are able to assess essential evaluation parameters of a basic communications system such as bandwidth efficiency or bit error rate and to decide for a suitable transmission method.
Personal Competence
Social Competence

 The students can jointly solve specific problems.

Autonomy

The students are able to acquire relevant information from appropriate literature sources. They can control their level of knowledge during the lecture period by solving tutorial problems, software tools, clicker system.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Electrical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Electrical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory
Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Course L0442: Introduction to Communications and Random Processes
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Gerhard Bauch
Language DE/EN
Cycle WiSe
Content
  • Fundamentals of random processes

  • Introduction to communications engineering

  • Quadrature amplitude modulation

  • Description of radio frequency transmission in the equivalent complex baseband

  • Transmission channels, channel models

  • Analog digital conversion: Sampling, quantization, pulsecode modulation (PCM)

  • Fundamentals of information theory, source coding, channel coding

  • Digital baseband transmission: Pulse shaping, eye diagramm, 1. and 2. Nyquist condition, matched filter, detection, error probability

  • Fundamentals of digital modulation

Literature

K. Kammeyer: Nachrichtenübertragung, Teubner

P.A. Höher: Grundlagen der digitalen Informationsübertragung, Teubner.

M. Bossert: Einführung in die Nachrichtentechnik, Oldenbourg.

J.G. Proakis, M. Salehi: Grundlagen der Kommunikationstechnik. Pearson Studium.

J.G. Proakis, M. Salehi: Digital Communications. McGraw-Hill.

S. Haykin: Communication Systems. Wiley

J.G. Proakis, M. Salehi: Communication Systems Engineering. Prentice-Hall.

J.G. Proakis, M. Salehi, G. Bauch, Contemporary Communication Systems. Cengage Learning.






Course L0443: Introduction to Communications and Random Processes
Typ Recitation Section (large)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Gerhard Bauch
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0959: Mechanics III (Hydrostatics, Kinematics, Kinetics I)

Courses
Title Typ Hrs/wk CP
Mechanics III (Hydrostatics, Kinematics, Kinetics I) (L1134) Lecture 3 3
Mechanics III (Hydrostatics, Kinematics, Kinetics I) (L1135) Recitation Section (small) 2 2
Mechanics III (Hydrostatics, Kinematics, Kinetics I) (L1136) Recitation Section (large) 1 1
Module Responsible Prof. Robert Seifried
Admission Requirements None
Recommended Previous Knowledge

Mathematics I, II, Mechanics I (Statics)

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students can

  • describe the axiomatic procedure used in mechanical contexts;
  • explain important steps in model design;
  • present technical knowledge in stereostatics.
Skills

The students can

  • explain the important elements of mathematical / mechanical analysis and model formation, and apply it to the context of their own problems;
  • apply basic hydrostatical, kinematic and kinetic methods to engineering problems;
  • estimate the reach and boundaries of statical methods and extend them to be applicable to wider problem sets.
Personal Competence
Social Competence

The students can work in groups and support each other to overcome difficulties.

Autonomy

Students are capable of determining their own strengths and weaknesses and to organize their time and learning based on those.

Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Credit points 6
Studienleistung
Compulsory Bonus Form Description
No 20 % Midterm Wird nur im WiSe angeboten
Examination Written exam
Examination duration and scale 120 min
Assignment for the Following Curricula General Engineering Science (German program): Core qualification: Compulsory
General Engineering Science (German program, 7 semester): Core qualification: Compulsory
Mechanical Engineering: Core qualification: Compulsory
Mechatronics: Core qualification: Compulsory
Naval Architecture: Core qualification: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L1134: Mechanics III (Hydrostatics, Kinematics, Kinetics I)
Typ Lecture
Hrs/wk 3
CP 3
Workload in Hours Independent Study Time 48, Study Time in Lecture 42
Lecturer Prof. Robert Seifried
Language DE
Cycle WiSe
Content

Hydrostatics

Kinematics

  • Kinematics of points and relative motion
  • Planar and spatial motion of point systems and rigid bodies 

Dynamics

  • Terms
  • Fundamental equations
  • Motion of the rigid body in 3D-space
  • Dynamics of gyroscopes, rotors
  • Realtive kinetics
  • Systems with non-constant mass
Literature K. Magnus, H.H. Müller-Slany: Grundlagen der Technischen Mechanik. 7. Auflage, Teubner (2009).
D. Gross, W. Hauger, J. Schröder, W. Wall: Technische Mechanik 3 und 4. 11. Auflage, Springer (2011).
Course L1135: Mechanics III (Hydrostatics, Kinematics, Kinetics I)
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Robert Seifried
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L1136: Mechanics III (Hydrostatics, Kinematics, Kinetics I)
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Robert Seifried
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0655: Computational Fluid Dynamics I

Courses
Title Typ Hrs/wk CP
Computational Fluid Dynamics I (L0235) Lecture 2 3
Computational Fluid Dynamics I (L0419) Recitation Section (large) 2 3
Module Responsible Prof. Thomas Rung
Admission Requirements None
Recommended Previous Knowledge
  • Mathematical Methods for Engineers
  • Fundamentals of Differential/integral calculus and series expansions
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students are able to list the basic numerics of partial differential equations.


Skills

The students are able develop appropriate numerical integration in space and time for the governing partial differential equations. They can code computational algorithms in a structured way.



Personal Competence
Social Competence

The students can arrive at work results in groups and document them.


Autonomy

The students can independently analyse approaches to solving specific problems.



Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 2h
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory
General Engineering Science (German program): Specialisation Naval Architecture: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Naval Architecture: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Elective Compulsory
General Engineering Science (English program): Specialisation Naval Architecture: Compulsory
General Engineering Science (English program): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Naval Architecture: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Elective Compulsory
Naval Architecture: Core qualification: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0235: Computational Fluid Dynamics I
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Thomas Rung
Language DE
Cycle WiSe
Content

Fundamentals of computational modelling of thermofluid dynamic problems. Development of numerical algorithms.

  1. Partial differential equations
  2. Foundations of finite numerical approximations
  3. Computation of potential flows
  4. Introduction of finite-differences
  5. Approximation of convective, diffusive and transient transport processes
  6. Formulation of boundary conditions and initial conditions
  7. Assembly and solution of algebraic equation systems
  8. Facets of weighted -residual approaches
  9. Finite volume methods
  10. Basics of grid generation
Literature

Ferziger and Peric: Computational Methods for Fluid Dynamics, Springer

Course L0419: Computational Fluid Dynamics I
Typ Recitation Section (large)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Thomas Rung
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0833: Introduction to Control Systems

Courses
Title Typ Hrs/wk CP
Introduction to Control Systems (L0654) Lecture 2 4
Introduction to Control Systems (L0655) Recitation Section (small) 2 2
Module Responsible Prof. Herbert Werner
Admission Requirements None
Recommended Previous Knowledge

Representation of signals and systems in time and frequency domain, Laplace transform


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can represent dynamic system behavior in time and frequency domain, and can in particular explain properties of first and second order systems
  • They can explain the dynamics of simple control loops and interpret dynamic properties in terms of frequency response and root locus
  • They can explain the Nyquist stability criterion and the stability margins derived from it.
  • They can explain the role of the phase margin in analysis and synthesis of control loops
  • They can explain the way a PID controller affects a control loop in terms of its frequency response
  • They can explain issues arising when controllers designed in continuous time domain are implemented digitally
Skills
  • Students can transform models of linear dynamic systems from time to frequency domain and vice versa
  • They can simulate and assess the behavior of systems and control loops
  • They can design PID controllers with the help of heuristic (Ziegler-Nichols) tuning rules
  • They can analyze and synthesize simple control loops with the help of root locus and frequency response techniques
  • They can calculate discrete-time approximations of controllers designed in continuous-time and use it for digital implementation
  • They can use standard software tools (Matlab Control Toolbox, Simulink) for carrying out these tasks
Personal Competence
Social Competence Students can work in small groups to jointly solve technical problems, and experimentally validate their controller designs
Autonomy

Students can obtain information from provided sources (lecture notes, software documentation, experiment guides) and use it when solving given problems.

They can assess their knowledge in weekly on-line tests and thereby control their learning progress.



Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 120 min
Assignment for the Following Curricula General Engineering Science (German program): Core qualification: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Naval Architecture: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Civil Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Process Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Aircraft Systems Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Product Development and Production: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory
Bioprocess Engineering: Core qualification: Compulsory
Computer Science: Specialisation Computational Mathematics: Elective Compulsory
Electrical Engineering: Core qualification: Compulsory
Energy and Environmental Engineering: Core qualification: Compulsory
General Engineering Science (English program): Core qualification: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Bioprocess Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Naval Architecture: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Civil Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Process Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Aircraft Systems Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Product Development and Production: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Logistics and Mobility: Specialisation Engineering Science: Elective Compulsory
Mechanical Engineering: Core qualification: Compulsory
Mechatronics: Core qualification: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course Core Studies: Elective Compulsory
Process Engineering: Core qualification: Compulsory
Course L0654: Introduction to Control Systems
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language DE
Cycle WiSe
Content

Signals and systems

  • Linear systems, differential equations and transfer functions
  • First and second order systems, poles and zeros, impulse and step response
  • Stability

Feedback systems

  • Principle of feedback, open-loop versus closed-loop control
  • Reference tracking and disturbance rejection
  • Types of feedback, PID control
  • System type and steady-state error, error constants
  • Internal model principle

Root locus techniques

  • Root locus plots
  • Root locus design of PID controllers

Frequency response techniques

  • Bode diagram
  • Minimum and non-minimum phase systems
  • Nyquist plot, Nyquist stability criterion, phase and gain margin
  • Loop shaping, lead lag compensation
  • Frequency response interpretation of PID control

Time delay systems

  • Root locus and frequency response of time delay systems
  • Smith predictor

Digital control

  • Sampled-data systems, difference equations
  • Tustin approximation, digital implementation of PID controllers

Software tools

  • Introduction to Matlab, Simulink, Control toolbox
  • Computer-based exercises throughout the course
Literature
  • Werner, H., Lecture Notes „Introduction to Control Systems“
  • G.F. Franklin, J.D. Powell and A. Emami-Naeini "Feedback Control of Dynamic Systems", Addison Wesley, Reading, MA, 2009
  • K. Ogata "Modern Control Engineering", Fourth Edition, Prentice Hall, Upper Saddle River, NJ, 2010
  • R.C. Dorf and R.H. Bishop, "Modern Control Systems", Addison Wesley, Reading, MA 2010
Course L0655: Introduction to Control Systems
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1333: BIO I: Implants and Fracture Healing

Courses
Title Typ Hrs/wk CP
Implants and Fracture Healing (L0376) Lecture 2 3
Module Responsible Prof. Michael Morlock
Admission Requirements None
Recommended Previous Knowledge

It is recommended to participate in "Introduction into Anatomie" before attending "Implants and Fracture Healing".

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students can describe the different ways how bones heal, and the requirements for their existence.

The students can name different treatments for the spine and hollow bones under given fracture morphologies.

Skills

The students can determine the forces acting within the human body under quasi-static situations under specific assumptions.

Personal Competence
Social Competence

The students can, in groups, solve basic numerical modeling tasks for the calculation of internal forces.

Autonomy

The students can, in groups, solve basic numerical modeling tasks for the calculation of internal forces.

Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Credit points 3
Studienleistung None
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory
Mechanical Engineering: Specialisation Biomechanics: Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0376: Implants and Fracture Healing
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Michael Morlock
Language DE
Cycle WiSe
Content

Topics to be covered include:

1.    Introduction (history, definitions, background importance)

2.    Bone (anatomy, properties, biology, adaptations in femur, tibia, humerus, radius)

3.    Spine (anatomy, biomechanics, function, vertebral bodies, intervertebral disc, ligaments)

3.1  The spine in its entirety

3.2  Cervical spine

3.3  Thoracic spine

3.4  Lumbar spine

3.5  Injuries and diseases

4.    Pelvis (anatomy, biomechanics, fracture treatment)

5     Fracture Healing

5.1  Basics and biology of fracture repair

5.2  Clinical principals and terminology of fracture treatment

5.3  Biomechanics of fracture treatment

5.3.1    Screws

5.3.2    Plates

5.3.3    Nails

5.3.4    External fixation devices

5.3.5    Spine implants

6.0       New Implants


Literature

Cochran V.B.: Orthopädische Biomechanik

Mow V.C., Hayes W.C.: Basic Orthopaedic Biomechanics

White A.A., Panjabi M.M.: Clinical biomechanics of the spine

Nigg, B.: Biomechanics of the musculo-skeletal system

Schiebler T.H., Schmidt W.: Anatomie

Platzer: dtv-Atlas der Anatomie, Band 1 Bewegungsapparat



Module M0708: Electrical Engineering III: Circuit Theory and Transients

Courses
Title Typ Hrs/wk CP
Circuit Theory (L0566) Lecture 3 4
Circuit Theory (L0567) Recitation Section (small) 2 2
Module Responsible Prof. Arne Jacob
Admission Requirements None
Recommended Previous Knowledge

Electrical Engineering I and II, Mathematics I and II


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to explain the basic methods for calculating electrical circuits. They know the Fourier series analysis of linear networks driven by periodic signals. They know the methods for transient analysis of linear networks in time and in frequency domain, and they are able to explain the frequency behaviour and the synthesis of passive two-terminal-circuits.


Skills

The students are able to calculate currents and voltages in linear networks by means of basic methods, also when driven by periodic signals. They are able to calculate transients in electrical circuits in time and frequency domain and are able to explain the respective transient behaviour. They are able to analyse and to synthesize the frequency behaviour of passive two-terminal-circuits.


Personal Competence
Social Competence

Students work on exercise tasks in small guided groups. They are encouraged to present and discuss their results within the group.


Autonomy

The students are able to find out the required methods for solving the given practice problems. Possibilities are given to test their knowledge during the lectures continuously by means of short-time tests. This allows them to control independently their educational objectives. They can link their gained knowledge to other courses like Electrical Engineering I and Mathematics I.


Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 150 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Electrical Engineering: Compulsory
General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Compulsory
Electrical Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Electrical Engineering: Compulsory
General Engineering Science (English program): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory
Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory
Computational Science and Engineering: Specialisation Mathematics & Engineering Science: Elective Compulsory
Mechatronics: Core qualification: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0566: Circuit Theory
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Arne Jacob
Language DE
Cycle WiSe
Content

- Circuit theorems

- N-port circuits

- Periodic excitation of linear circuits

- Transient analysis in time domain

- Transient analysis in frequency domain; Laplace Transform

- Frequency behaviour of passive one-ports


Literature

- M. Albach, "Grundlagen der Elektrotechnik 1", Pearson Studium (2011)

- M. Albach, "Grundlagen der Elektrotechnik 2", Pearson Studium (2011)

- L. P. Schmidt, G. Schaller, S. Martius, "Grundlagen der Elektrotechnik 3", Pearson Studium (2011)

- T. Harriehausen, D. Schwarzenau, "Moeller Grundlagen der Elektrotechnik", Springer (2013) 

- A. Hambley, "Electrical Engineering: Principles and Applications", Pearson (2008)

- R. C. Dorf, J. A. Svoboda, "Introduction to electrical circuits", Wiley (2006)

- L. Moura, I. Darwazeh, "Introduction to Linear Circuit Analysis and Modeling", Amsterdam Newnes (2005)


Course L0567: Circuit Theory
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Arne Jacob
Language DE
Cycle WiSe
Content see interlocking course
Literature

siehe korrespondierende Lehrveranstaltung

see interlocking course

Module M0755: Geotechnics II

Courses
Title Typ Hrs/wk CP
Foundation Engineering (L0552) Lecture 2 2
Foundation Engineering (L0553) Recitation Section (large) 2 2
Foundation Engineering (L1494) Recitation Section (small) 2 2
Module Responsible Prof. Jürgen Grabe
Admission Requirements None
Recommended Previous Knowledge

Modules:

  • Mechanics I-II
  • Geotechnics I


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students know the basic principles and methods which are required to verificate the stability of geotechnical structures.
Skills

After successful completion of the module the students are able to:

  • verificate the stability and usability of foundations,
  • know individual methods of ground improvement and apply them in their range of application,
  • design retaining walls.
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 60 minutes
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Civil- and Enviromental Engeneering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Civil Engineering: Elective Compulsory
Civil- and Environmental Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Civil- and Enviromental Engeneering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Civil Engineering: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0552: Foundation Engineering
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Jürgen Grabe
Language DE
Cycle WiSe
Content
  • Shallow foundations
  • Pile foundations
  • Ground improvement
  • Retaining walls
  • Underpinning
  • Groundwater Conservation
  • Cut-off Walls
Literature
  • Vorlesung/Übung s. www.tu-harburg.de/gbt
  • Grabe, J. (2004): Bodenmechanik und Grundbau
  • Kolymbas, D. (1998): Geotechnik - Bodenmechanik und Grundbau
  • Grundbau-Taschenbuch, neueste Auflage
Course L0553: Foundation Engineering
Typ Recitation Section (large)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Jürgen Grabe
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L1494: Foundation Engineering
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Jürgen Grabe
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0606: Numerical Algorithms in Structural Mechanics

Courses
Title Typ Hrs/wk CP
Numerical Algorithms in Structural Mechanics (L0284) Lecture 2 3
Numerical Algorithms in Structural Mechanics (L0285) Recitation Section (small) 2 3
Module Responsible Prof. Alexander Düster
Admission Requirements None
Recommended Previous Knowledge

Knowledge of partial differential equations is recommended.

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to
+ give an overview of the standard algorithms that are used in finite element programs.
+ explain the structure and algorithm of finite element programs.
+ specify problems of numerical algorithms, to identify them in a given situation and to explain their mathematical and computer science background.

Skills

Students are able to 
+ construct algorithms for given numerical methods.
+ select for a given problem of structural mechanics a suitable algorithm.
+ apply numerical algorithms to solve problems of structural mechanics.
+ implement algorithms in a high-level programming languate (here C++).
+ critically judge and verfiy numerical algorithms.

Personal Competence
Social Competence

Students are able to
+ solve problems in heterogeneous groups and to document the corresponding results.

Autonomy

Students are able to
+ acquire independently knowledge to solve complex problems.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Studienleistung None
Examination Written exam
Examination duration and scale 2h
Assignment for the Following Curricula Materials Science: Specialisation Modeling: Elective Compulsory
Naval Architecture and Ocean Engineering: Core qualification: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Course L0284: Numerical Algorithms in Structural Mechanics
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Alexander Düster
Language DE
Cycle SoSe
Content

1. Motivation
2. Basics of C++
3. Numerical integration
4. Solution of nonlinear problems
5. Solution of linear equation systems
6. Verification of numerical algorithms
7. Selected algorithms and data structures of a finite element code

Literature

[1] D. Yang, C++ and object-oriented numeric computing, Springer, 2001.
[2] K.-J. Bathe, Finite-Elemente-Methoden, Springer, 2002.

Course L0285: Numerical Algorithms in Structural Mechanics
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Alexander Düster
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0709: Electrical Engineering IV: Transmission Lines and Research Seminar

Courses
Title Typ Hrs/wk CP
Research Seminar Electrical Engineering, Computer Science, Mathematics (L0571) Seminar 2 2
Transmission Line Theory (L0570) Lecture 2 3
Transmission Line Theory (L0572) Recitation Section (large) 2 1
Module Responsible Prof. Arne Jacob
Admission Requirements None
Recommended Previous Knowledge

Electrical Engineering I-III, Mathematics I-III

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the fundamentals of wave propagation on transmission lines at low and high frequencies. They are able to analyze circuits with transmission lines in time and frequency domain. They can describe simple equivalent circuits of transmission lines. They are able to solve problems with coupled transmission lines. They can present and discuss a self-chosen research topic.


Skills

Students can analyze and calculate the propagation of waves in simple circuits with transmission lines. They are able to analyze circuits in frequency domain and with the Smith chart. They can analyze equivalent circuits of transmission lines. They are able to solve problems including coupled transmission lines using the vectorial transmission line equations. They are able to give a talk to professionals.


Personal Competence
Social Competence

Students can analyze and solve problems in small groups and discuss their solutions. They can compare the learned theory with experiments in the lecture and discuss it in small groups. They are able to present a research topic to professionals and discuss it with them.


Autonomy

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