Module Manual

Bachelor

Computational Science and Engineering

Cohort: Winter Term 2014

Updated: 17th March 2017

Program description

Content

Engineering disciplines directly benefit from research results in computer science and mathematics to an ever-growing extent. This holds for the development process of products as well as for the design of products themselves. New results in computer science and mathematics are a powerful driver for innovations in engineering, and therefore, computer science and mathematics are central areas of competence both for engineers and for engineering universities.

Due to new research results, engineers are enabled to build flexible systems such that the functionality provided can be automatically adapted to new requirements. It is important to understand that it is not only relevant to combine simple instructions to small programs which are to be executed fast in order to realise desired functionality. Developing systems today means that models of various kinds need to be designed, and, later on, realised by combined hardware and software components. Indeed, often hardware and software systems are even automatically generated from declarative models. Even more importantly, often on the fly reconfiguration of hard and software systems is pursued in order to fulfil flexibility requirements in practical application scenarios. In this context, a combined state-based and continuous modeling approach for system behavior becomes more and more important in a world in which hardware and software systems are tightly coupled.

It becomes clear that desired and unwanted properties of technical systems need to be automatically checked in order to fulfil security, safety, and reliability requirements. In case of a dynamic reconfiguration, satisfaction of certain properties needs to be checked also during the lifetime of a system in order to guarantee a safe and optimal mode of operation for technical systems, be this in medical or industrial application areas. In some cases, new properties or requirements first arise during a system's lifetime. Simulating physical systems it is possible to investigate and optimise certain properties before the production phase begins. On the one hand, new numerical algortihms and techniques allow for a more exact continuous behavior prediction, while, on the other hand, they can be combined with new and expressive discrete modeling techniques for future engineering products that are characterised by behavior switches. Thus, it is important to see that not only partial aspects of technical systems need to be investigated. It becomes clear that state-oriented and continuous models need to be combined in order to describe and design powerful real-world systems such as, e.g., robots or embedded systems, which are to successfully used in, for instance, medical or industrial application contexts.

The world is characterized by global information exchange. The advances started in microelectronics have influenced not only electronic data processing and software technology but have a substantial impact on all areas of everyday life. Many visions for future use of information and communication technology are just emerging. Computer science benefits form engineering science and vice versa. In order to be well prepared for the future, a combined education in computer science and engineering disciplines gives young students an excellent starting point, for research as well as for a career in industry. The study program Computational Science and Engineering systematically combines hardware and software. Given a well-founded mathematical basis, decisions about which parts of a system are best realized in hardware or software need to be based on solid knowledge in computer science and engineering sciences.

The study program Computational Science and Engineering supports this vision in all respects. Building on an integrated computer science and engineering education, students can select a specialisation in

• Computer Science or

• Engineering

in order to finalise their studies.

In the Computer Science and Engineering Master's Program, students later can select specialisation in areas

• Systems Engineering and Robotics

• Scientific Computing

• Reliable Embedded Systems / Cyber Physical Systems

while still be able to flexibly design their studies by choosing some modules from other study programs.

Core qualification

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 Diploma.
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, groups, rings, 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 this knowledge with other classes.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 120 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Computer Science and Engineering: Compulsory
Computer Science: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Computer Science and Engineering: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Technomathematics: Specialisation 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 M0575: Procedural Programming

Courses
Title Typ Hrs/wk CP
Procedural Programming (L0197) Lecture 1 2
Procedural Programming (L0201) Recitation Section (small) 1 1
Procedural Programming (L0202) Laboratory 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
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 (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
Course L0202: Procedural Programming
Typ Laboratory 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 take a look at lecture descriptions
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The Non-technical Elective Study Area

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 “non-technical department” 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, 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 M0743: Electrical Engineering I: Direct Current Networks and Electromagnetic Fields

Courses
Title Typ Hrs/wk CP
Electrical Engineering I: Direct Current Networks and Electromagnetic Fields (L0675) Lecture 3 5
Electrical Engineering I: Direct Current Networks and Electromagnetic Fields (L0676) Recitation Section (small) 2 1
Module Responsible Prof. Manfred Kasper
Admission Requirements
Recommended Previous Knowledge
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 110, Study Time in Lecture 70
Credit points 6
Examination Written exam
Examination duration and scale zweistündig
Assignment for the Following Curricula General Engineering Science (German program): Core qualification: Compulsory
Electrical Engineering: Core qualification: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Mechatronics: Core qualification: Compulsory
Course L0675: Electrical Engineering I: Direct Current Networks and Electromagnetic Fields
Typ Lecture
Hrs/wk 3
CP 5
Workload in Hours Independent Study Time 108, Study Time in Lecture 42
Lecturer Prof. Manfred Kasper
Language DE
Cycle WiSe
Content
Literature
  1. M. Kasper, Skript zur Vorlesung Elektrotechnik 1, 2013
  2. M. Albach: Grundlagen der Elektrotechnik 1, Pearson Education, 2004
  3. F. Moeller, H. Frohne, K.H. Löcherer, H. Müller: Grundlagen der Elektrotechnik, Teubner, 2005
  4. A. R. Hambley: Electrical Engineering, Principles and Applications, Pearson Education, 2008
Course L0676: Electrical Engineering I: Direct Current Networks and Electromagnetic Fields
Typ Recitation Section (small)
Hrs/wk 2
CP 1
Workload in Hours Independent Study Time 2, Study Time in Lecture 28
Lecturer Prof. Manfred Kasper
Language DE
Cycle WiSe
Content
Literature
  1. Übungsaufgaben zur Elektrotechnik 1, TUHH, 2013
  2. Ch. Kautz: Tutorien zur Elektrotechnik, Pearson Studium, 2010

Module M0850: Mathematics I

Courses
Title Typ Hrs/wk CP
Analysis I (L1010) Lecture 2 2
Analysis I (L1012) Recitation Section (small) 1 1
Analysis I (L1013) Recitation Section (large) 1 1
Linear Algebra I (L0912) Lecture 2 2
Linear Algebra I (L0913) Recitation Section (small) 1 1
Linear Algebra I (L0914) Recitation Section (large) 1 1
Module Responsible Prof. Anusch Taraz
Admission Requirements none
Recommended Previous Knowledge

School mathematics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can name the basic concepts in analysis and linear algebra. 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 analysis and linear 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 128, Study Time in Lecture 112
Credit points 8
Examination Written exam
Examination duration and scale 60 min (Analysis I) + 60 min (Linear Algebra I)
Assignment for the Following Curricula General Engineering Science (German program): Core qualification: Compulsory
Civil- and Environmental Engeneering: Core qualification: Compulsory
Bioprocess Engineering: Core qualification: Compulsory
Electrical Engineering: Core qualification: Compulsory
Energy and Environmental 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
Process Engineering: Core qualification: Compulsory
Course L1010: Analysis I
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE
Cycle WiSe
Content

Foundations of differential and integrational calculus of one variable

  • statements, sets and functions
  • natural and real numbers
  • convergence of sequences and series
  • continuous and differentiable functions
  • mean value theorems
  • Taylor series
  • calculus
  • error analysis
  • fixpoint iteration
Literature
  • R. Ansorge, H. J. Oberle: Mathematik für Ingenieure, Band 1. Verlag Wiley-VCH, Berlin, Weinheim, New York, 2000
  • H.J. Oberle, K. Rothe, Th. Sonar: Mathematik für Ingenieure, Band 3: Aufgaben und Lösungen. Verlag Wiley-VCH, Berlin, Weinheim, New York, 2000.


Course L1012: Analysis I
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 WiSe
Content See interlocking course
Literature See interlocking course
Course L1013: Analysis I
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 WiSe
Content See interlocking course
Literature See interlocking course
Course L0912: Linear Algebra I
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Anusch Taraz
Language DE
Cycle WiSe
Content
  • vectors: intuition, rules, inner and cross product, lines and planes
  • general vector spaces: subspaces, isomorphic spaces, Euclidean vector spaces
  • systems of linear equations: Gauß-elimination, matrix product, inverse matrices, transformations, LR-decomposition, block matrices, determinants 
Literature
  • W. Mackens, H. Voß: Mathematik I für Studierende der Ingenieurwissenschaften, HECO-Verlag, Alsdorf 1994
  • W. Mackens, H. Voß: Aufgaben und Lösungen zur Mathematik I für Studierende der Ingenieurwissenschaften, HECO-Verlag, Alsdorf 1994
Course L0913: Linear Algebra I
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Anusch Taraz
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0914: Linear Algebra I
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Anusch Taraz
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0547: Electrical Engineering II: Alternating Current Networks and Basic Devices

Courses
Title Typ Hrs/wk CP
Electrical Engineering II: Alternating Current Networks and Basic Devices (L0178) Lecture 3 5
Electrical Engineering II: Alternating Current Networks and Basic Devices (L0179) Recitation Section (small) 2 1
Module Responsible Prof. Christian Schuster
Admission Requirements

Elektrotechnik I, Mathematik I


Recommended Previous Knowledge

Direct current networks, complex numbers


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

Students are able to reproduce and explain fundamental theories, principles, and methods related to the theory of alternating currents. They can describe networks of linear elements using a complex notation for voltages and currents. They can reproduce an overview of applications for the theory of alternating currents in the area of electrical engineering. Students are capable of explaining the behavior of fundamental passive and active devices as well as their impact on simple circuits.


Skills

Students are capable of calculating parameters within simple electrical networks at alternating currents by means of a complex notation for voltages and currents. They can appraise the fundamental effects that may occur within electrical networks at alternating currents. Students are able to analyze simple circuits such as oscillating circuits, filter, and matching networks quantitatively and dimension elements by means of a design. They can motivate and justify the fundamental elements of an electrical power supply (transformer, transmission line, compensation of reactive power, multiphase system) and are qualified to dimension their main features.


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 a week of project work).


Autonomy

Students are capable to gather necessary information from the references provided and relate that information to the context of the lecture. They are able to continually reflect their knowledge by means of activities that accompany the lecture, such as online-tests 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
Examination Written exam
Examination duration and scale 90 - 150 minutes
Assignment for the Following Curricula General Engineering Science (German program): Core qualification: Compulsory
Electrical Engineering: Core qualification: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Mechatronics: Core qualification: Compulsory
Course L0178: Electrical Engineering II: Alternating Current Networks and Basic Devices
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

- General time-dependency of electrical networks

- Representation and properties of harmonic signals

- RLC-elements at alternating currents/voltages

- Complex notation for the representation of RLC-elements

- Power in electrical networks at alternating currents, compensation of reactive power

- Frequency response locus (Nyquist plot) and Bode-diagrams

- Measurement instrumentation for assessing alternating currents

- Oscillating circuits, filters, electrical transmission lines

- Transformers, three-phase current, energy converters

- Simple non-linear and active electrical devices


Literature

- M. Albach, "Elektrotechnik", Pearson Studium (2011)

- T. Harriehausen, D. Schwarzenau, "Moeller Grundlagen der Elektrotechnik", Springer (2013)  

- R. Kories, H. Schmidt-Walter, "Taschenbuch der Elektrotechnik", Harri Deutsch (2010)

- C. Kautz, "Tutorien zur Elektrotechnik", Pearson (2009)

- A. Hambley, "Electrical Engineering: Principles and Applications", Pearson (2013)

- R. Dorf, "The Electrical Engineering Handbook", CRC (2006)


Course L0179: Electrical Engineering II: Alternating Current Networks and Basic Devices
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

- General time-dependency of electrical networks

- Representation and properties of harmonic signals

- RLC-elements at alternating currents/voltages

- Complex notation for the representation of RLC-elements

- Power in electrical networks at alternating currents, compensation of reactive power

- Frequency response locus (Nyquist plot) and Bode-diagrams

- Measurement instrumentation for assessing alternating currents

- Oscillating circuits, filters, electrical transmission lines

- Transformers, three-phase current, energy converters

- Simple non-linear and active electrical devices


Literature

- M. Albach, "Elektrotechnik", Pearson Studium (2011)

- T. Harriehausen, D. Schwarzenau, "Moeller Grundlagen der Elektrotechnik", Springer (2013)  

- R. Kories, H. Schmidt-Walter, "Taschenbuch der Elektrotechnik", Harri Deutsch (2010)

- C. Kautz, "Tutorien zur Elektrotechnik", Pearson (2009)

- A. Hambley, "Electrical Engineering: Principles and Applications", Pearson (2013)

- R. Dorf, "The Electrical Engineering Handbook", CRC (2006)


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 Lecture Prozedurale Programmierung or equivalent proficiency in imperative programming
Recommended Previous Knowledge

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
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 and Engineering: Compulsory
Computer Science: Core qualification: Compulsory
Electrical Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Computer Science and Engineering: 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 M0624: Logic, Automata and Formal Languages

Courses
Title Typ Hrs/wk CP
Logic, Automata Theory and Formal Languages (L0332) Lecture 2 4
Logic, Automata Theory and Formal Languages (L0507) Recitation Section (small) 2 2
Module Responsible Prof. Tobias Knopp
Admission Requirements
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
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Computer Science and Engineering: Compulsory
Computer Science: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Computer Science and Engineering: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Technomathematics: Specialisation Informatics: Elective Compulsory
Course L0332: Logic, 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: Logic, 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 M0829: Foundations of Management

Courses
Title Typ Hrs/wk CP
Introduction to Management (L0880) Lecture 4 4
Project Entrepreneurship (L0882) Problem-based Learning 2 2
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 96, Study Time in Lecture 84
Credit points 6
Examination Written exam
Examination duration and scale 90 Minuten
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Electrical Engineering: Compulsory
General Engineering Science (German program): Specialisation Computer Science and Engineering: Compulsory
General Engineering Science (German program): Specialisation Chemical 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
Civil- and Environmental Engeneering: 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 and 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): Specialisation Chemical Engineering: 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 L0880: Introduction to Management
Typ Lecture
Hrs/wk 4
CP 4
Workload in Hours Independent Study Time 64, Study Time in Lecture 56
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. 


Course L0882: Project Entrepreneurship
Typ Problem-based Learning
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Christoph Ihl
Language DE
Cycle WiSe/SoSe
Content

In this project module, students work on an Entrepreneurship project. They are required to go through all relevant steps, from the first idea to the concept, using their knowledge from the corresponding lecture.

Project work is carried out in teams with the support of a mentor.

Literature Relevante Literatur aus der korrespondierenden Vorlesung.

Module M0851: Mathematics II

Courses
Title Typ Hrs/wk CP
Analysis II (L1025) Lecture 2 2
Analysis II (L1026) Recitation Section (large) 1 1
Analysis II (L1027) Recitation Section (small) 1 1
Linear Algebra II (L0915) Lecture 2 2
Linear Algebra II (L0916) Recitation Section (small) 1 1
Linear Algebra II (L0917) Recitation Section (large) 1 1
Module Responsible Prof. Anusch Taraz
Admission Requirements none
Recommended Previous Knowledge Mathematics I
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can name further concepts in analysis and linear algebra. 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 analysis and linear 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 128, Study Time in Lecture 112
Credit points 8
Examination Written exam
Examination duration and scale 60 min (Analysis II) + 60 min (Linear Algebra II)
Assignment for the Following Curricula General Engineering Science (German program): Core qualification: Compulsory
Civil- and Environmental Engeneering: Core qualification: Compulsory
Bioprocess Engineering: Core qualification: Compulsory
Electrical Engineering: Core qualification: Compulsory
Energy and Environmental 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
Process Engineering: Core qualification: Compulsory
Course L1025: Analysis II
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE
Cycle SoSe
Content
  • power series and elementary functions
  • interpolation
  • integration (proper integrals, fundamental theorem, integration rules, improper integrals, parameter dependent integrals
  • applications of integration (volume and surface of bodies of revolution, lines and arc length, line integrals
  • numerical quadrature
  • periodic functions

Literature
  • R. Ansorge, H. J. Oberle: Mathematik für Ingenieure, Band 1; Verlag Wiley-VCH, Berlin, Weinheim, New York, 2000
  • H.J. Oberle, K. Rothe, Th. Sonar: Mathematik für Ingenieure, Band 3: Aufgaben und Lösungen; Verlag Wiley-VCH, Berlin, Weinheim, New York, 2000.

Course L1026: Analysis II
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 L1027: Analysis II
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
Course L0915: Linear Algebra II
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Anusch Taraz
Language DE
Cycle SoSe
Content
  • linear mappings: basis transformation, orthogonal projection, orthogonal matrices, householder matrices
  • linear regression: QR-decomposition, normal equations, linear discrete approximation
  • eigenvalues: diagonalising matrices, normal matrices, symmetric and Hermite matrices, Jordan normal form, singular value decomposition
  • system of linear differential equations 
Literature
  • W. Mackens, H. Voß: Mathematik I für Studierende der Ingenieurwissenschaften, HECO-Verlag, Alsdorf 1994
  • W. Mackens, H. Voß: Aufgaben und Lösungen zur Mathematik I für Studierende der Ingenieurwissenschaften, HECO-Verlag, Alsdorf 1994
Course L0916: Linear Algebra II
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Anusch Taraz
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course
Course L0917: Linear Algebra II
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Anusch Taraz
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0569: Engineering Mechanics I

Courses
Title Typ Hrs/wk CP
Engineering Mechanics I (L0187) Lecture 3 3
Engineering Mechanics I (L0190) Recitation Section (small) 2 3
Module Responsible Prof. Uwe Weltin
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 Students are able to describe fundamental connections, theories and methods to calculate forces in statically determined mounted systems of rigid bodies and fundamentals in elastostatics.
Skills Students are able to apply theories and methods to calculate forces in statically determined mounted systems of rigid bodies and fundamentals of elastostatics.
Personal Competence
Social Competence

Students are able to work goal-oriented in small mixed groups, learning and broadening teamwork abilities.

Autonomy

Students are able to solve individually exercises related to this lecture.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Written exam
Examination duration and scale 90 min.
Assignment for the Following Curricula Bioprocess Engineering: Core qualification: Compulsory
Electrical Engineering: Core qualification: Elective Compulsory
Energy and Environmental Engineering: Core qualification: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Logistics and Mobility: Core qualification: Compulsory
Process Engineering: Core qualification: Compulsory
Course L0187: Engineering Mechanics I
Typ Lecture
Hrs/wk 3
CP 3
Workload in Hours Independent Study Time 48, Study Time in Lecture 42
Lecturer Prof. Uwe Weltin
Language DE
Cycle WiSe
Content

Methods to calculate forces in statically determined systems of rigid bodies

  • Newton-Euler-Method
  • Energy-Methods

Fundamentals of elasticity

  • Forces and deformations in elastic systems
Literature
  • Gross, D.; Hauger, W.; Schröder, J.; Wall, W.A.: Technische Mechanik 1: Statik, Springer  Vieweg, 2013
  • Gross, D.; Hauger, W.; Schröder, J.; Wall, W.A.: Technische Mechanik 2: Elastostatik, Springer Verlag, 2011
  • Gross, D; Ehlers, W.; Wriggers, P.; Schröder, J.; Müller, R.: Formeln und Aufgaben zur Technischen Mechanik 1: Statik, Springer Vieweg, 2013 
  • Gross, D; Ehlers, W.; Wriggers, P.; Schröder, J.; Müller, R.: Formeln und Aufgaben zur Technischen Mechanik 2: Elastostatik, Springer Verlag, 2011 
  • Hibbeler, Russel C.: Technische Mechanik 1 Statik, Pearson Studium, 2012
  • Hibbeler, Russel C.: Technische Mechanik 2 Festigkeitslehre, Pearson Studium, 2013 
  • Hauger, W.; Mannl, V.; Wall, W.A.; Werner, E.: Aufgaben zu Technische Mechanik 1-3: Statik, Elastostatik, Kinetik, Springer Verlag, 2011 
Course L0190: Engineering Mechanics I
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Uwe Weltin
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0662: Numerical Mathematics I

Courses
Title Typ Hrs/wk CP
Numerical Mathematics I (L0417) Lecture 2 3
Numerical Mathematics I (L0418) Recitation Section (small) 2 3
Module Responsible Prof. Sabine Le Borne
Admission Requirements None
Recommended Previous Knowledge
  • Lecture material of prerequisite lectures
  • basic MATLAB knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  • name numerical methods for interpolation, integration, least squares problems, eigenvalue problems, nonlinear root finding problems and to explain their core ideas,
  • repeat convergence statements for the numerical methods,
  • explain aspects for the practical execution of numerical methods with respect to computational and storage complexitx.


Skills

Students are able to

  • implement, apply and compare numerical methods using MATLAB,
  • justify the convergence behaviour of numerical methods with respect to the problem and solution algorithm,
  • select and execute a suitable solution approach for a given problem.
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
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Computer Science and Engineering: Compulsory
General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory
General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory
Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory
Computer Science: Specialisation Computational Mathematics: Elective Compulsory
Electrical Engineering: Core qualification: Elective Compulsory
General Engineering Science (English program): Specialisation Computer Science and 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): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Process Engineering: Specialisation Process Engineering : Elective Compulsory
Course L0417: Numerical Mathematics I
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
Cycle WiSe
Content
  1. Error analysis: Number representation, error types, conditioning and stability
  2. Interpolation: polynomial and spline interpolation
  3. Numerical integration and differentiation: order, Newton-Cotes formula, error estimates, Gaussian quadrature, adaptive quadrature, difference formulas
  4. Linear systems: LU and Cholesky factorization, matrix norms, conditioning
  5. Linear least squares problems: normal equations, Gram.Schmidt and Householder orthogonalization, singular value decomposition, regularization
  6. Eigenvalue problems: power iteration, inverse iteration, QR algorithm
  7. Nonlinear systems of equations: Fixed point iteration, root-finding algorithms for real-valued functions, Newton and Quasi-Newton methods for systems
Literature
  • Stoer/Bulirsch: Numerische Mathematik 1, Springer
  • Dahmen, Reusken: Numerik für Ingenieure und Naturwissenschaftler, Springer


Course L0418: Numerical Mathematics I
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
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
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
Examination Written exam
Examination duration and scale
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Computer Science and Engineering: Compulsory
Computer Science: Core qualification: Compulsory
Electrical Engineering: Core qualification: Elective Compulsory
General Engineering Science (English program): Specialisation Computer Science and Engineering: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Technomathematics: Specialisation 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 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


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
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
Computer Science: Core qualification: Compulsory
Electrical Engineering: Core qualification: Compulsory
General Engineering Science (English program): Core qualification: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Mechatronics: Core qualification: Compulsory
Technomathematics: Specialisation 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

1. Introduction

  • Principles of digital design
  • Analog versus Digital
  • Gates and flip-flops
  • Aspects of digital design
  • Integrated cicuits
  • Digital devices
  • Time-to-market


2. Number Systems and Codes

  • General positional number systems
  • Representation of numbers
  • Binary arithmetic
  • Number and character codes
  • Codes for detecting and correcting errors
  • Codes for serial data transmission
  • Binary prefixes


3. Digital Circuits

  • Logic signals and gates
  • Logic families
  • CMOS logic
  • CMOS circuits: electrical behavior
  • CMOS input and output structures
  • Bipolar logic
  • CMOS logic families
  • CMOS/TLL interfacing


4. Combinational Logic Design (Principles)

  • Switching algebra
  • Combinational-circuit analysis
  • Combinational-circuit synthesis
  • Minimization
  • Timing hazards


5. Combinational Logic Design (Practices)

  • Documentation standards
  • Timing of digital circuits
  • Decoders and encoders
  • Three-state devices
  • Multiplexers and demultiplexers
  • Exclusive-OR gates and parity circuits
  • Comparators
  • Adders and subtractors
  • Combinational multiplier
  • Barrel shifter
  • Arithmetic and logic unit (ALU)


6. Sequential Logic Design (Principles)

  • State concept and clock signal
  • Bistable elements
  • Asynchronous latches
  • Synchronous latches
  • Synchronous flip-flops
  • Overview: latches and flip-flops
  • Clocked synchronous state-machine analysis
  • Clocked synchronous state-machine design
  • Designing state machines using state diagrams
  • Sequential-circuit design with VHDL
  • Decomposing state machines


7. Sequential Logic Design (Practices)

  • Sequential-circuit documentation standards
  • Latches and flip-flops
  • Counters
  • Shift registers
  • Iterative versus sequential circuits
  • Synchronous design methodology
  • Impediments to synchronous design


8. Memory, PLDs, CPLDs und FPGAs

  • ROM, SRAM, DRAM, SDRAM
  • Programmable logic devices (PLDs)
  • Complex programmable logic devices (CPLDs)
  • Field-programmable gate arrays (FPGAs)


9. Microprocessor Technology (Principles)

  • Computer history
  • Von Neumann architecture
  • Components of a microprocessor system
Literature
  • S. Voigt, Skript zur Vorlesung „Technische Informatik"
  • J. Wakerly, Digital Design: Principles and Practices, 4. Auflage, 2010, Pearson Prentice Hall, ISBN: 978-0-13-613987-4
  • D. Hoffmann, Grundlagen der Technischen Informatik, 2. Auflage, 2010, Carl Hanser Verlag, ISBN: 978-3-446-42150-9
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

1. Introduction

  • Principles of digital design
  • Analog versus Digital
  • Gates and flip-flops
  • Aspects of digital design
  • Integrated cicuits
  • Digital devices
  • Time-to-market


2. Number Systems and Codes

  • General positional number systems
  • Representation of numbers
  • Binary arithmetic
  • Number and character codes
  • Codes for detecting and correcting errors
  • Codes for serial data transmission
  • Binary prefixes


3. Digital Circuits

  • Logic signals and gates
  • Logic families
  • CMOS logic
  • CMOS circuits: electrical behavior
  • CMOS input and output structures
  • Bipolar logic
  • CMOS logic families
  • CMOS/TLL interfacing


4. Combinational Logic Design (Principles)

  • Switching algebra
  • Combinational-circuit analysis
  • Combinational-circuit synthesis
  • Minimization
  • Timing hazards


5. Combinational Logic Design (Practices)

  • Documentation standards
  • Timing of digital circuits
  • Decoders and encoders
  • Three-state devices
  • Multiplexers and demultiplexers
  • Exclusive-OR gates and parity circuits
  • Comparators
  • Adders and subtractors
  • Combinational multiplier
  • Barrel shifter
  • Arithmetic and logic unit (ALU)


6. Sequential Logic Design (Principles)

  • State concept and clock signal
  • Bistable elements
  • Asynchronous latches
  • Synchronous latches
  • Synchronous flip-flops
  • Overview: latches and flip-flops
  • Clocked synchronous state-machine analysis
  • Clocked synchronous state-machine design
  • Designing state machines using state diagrams
  • Sequential-circuit design with VHDL
  • Decomposing state machines


7. Sequential Logic Design (Practices)

  • Sequential-circuit documentation standards
  • Latches and flip-flops
  • Counters
  • Shift registers
  • Iterative versus sequential circuits
  • Synchronous design methodology
  • Impediments to synchronous design


8. Memory, PLDs, CPLDs und FPGAs

  • ROM, SRAM, DRAM, SDRAM
  • Programmable logic devices (PLDs)
  • Complex programmable logic devices (CPLDs)
  • Field-programmable gate arrays (FPGAs)


9. Microprocessor Technology (Principles)

  • Computer history
  • Von Neumann architecture
  • Components of a microprocessor system
Literature
  • S. Voigt, Skript zur Vorlesung „Technische Informatik"
  • J. Wakerly, Digital Design: Principles and Practices, 4. Auflage, 2010, Pearson Prentice Hall, ISBN: 978-0-13-613987-4
  • D. Hoffmann, Grundlagen der Technischen Informatik, 2. Auflage, 2010, Carl Hanser Verlag, ISBN: 978-3-446-42150-9

Module M0853: Mathematics III

Courses
Title Typ Hrs/wk CP
Analysis III (L1028) Lecture 2 2
Analysis III (L1029) Recitation Section (small) 1 1
Analysis III (L1030) Recitation Section (large) 1 1
Differential Equations 1 (Ordinary Differential Equations) (L1031) Lecture 2 2
Differential Equations 1 (Ordinary Differential Equations) (L1032) Recitation Section (small) 1 1
Differential Equations 1 (Ordinary Differential Equations) (L1033) Recitation Section (large) 1 1
Module Responsible Prof. Anusch Taraz
Admission Requirements none
Recommended Previous Knowledge Mathematics I + II
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can name the basic concepts in the area of analysis and differential equations. 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 the area of analysis and differential equations 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 128, Study Time in Lecture 112
Credit points 8
Examination Written exam
Examination duration and scale 60 min (Analysis III) + 60 min (Differential Equations 1)
Assignment for the Following Curricula General Engineering Science (German program): Core qualification: 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): Core qualification: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Mechanical Engineering: Core qualification: Compulsory
Mechatronics: Core qualification: Compulsory
Naval Architecture: Core qualification: Compulsory
Process Engineering: Core qualification: Compulsory
Course L1028: Analysis III
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE
Cycle WiSe
Content

Main features of differential and integrational calculus of several variables 

  • Differential calculus for several variables
  • Mean value theorems and Taylor's theorem
  • Maximum and minimum values
  • Implicit functions
  • Minimization under equality constraints
  • Newton's method for multiple variables
  • Double integrals over general regions
  • Line and surface integrals
  • Theorems of Gauß and Stokes
Literature
  • R. Ansorge, H. J. Oberle: Mathematik für Ingenieure, Band 2; Verlag Wiley-VCH, Berlin, Weinheim, New York, 2000
  • H.J. Oberle, K. Rothe, Th. Sonar: Mathematik für Ingenieure, Band 3: Aufgaben und Lösungen; Verlag Wiley-VCH, Berlin, Weinheim, New York, 2000.

Course L1029: Analysis III
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 WiSe
Content See interlocking course
Literature See interlocking course
Course L1030: Analysis III
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 WiSe
Content See interlocking course
Literature See interlocking course
Course L1031: Differential Equations 1 (Ordinary Differential Equations)
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Dozenten des Fachbereiches Mathematik der UHH
Language DE
Cycle WiSe
Content

Main features of the theory and numerical treatment of ordinary differential equations 

  • Introduction and elementary methods
  • Exsitence and uniqueness of initial value problems
  • Linear differential equations
  • Stability and qualitative behaviour of the solution
  • Boundary value problems and basic concepts of calculus of variations
  • Eigenvalue problems
  • Numerical methods for the integration of initial and boundary value problems
  • Classification of partial differential equations

Literature
  • R. Ansorge, H. J. Oberle: Mathematik für Ingenieure, Band 2; Verlag Wiley-VCH, Berlin, Weinheim, New York, 2000
  • H.J. Oberle, K. Rothe, Th. Sonar: Mathematik für Ingenieure, Band 3: Aufgaben und Lösungen; Verlag Wiley-VCH, Berlin, Weinheim, New York, 2000.

Course L1032: Differential Equations 1 (Ordinary Differential Equations)
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 WiSe
Content See interlocking course
Literature See interlocking course
Course L1033: Differential Equations 1 (Ordinary Differential Equations)
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 WiSe
Content See interlocking course
Literature See interlocking course

Module M0570: Engineering Mechanics II

Courses
Title Typ Hrs/wk CP
Engineering Mechanics II (L0191) Lecture 3 3
Engineering Mechanics II (L0192) Recitation Section (small) 2 3
Module Responsible Prof. Uwe Weltin
Admission Requirements none
Recommended Previous Knowledge Technical Mechnics I
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge Students are able to describe connections, theories and methods to calculate forces and motions of rigid bodies in 3D.
Skills Students are able to apply theories and method to calculate forces and motions of rigid bodies in 3D.
Personal Competence
Social Competence

Students are able to work goal-oriented in small mixed groups, learning and broadening teamwork abilities.

Autonomy

Students are able to solve individually exercises related to this lecture with instructional direction.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Written exam
Examination duration and scale 90 min.
Assignment for the Following Curricula Bioprocess Engineering: Core qualification: Compulsory
Electrical Engineering: Core qualification: Elective Compulsory
Energy and Environmental Engineering: Core qualification: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Logistics and Mobility: Core qualification: Compulsory
Process Engineering: Core qualification: Compulsory
Course L0191: Engineering Mechanics II
Typ Lecture
Hrs/wk 3
CP 3
Workload in Hours Independent Study Time 48, Study Time in Lecture 42
Lecturer Prof. Uwe Weltin
Language DE
Cycle SoSe
Content

Method for calculation of forces and motion of rigid bodies in 3D

  • Newton-Euler-Method
  • Energy methods
Literature
  • Gross, D.; Hauger, W.; Schröder, J.; Wall, W.A.: Technische Mechanik 2: Elastostatik, Springer Verlag, 2011
  • Gross, D.; Hauger, W.; Schröder, J.; Wall, W.A.: Technische Mechanik 3: Kinetik, Springer Vieweg, 2012 
  • Gross, D; Ehlers, W.; Wriggers, P.; Schröder, J.; Müller, R.: Formeln und Aufgaben zur Technischen Mechanik 2: Elastostatik, Springer Verlag, 2011 
  • Gross, D; Ehlers, W.; Wriggers, P.; Schröder, J.; Müller, R.: Formeln und Aufgaben zur Technischen Mechanik 3: Kinetik, Springer Vieweg, 2012
  • Hibbeler, Russel C.: Technische Mechanik 2 Festigkeitslehre, Pearson Studium, 2013
  • Hibbeler, Russel C.: Technische Mechanik 3 Dynamik, Pearson Studium, 2012 
  • Hauger, W.; Mannl, V.; Wall, W.A.; Werner, E.: Aufgaben zu Technische Mechanik 1-3: Statik, Elastostatik, Kinetik, Springer Verlag, 2011 
Course L0192: Engineering Mechanics II
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Uwe Weltin
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0672: Signals and Systems

Courses
Title Typ Hrs/wk CP
Signals and Systems (L0432) Lecture 3 4
Signals and Systems (L0433) Recitation Section (large) 1 2
Module Responsible Prof. Gerhard Bauch
Admission Requirements None
Recommended Previous Knowledge

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 124, Study Time in Lecture 56
Credit points 6
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 and Engineering: Compulsory
General Engineering Science (German program): Specialisation Chemical 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
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 and 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 Chemical Engineering: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Mechatronics: Core qualification: Compulsory
Technomathematics: Specialisation 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 (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 SoSe
Content See interlocking course
Literature See interlocking course

Module M0803: Embedded Systems

Courses
Title Typ Hrs/wk CP
Embedded Systems (L0805) Lecture 3 4
Embedded Systems (L0806) Recitation Section (small) 1 2
Module Responsible Prof. Heiko Falk
Admission Requirements None
Recommended Previous Knowledge Computer Engineering
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Embedded systems can be defined as information processing systems embedded into enclosing products. This course teaches the foundations of such systems. In particular, it deals with an introduction into these systems (notions, common characteristics) and their specification languages (models of computation, hierarchical automata, specification of distributed systems, task graphs, specification of real-time applications, translations between different models).

Another part covers the hardware of embedded systems: Sonsors, A/D and D/A converters, real-time capable communication hardware, embedded processors, memories, energy dissipation, reconfigurable logic and actuators. The course also features an introduction into real-time operating systems, middleware and real-time scheduling. Finally, the implementation of embedded systems using hardware/software co-design (hardware/software partitioning, high-level transformations of specifications, energy-efficient realizations, compilers for embedded processors) is covered.

Skills After having attended the course, students shall be able to realize simple embedded systems. The students shall realize which relevant parts of technological competences to use in order to obtain a functional embedded systems. In particular, they shall be able to compare different models of computations and feasible techniques for system-level design. They shall be able to judge in which areas of embedded system design specific risks exist.
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
Examination Written exam
Examination duration and scale 90 minutes, contents of course and labs
Assignment for the Following Curricula Computer Science: Specialisation Computer Engineering: Elective Compulsory
Electrical Engineering: Core qualification: Elective Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Course L0805: Embedded Systems
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/EN
Cycle SoSe
Content
Literature
  • Peter Marwedel. Embedded System Design - Embedded Systems Foundations of Cyber-Physical Systems. 2nd Edition, Springer, 2012.
Course L0806: Embedded Systems
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/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
Examination Written exam
Examination duration and scale 120 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Computer Science and Engineering: Compulsory
Computer Science: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Computer Science and Engineering: Compulsory
Computational Science and Engineering: Core qualification: Compulsory
Logistics and Mobility: Specialisation Engineering Science: Elective Compulsory
Technomathematics: Specialisation 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 M0793: Seminars Computer Science and Mathematics

Courses
Title Typ Hrs/wk CP
Seminar Computational Mathematics/Computer Science (L0797) Seminar 2 2
Seminar Computational Engineering Science (L0796) Seminar 2 2
Seminar Engineering Mathematics/Computer Science (L1781) Seminar 2 2
Module Responsible Prof. Karl-Heinz Zimmermann
Admission Requirements None
Recommended Previous Knowledge Basic knowledge in Computer Science, Mathematics, and eventually Engineering Science.
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students know who to acquire basic knowledge in a rudimentary field of Computer Science, Mathematics, or Engineering Science.
Skills The students are able to elaborate self-reliantly a rudimentary subfield of Computer Science, Mathematics, or Engineering Science.
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Credit points 6
Examination Presentation
Examination duration and scale Pro Seminar erfolgt der Scheinerwerb durch Präsentation (Seminarvortrag 25 min und Diskussion 5 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
Course L0797: Seminar Computational Mathematics/Computer Science
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Karl-Heinz Zimmermann, Dr. Jens-Peter Zemke
Language DE/EN
Cycle WiSe/SoSe
Content
  • Seminar presentations by enrolled students. Seminar topics from the field of computer-oriented mathematics or computer science are proposed by the organizer
  • Active participation in discussions.
Literature Wird vom Seminarveranstalter bekanntgegeben.
Course L0796: Seminar Computational Engineering Science
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Karl-Heinz Zimmermann
Language DE/EN
Cycle WiSe/SoSe
Content
  • Seminar presentations by enrolled students. Seminar topics from the field of computer science or engineering science are proposed by the organizer
  • Active participation in discussions.

Literature

Wird vom Seminarveranstalter bekanntgegeben.


Course L1781: Seminar Engineering Mathematics/Computer Science
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Karl-Heinz Zimmermann, Dr. Jens-Peter Zemke
Language DE/EN
Cycle WiSe/SoSe
Content
  • Seminar presentations by enrolled students. Seminar topics from the field of computer science or engineering mathematics are proposed by the organizer
  • Active participation in discussions.
Literature

Wird vom Seminarveranstalter bekanntgegeben.

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
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
Logistics and Mobility: Specialisation Engineering Science: Elective Compulsory
Mechanical Engineering: Core qualification: Compulsory
Mechatronics: Core qualification: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective 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 M0727: Stochastics

Courses
Title Typ Hrs/wk CP
Stochastics (L0777) Lecture 2 4
Stochastics (L0778) Recitation Section (small) 2 2
Module Responsible Prof. Marko Lindner
Admission Requirements none
Recommended Previous Knowledge
  • Calculus
  • Discrete algebraic structures (combinatorics)
  • Propositional logic
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge Students can explain the main definitions of probability, and they can give basic definitions of modeling elements (random variables, events, dependence, independence assumptions) used in discrete and continuous settings (joint and marginal distributions, density functions). Students can describe characteristic notions such as expected values, variance, standard deviation, and moments. Students can define decision problems and explain algorithms for solving these problems (based on the chain rule or Bayesian networks). Algorithms, or estimators as they are caller, can be analyzed in terms of notions such as bias of an estimator, etc. Student can describe the main ideas of stochastic processes and explain algorithms for solving decision and computation problem for stochastic processes. Students can also explain basic statistical detection and estimation techniques.
Skills

Students can apply algorithms for solving decision problems, and they can justify whether approximation techniques are good enough in various application contexts, i.e., students can derive estimators and judge whether they are applicable or reliable.

Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
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
Course L0777: Stochastics
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Dr. Francisco Javier Hoecker-Escuti
Language EN
Cycle SoSe
Content

Foundations of probability theory

  • Definitions of probability, conditional probability
  • Random variables, dependencies, independence assumptions, 
  • Marginal and joint probabilities
  • Distributions and density functions
  • Characteristics: expected values, variance, standard deviation, moments

Practical representations for joint probabilities

  • Bayessche Netzwerke
  • Semantik, Entscheidungsprobleme, exakte und approximative Algorithmen

Stochastic processes

  • Stationarity, ergodicity
  • Correlations
  • Dynamic Bayesian networks, Hidden Markov networks, Kalman filters, queues

Detection & estimation

  • Detectors
  • Estimation rules and procedures
  • Hypothesis and distribution tests
  • Stochastic regression
Literature
  1. Methoden der statistischen Inferenz, Likelihood und Bayes, Held, L., Spektrum 2008
  2. Stochastik für Informatiker, Dümbgen, L., Springer 2003
  3. Statistik: Der Weg zur Datenanalyse, Fahrmeir, L., Künstler R., Pigeot, I, Tutz, G., Springer 2010
  4. Stochastik, Georgii, H.-O., deGruyter, 2009
  5. Probability and Random Processes, Grimmett, G., Stirzaker, D., Oxford University Press, 2001
  6. Programmieren mit R, Ligges, U., Springer 2008
Course L0778: Stochastics
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Dr. Francisco Javier Hoecker-Escuti
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Specialization Computer Science

Module M0868: System on Chip Design (Lab)

Courses
Title Typ Hrs/wk CP
System on Chip Design (L0792) Problem-based Learning 3 6
Module Responsible NN
Admission Requirements None.
Recommended Previous Knowledge Computer Engineering
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students know the basics of VHDL, CPUs, and FPGAs as well as their the environment.
Skills

The students are able to design simple CPUs and are in the position to describe their embedding into a larger system.  

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 standard books and to associate this knowledge with other classes.

Workload in Hours Independent Study Time 138, Study Time in Lecture 42
Credit points 6
Examination Project
Examination duration and scale
Assignment for the Following Curricula Computer Science: Specialisation Computer Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Course L0792: System on Chip Design
Typ Problem-based Learning
Hrs/wk 3
CP 6
Workload in Hours Independent Study Time 138, Study Time in Lecture 42
Lecturer NN
Language DE/EN
Cycle SoSe
Content
Literature

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
  • 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
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Computer Science and Engineering: Compulsory
Computer Science: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Computer Science and Engineering: Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Technomathematics: Specialisation 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 M0791: Computer Architecture

Courses
Title Typ Hrs/wk CP
Computer Architecture (L0793) Lecture 2 4
Computer Architecture (L0794) Recitation Section (small) 2 2
Module Responsible Prof. Heiko Falk
Admission Requirements None
Recommended Previous Knowledge

Module "Computer 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 presents advanced concepts from the discipline of computer architecture. In the beginning, a broad overview over various programming models is given, both for general-purpose computers and for special-purpose machines (e.g., signal processors). Next, foundational aspects of the micro-architecture of processors are covered. Here, the focus particularly lies on the so-called pipelining and the methods used for the acceleration of instruction execution used in this context. The students get to know concepts for dynamic scheduling, branch prediction, superscalar execution of machine instructions and for memory hierarchies.

Skills

The students are able to describe the organization of processors. They know the different architectural principles and programming models. The students examine various structures of pipelined processor architectures and are able to explain their concepts and to analyze them w.r.t. criteria like, e.g., performance or energy efficiency. They evaluate different structures of memory hierarchies, know parallel computer architectures and are able to distinguish between instruction- and data-level parallelism.

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
Examination Written exam
Examination duration and scale 90 minutes, contents of course and 4 lab attestations
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: Specialisation Computer and Software Engineering: 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: Specialisation Computer Science: Elective Compulsory
Course L0793: Computer Architecture
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Heiko Falk
Language DE/EN
Cycle WiSe
Content
  • Introduction
  • VHDL Basics
  • Programming Models
  • Realization of Elementary Data Types
  • Dynamic Scheduling
  • Branch Prediction
  • Superscalar Machines
  • Memory Hierarchies
Literature
  • D. Patterson, J. Hennessy. Rechnerorganisation und -entwurf. Elsevier, 2005.
  • A. Tanenbaum, J. Goodman. Computerarchitektur. Pearson, 2001.
Course L0794: Computer Architecture
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Heiko Falk
Language DE/EN
Cycle WiSe
Content see interlocking course
Literature

siehe korrespondierende Lehrveranstaltung

see interlocking course

Module M0651: Computational Geometry

Courses
Title Typ Hrs/wk CP
Computational Geoemetry (L0393) Lecture 2 4
Computational Geoemetry (L0394) Recitation Section (small) 2 2
Module Responsible Dr. Prashant Batra
Admission Requirements None
Recommended Previous Knowledge

Linear algebra and  analytic geometry as taught in higher secondary school

(Computing   with vectors a. determinants, Interpretation of scalar product, cross-product,  Representation of  lines/planes, Satz d. Pythagoras' theorem, cosine theorem, Thales' theorem, projections/embeddings)

Basic data structures (trees, binary trees, search trees, balanced binary trees, linked lists)

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

Students can name the basic concepts of computer-assisted geometry, describe them with mathematical precision, and explain them by means of examples.

Students are conversant with the computational description of geometrical (combinational/topological) facts, including determinant formulas and complexity assessments and proofs for all algorithms, especially output-sensitive algorithms.

Students are able to discuss logical connections between these concepts and to explain them by means of examples.


Skills

Students can model tasks from computer-assisted geometry with the aid of the concepts about which they have learnt and can solve them by means of the methods they have learnt.


Personal Competence
Social Competence

Students are able to discuss with other attendees their own algorithmic suggestions for solving the problems presented. They are also able to work in teams and are conversant with mathematics as a common language.


Autonomy

Students are capable of accessing independently further logical connections between the concepts about which they have learnt and are able to verify them.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale
Assignment for the Following Curricula Computer Science: Specialisation Computational Mathematics: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Course L0393: Computational Geoemetry
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
Cycle WiSe
Content

Construction of the convex hull of  n points, triangulation of a simple polygon

 

Construction of Delaunay-triangulation and Voronoi-diagram

Algorithms and data structures  for the construction of  arrangements, and Ham-Sandwich-Cuts.

the intersection of half-planes, the optimization of a  linear functional over the latter.

Efficiente determination  of all  intersection  of (orthogonal) lines (line segments)

Approximative computation of the diameter of a point set

Randomised incremental algorithms

Basics of lattice point theory , LLL-algorithm and application in integer-valued optimization.

Basics of motion planning


Literature Computational Geometry Algorithms and Applications Authors:
  • Prof. Dr. Mark de Berg,
  • Dr. Otfried Cheong,
  • Dr. Marc van Kreveld,
  • Prof. Dr. Mark Overmars

Springer e-Book: http://dx.doi.org/10.1007/978-3-540-77974-2


Algorithmische Geometrie : Grundlagen, Methoden, Anwendungen / Rolf Klein
Verfasser: 
Klein, Rolf
Ausgabe: 
2., vollst. überarb. Aufl.
Erschienen: 
Berlin [u.a.] : Springer, 2005
Umfang: 
XI, 392 S. : graph. Darst.

Springer e-Book: http://dx.doi.org/10.1007/3-540-27619-X

O’Rourke, Joseph
Computational geometry in C. (English) Zbl 0816.68124
Cambridge: Univ. Press. ix, 346 p. $ 24.95; £16.95 /sc; $ 59.95; £35.00 /hc (1994).

ISBN:  0-521-44034-3  ; 0-521-44592-2


Computational geometry : an introduction / Franco P. Preparata; Michael Ian Shamos
Verfasser: 
Preparata, Franco P. ; Shamos, Michael Ian
Ausgabe: 
Corr. and expanded 2. printing.
Erschienen: 
New York [u.a.] : Springer, 1988
Umfang: 
XIV, 398 S. : graph. Darst.
Schriftenreihe: 
Texts and monographs in computer science
ISBN: 
3-540-96131-3
0-387-96131-3


Devadoss, Satyan L.; O’Rourke, Joseph
Discrete and computational geometry. (English) Zbl 1232.52001
Princeton, NJ: Princeton University Press (ISBN 978-0-691-14553-2/hbk; 978-1-400-83898-1/ebook). xi, 255 p.



ISBN: 978-3-540-77973-5 (Print) 978-3-540-77974-2 (Online)

Course L0394: Computational Geoemetry
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
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
Examination Written exam
Examination duration and scale
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: 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 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
Examination Written exam
Examination duration and scale 90 minutes
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
Literature
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 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
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 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 M0760: Electronic Devices

Courses
Title Typ Hrs/wk CP
Electronic Devices (L0720) Lecture 3 4
Electronic Devices (L0721) Problem-based Learning 2 2
Module Responsible Prof. Hoc Khiem Trieu
Admission Requirements None
Recommended Previous Knowledge

Atomic model and quantum theory, electrical currents in solid state materials, basics in solid-state physics

Successful participation of Physics for Engineers and Materials in Electrical Engineering or courses with equivalent contents

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


Students are able

  • to represent the basics of semiconductor physics,

  • to explain the operating principle of important semiconductor devices,

  • to outline device characteristics and equivalent circuits as well as to explain their derivation and

  • to discuss the limitation of device models.


Skills


Students are capable

  • to apply devices in basic circuits,

  • to realize the physical context and to solve complex problems by oneself


Personal Competence
Social Competence

Students are able to prepare and perform their lab experiments in team work as well as to present and discuss the results in front of audience.

Autonomy Students are capable to acquire knowledge based on literature in order to prepare their experiments.
Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Written exam
Examination duration and scale 120 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
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 Computer Science: Elective Compulsory
Course L0720: Electronic Devices
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Hoc Khiem Trieu
Language DE
Cycle WiSe
Content
  • Uniformly doped semiconductor (semiconductor, crystal structure, energy band diagram, effective mass, density of state, probability of occupancy, mass action law, generation and recombination processes, generation and recombination lifetime, carrier transport mechanisms: drift current, diffusion current; equilibriums in semiconductor, semiconductor equations)
  • pn-junction (zero applied bias, energy band diagram in thermal equilibrium, current-voltage characteristics, derivation of diode equation, consideration of space charge recombination, transient behaviour, breakdown mechanisms, various types of diodes: Zener diode, tunnel diode, backward diode, photo diode, LED, laser diode)
  • Bipolar transistor (principle of operation, current-voltage characteristics: calculation of  base, collector and emitter current, operating modes; non-ideality: actual doping profile, Early effect, breakdown, generation and recombination current and high injection; Ebers-Moll model: family of characteristics, equivalent circuit; frequency response, switching characteristics, heterojunction bipolar transistor)
  • Unipolar devices (surface effects: surface states, work function, energy band diagram; metal-semiconductor junctions: Schottky contact, current-voltage characteristics, ohmic  contact; junction field effect transistor: operating principle, current-voltage characteristics, small-signal model, breakdown characteristics; MESFET: operating principle,  depletion mode and enhancement mode MESFET; MIS structure: accumulation, depletion, inversion, strong inversion, flatband voltage, oxide charges, threshold voltage, capacitance voltage characteristics; MOSFET: basic structure, principle of operation, current voltage characteristics, frequency response, subthreshold behaviour, threshold voltage, device scaling; CMOS)

 

Literature

S.M. Sze: Semiconductor devices, Physics and Technology, John Wiley & Sons (1985)F. Thuselt: Physik der Halbleiterbauelemente, Springer (2011)

T. Thille, D. Schmitt-Landsiedel: Mikroelektronik, Halbleiterbauelemente und deren Anwendung in elektronischen Schaltungen, Springer (2004)

B.L. Anderson, R.L. Anderson: Fundamentals of Semiconductor Devices, McGraw-Hill (2005)

D.A. Neamen: Semiconductor Physics and Devices, McGraw-Hill (2011)

M. Shur: Introduction to Electronic Devices, John Wiley & Sons (1996)

S.M. Sze: Physics of semiconductor devices, John Wiley & Sons (2007)

H. Schaumburg: Halbleiter, B.G. Teubner (1991)

A. Möschwitzer: Grundlagen der Halbleiter-&Mikroelektronik, Bd1 Elektronische Halbleiterbauelemente, Carl Hanser (1992)

H.-G. Unger, W. Schultz, G. Weinhausen: Elektronische Bauelemente und Netzwerke I, Physikalische Grundlagen der Halbleiterbauelemente, Vieweg (1985)
Course L0721: Electronic Devices
Typ Problem-based Learning
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Hoc Khiem Trieu
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1254: Foundations of Computer Science

Courses
Title Typ Hrs/wk CP
Foundations of Computer Science (L1699) Lecture 2 3
Foundations of Computer Science (L1700) Recitation Section (small) 2 3
Module Responsible Prof. Bernd-Christian Renner
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 representation of numbers in computers, the concept of Boolean functions and combinatorial logic, the structure, organization, and behavior of the von Neumann computer, assembler and machine programming, and programming in a block structured language.
Skills Students are able to calculate with binary numbers, specify and analyze Boolean functions, design simple combinatorial networks, describe the workflow in a von Neumann computer, program in Assembler and in a block structured language, and be particularly able to think algorithmically.
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 this knowledge with other classes.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Course L1699: Foundations of Computer Science
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Bernd-Christian Renner
Language DE/EN
Cycle WiSe
Content
Literature
Course L1700: Foundations of Computer Science
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Bernd-Christian Renner
Language DE/EN
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) Problem-based Learning 1 1
Module Responsible Dr. Sandro Schulze
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
Examination Written exam
Examination duration and scale
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: 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 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 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
Examination Project
Examination duration and scale
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: 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 M0777: Semiconductor Circuit Design

Courses
Title Typ Hrs/wk CP
Semiconductor Circuit Design (L0763) Lecture 3 4
Semiconductor Circuit Design (L0864) Recitation Section (small) 1 2
Module Responsible Prof. Wolfgang Krautschneider
Admission Requirements none
Recommended Previous Knowledge

Fundamentals of electrical engineering

Basics of physics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students are able to explain the functionality of different MOS devices in electronic circuits.
  • Students know the fundamental digital logic circuits and can discuss their advantages and disadvantages.
  • Students have solid knowledge about memory circuits and can explain their functionality and specifications.
  • Students are able to explain how analog circuits functions and where they are applied.
  • Students know the appropriate fields for the use of bipolar transistors.


Skills
  • Students can calculate the specifications of different MOS devices and can define the parameters of electronic circuits.
  • Students are able to develop different logic circuits and can design different types of logic circuits.
  • Students can use MOS devices, operational amplifiers and bipolar transistors for specific applications.


Personal Competence
Social Competence
  • Students are able work efficiently in heterogeneous teams.
  • Students working together in small groups can solve problems and answer professional  questions.


Autonomy
  • Students are able to assess their level of knowledge.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 120 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 Electrical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: 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): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Mechanical Engineering: Specialisation Mechatronics: Compulsory
Mechatronics: Core qualification: Compulsory
Technomathematics: Core qualification: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0763: Semiconductor Circuit Design
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Wolfgang Krautschneider
Language DE
Cycle SoSe
Content
  • Basic circuits with MOS transistors for logic gates and amplifiers
  • Typical applications for analog and digital circuits
  • Realization of logical functions
  • Memory circuits
  • Scaling-down of CMOS circuits and further perfomance improvements
  • Operational amplifiers and their applications
  • Basic circuits with bipolar transistors
  • Design of exemplary circuits
  • Electrical behavoir of BiCMOS circuits
Literature

R. J. Baker, CMOS - Circuit Design, Layout and Simulation, J. Wiley & Sons Inc., 3. Auflage, 2011, ISBN: 047170055S

H.-G. Wagemann und T. Schönauer, Silizium-Planartechnologie, Grundprozesse, Physik und Bauelemente, Teubner-Verlag, 2003, ISBN 3519004674

K. Hoffmann, Systemintegration, Oldenbourg-Verlag, 2. Aufl. 2006, ISBN: 3486578944

U. Tietze und Ch. Schenk, E. Gamm, Halbleiterschaltungstechnik, Springer Verlag, 14. Auflage, 2012, ISBN 3540428496

H. Göbel, Einführung in die Halbleiter-Schaltungstechnik, Berlin, Heidelberg Springer-Verlag Berlin Heidelberg, 2011, ISBN: 9783642208874 ISBN: 9783642208867

URL: http://site.ebrary.com/lib/alltitles/docDetail.action?docID=10499499

URL: http://dx.doi.org/10.1007/978-3-642-20887-4

URL: http://ebooks.ciando.com/book/index.cfm/bok_id/319955

URL: http://www.ciando.com/img/bo


Course L0864: Semiconductor Circuit Design
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Wolfgang Krautschneider
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1269: Lab Cyber-Physical Systems

Courses
Title Typ Hrs/wk CP
Lab Cyber-Physical Systems (L1740) Problem-based Learning 4 6
Module Responsible Prof. Heiko Falk
Admission Requirements None
Recommended Previous Knowledge Module "Embedded Systems"
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Cyber-Physical Systems (CPS) are tightly integrated with their surrounding environment, via sensors, A/D and D/A converters, and actors. Due to their particular application areas, highly specialized sensors, processors and actors are common. Accordingly, there is a large variety of different specification approaches for CPS - in contrast to classical software engineering approaches.

Based on practical experiments using robot kits and computers, the basics of specification and modelling of CPS are taught. The lab introduces into the area (basic notions, characteristical properties) and their specification techniques (models of computation, hierarchical automata, data flow models, petri nets, imperative approaches). Since CPS frequently perform control tasks, the lab's experiments will base on simple control applications. The experiments will use state-of-the-art industrial specification tools (MATLAB/Simulink, LabVIEW, NXC) in order to model cyber-physical models that interact with the environment via sensors and actors.


Skills After successful attendance of the lab, students are able to develop simple CPS. They understand the interdependencies between a CPS and its surrounding processes which stem from the fact that a CPS interacts with the environment via sensors, A/D converters, digital processors, D/A converters and actors. The lab enables students to compare modelling approaches, to evaluate their advantages and limitations, and to decide which technique to use for a concrete task. They will be able to apply these techniques to practical problems. They obtain first experiences in hardware-related software development, in industry-relevant specification tools and in the area of simple control applications.
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
Examination Project
Examination duration and scale Execution and documentation of all lab experiments
Assignment for the Following Curricula General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Course L1740: Lab Cyber-Physical Systems
Typ Problem-based Learning
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Prof. Heiko Falk
Language DE/EN
Cycle SoSe
Content
  • Experiment 1: Programming in NXC
  • Experiment 2: Programming the Robot in Matlab/Simulink
  • Experiment 3: Programming the Robot in LabVIEW
Literature
  • Peter Marwedel. Embedded System Design - Embedded System Foundations of Cyber-Physical Systems. 2nd Edition, Springer, 2012.
  • Begleitende Foliensätze

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) Problem-based Learning 4 3
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 medical technology and its principles, including imaging systems, computer aided surgery, medical sensor systems, medical information systems. They are able to give an overview of regulatory affairs and standards in medical technology.

Skills

The students are able to apply principles of medical technology to solving actual problems.


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 96, Study Time in Lecture 84
Credit points 6
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
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 Problem-based Learning
Hrs/wk 4
CP 3
Workload in Hours Independent Study Time 34, Study Time in Lecture 56
Lecturer Prof. Alexander Schlaefer
Language DE
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
Examination Oral exam
Examination duration and scale 30 minutes
Assignment for the Following Curricula Computer Science: Specialisation Computational Mathematics: Elective Compulsory
Electrical Engineering: Core qualification: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Computer 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. Anusch Taraz
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 name the basic concepts in Mathematical Statistics. 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
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 M1300: Software Development

Courses
Title Typ Hrs/wk CP
Software Development (L1790) Problem-based Learning 2 5
Software Development (L1789) Lecture 1 1
Module Responsible Prof. Sibylle Schupp
Admission Requirements None
Recommended Previous Knowledge
  • Introduction to Software Engineering
  • Programming Skills
  • Experience with Developing Small to Medium-Size Programs 
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
Students explain the fundamental concepts of agile methods, describe the process of 
test-driven development, and explain how continuous integration can be used in
different scenarios. They give examples of selected pitfalls in software development,
regarding scalability and other non-functional requirements. They write unit tests and build scripts and combine them in a corresponding integration environment. They explain major activities in requirements analysis, program comprehension, and agile project development.
Skills
For a given task on a legacy system, students identify the corresponding
parts in the system and select an appropriate method for understanding the
details. They choose the proper approach of splitting a task in
independent testable and extensible pieces and, thus, solve the task
with proper methods for quality assurance. They design tests for 
legacy systems, create automated builds, and find errors at different
levels. They integrate the resulting artifacts in a continuous
development environment
Personal Competence
Social Competence

Students discuss different design decisions in a group. They defend their solutions orally. They communicate in English.

Autonomy

Using accompanying tools, students can assess their level of knowledge continuously and adjust it appropriately.   Within limits, they can set their own learning goals. Upon successful completion, students can identify and formulate concrete problems of software systems and propose solutions. Within this field, they can conduct independent studies to acquire the necessary competencies. They can devise plans to arrive at new solutions or assess existing ones.

Workload in Hours Independent Study Time 138, Study Time in Lecture 42
Credit points 6
Examination Project
Examination duration and scale
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Course L1790: Software Development
Typ Problem-based Learning
Hrs/wk 2
CP 5
Workload in Hours Independent Study Time 122, Study Time in Lecture 28
Lecturer Dr. Sandro Schulze
Language EN
Cycle SoSe
Content
Literature
Course L1789: Software Development
Typ Lecture
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dr. Sandro Schulze
Language EN
Cycle SoSe
Content
  • Agile Methods
  • Test-Driven Development and Unit Testing
  • Continuous Integration
  • Web Services
  • Scalability
  • From Defects to Failure
Literature

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
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

Specialization Engineering Sciences

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

Elektrotechnik I, Elektrotechnik II, Mathematik I, Mathematik II, Mathematik III


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
Examination Written exam
Examination duration and scale 90-150 minutes
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Electrical Engineering: Compulsory
Electrical Engineering: Core qualification: Compulsory
General Engineering Science (English program): Specialisation Electrical Engineering: Compulsory
Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory
Technomathematics: Specialisation 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 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 Thermodynamic. They know the relation of the kinds of energy according to 1st law of Thermodynamic and are aware about the limits of energy conversions according to 2nd law of Thermodynamic. 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 Thermodynamic 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 Thermodynamic.


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
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula General Engineering Science (German program): Core qualification: Compulsory
Bioprocess Engineering: Core qualification: Compulsory
Energy and Environmental Engineering: Core qualification: Compulsory
General Engineering Science (English program): 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 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 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
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
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 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
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
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 M1105: Mechanics III (GES)

Courses
Title Typ Hrs/wk CP
Mechanics III (GES) (L1421) Lecture 3 3
Mechanics III (GES) (L1420) Recitation Section (small) 2 2
Mechanics III (GES) (L1419) Recitation Section (large) 1 1
Module Responsible Prof. Radoslaw Iwankiewicz
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge  The primary purpose of the study of Mechanics III (Fluid Statics, Kinematics and Kinetics)  is to develop the capacity to predict the effects of forces and motions, necessary for the analysis and design of moving machine parts, different machinery, vehicles, aircraft, spacecraft, automatic control systems, etc.The particular objectives of this course are to:
  1. Determine the hydrostatic forces acting on different objects.
  2. Analyse stability of floating bodies.
  3. Analyse the  kinematics and kinetics of a  particle  in different  reference systems,
  4. Analyse the motion of the system of  particles and forces acting on it,
  5. Analyse the plane motion of a rigid body (simple mechanism) and forces acting on it.  
  6. Analyse the three-dimensional motion of a rigid body and forces acting on it.
Skills  At the end of this course the student should be able to:
  1. Solve the equilibrium problems with account for hydrostatic pressure forces.
  2. Analyse stability of  simple floating bodies.

3. Calculate the velocity and acceleration of a particle in different reference systems.

  • 4. Derive and solve the equation of motion of a particle in different reference systems.

5. Analyse the motion of the system of  particles and forces acting on it with the aid of work-energy and impulse-momentum relationships,

6. Calculate the instantaneous  linear and angular velocities and accelerations of the planar mechanisms.

7. Derive and solve the equations of a plane motion of a  rigid body and find forces acting on it,

8. Apply work-energy and impulse-momentum relationships to analyse plane kinetics of a rigid body.

9. Calculate the instantaneous  linear and angular velocities and accelerations of  the three-dimensional motion of a rigid body.

10. Derive the equations of a motion of a  three-dimensional motion  of a rigid body.

11. Apply in three-dimensional kinematics and  kinetics of rigid body  both methods of vector algebra and matrix methods.

Personal Competence
Social Competence Students can: - work in groups and report on the findings, - develop joint solutions in mixed teams and present them to others, - assess the team collaboration and their share in it.
Autonomy Students are able to: -solve the problems independently with the help of hints, - assess their own strengths and weaknesses, e.g. with the aid of the mid-term test.
Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Credit points 6
Examination Written exam
Examination duration and scale 2 hours Fluid Statics: hydrostatic pressure, buoyancy, stability of floating vessels. Kinematics of particle, of plane and 3D rigid bod,y. Kinetics of particle, system of particles, of plane and 3D rigid body. Vector and matrix algebra formulation.
Assignment for the Following Curricula 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
Course L1421: Mechanics III (GES)
Typ Lecture
Hrs/wk 3
CP 3
Workload in Hours Independent Study Time 48, Study Time in Lecture 42
Lecturer Prof. Radoslaw Iwankiewicz
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L1420: Mechanics III (GES)
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Radoslaw Iwankiewicz
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L1419: Mechanics III (GES)
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Radoslaw Iwankiewicz
Language EN
Cycle WiSe
Content

FLUID  STATICS

  1. Fluid pressure, hydrostatic pressure  on flat and cylindrical surfaces.
  2. Buoyancy force, buoyancy center, metacenter, stability of floating objects.

KINEMATICS

  1. Kinematics of a particle. Plane curvilinear motion: rectangular coordinates, normal and tangential coordinates, polar coordinates. Space curvilinear motion.
  2. Constrained motion of connected particles.
  3. Plane kinematics of a rigid body.
  4. Relative (compound) motion.
  5. Three-dimensional kinematics of a rigid body.

KINETICS

  1. Kinetics of  a particle and of a system of particles.
  2. Plane  kinetics of a rigid body.
  3. Three-dimensional kinetics of a rigid body.
Literature

1.  J.L. Meriam and L.G, Kraige, Engineering Mechanics,  Vol. 2, Dynamics, John Wiley & Sons, SI Version, 4th Edition

2 . R.C. Hibbeler, Engineering Mechanics,  Dynamics, Pearson, Prentice Hall, SI 3rd Edition

Module M0783: Measurements: Methods and Data Processing

Courses
Title Typ Hrs/wk CP
EE Experimental Lab (L0781) Laboratory 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
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
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: Elective Compulsory
Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Course L0781: EE Experimental Lab
Typ Laboratory 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. Günter Ackermann, 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 M1235: Electrical Power Systems I

Courses
Title Typ Hrs/wk CP
Electrical Power Systems I (L1670) Lecture 3 4
Electrical Power Systems I (L1671) Recitation Section (large) 2 2
Module Responsible Prof. Christian Becker
Admission Requirements none
Recommended Previous Knowledge

Fundamentals of Electrical Engineering

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

Students are able to give an overview of conventional and modern electric power systems.  They can explain in detail and critically evaluate technologies of electric power generation, transmission, storage, and distribution as well as integration of equipment into electric power systems.

Skills

With completion of this module the students are able to apply the acquired skills in applications of the design, integration, development of electric power systems and to assess the results.

Personal Competence
Social Competence

The students can participate in specialized and interdisciplinary discussions, advance ideas and represent their own work results in front of others.

Autonomy

Students can independently tap knowledge of the emphasis of the lectures. 

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Written exam
Examination duration and scale 90 - 150 minutes
Assignment for the Following Curricula General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Elective Compulsory
Electrical Engineering: Core qualification: Elective Compulsory
Energy and Environmental Engineering: Specialisation Energy Engineering: Elective Compulsory
Energy Systems: Specialisation Energy Systems: Elective Compulsory
Energy Systems: Specialisation Energy Systems: Elective Compulsory
General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory
Renewable Energies: Core qualification: Compulsory
Renewable Energies: Core qualification: Compulsory
Course L1670: Electrical Power Systems I
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Christian Becker
Language DE
Cycle WiSe
Content
  • fundamentals and current development trends in electric power engineering 
  • tasks and history of electric power systems
  • symmetric three-phase systems
  • fundamentals and modelling of eletric power systems 
    • lines
    • transformers
    • synchronous machines
    • grid structures and substations 
  • fundamentals of energy conversion
    • electro-mechanical energy conversion
    • thermodynamics
    • power station technology
    • renewable energy conversion systems
  • on-board electrical power systems 
  • steady-state network calculation
    • network modelling
    • load flow calculation
    • (n-1)-criterion
  • symmetric failure calculations, short-circuit power
  • asymmetric failure calculation
    • symmetric components
    • calculation of asymmetric failures
  • control in networks and power stations
  • insulation coordination and protection
  • grid planning
  • power economy fundamentals
Literature

K. Heuck, K.-D. Dettmann, D. Schulz: "Elektrische Energieversorgung", Vieweg + Teubner, 9. Auflage, 2014

A. J. Schwab: "Elektroenergiesysteme", Springer, 3. Auflage, 2012

R. Flosdorff: "Elektrische Energieverteilung" Vieweg + Teubner, 9. Auflage, 2005

Course L1671: Electrical Power Systems I
Typ Recitation Section (large)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Christian Becker
Language DE
Cycle WiSe
Content
  • fundamentals and current development trends in electric power engineering 
  • tasks and history of electric power systems
  • symmetric three-phase systems
  • fundamentals and modelling of eletric power systems 
    • lines
    • transformers
    • synchronous machines
    • grid structures and substations 
  • fundamentals of energy conversion
    • electro-mechanical energy conversion
    • thermodynamics
    • power station technology
    • renewable energy conversion systems
  • on-board electrical power systems 
  • steady-state network calculation
    • network modelling
    • load flow calculation
    • (n-1)-criterion
  • symmetric failure calculations, short-circuit power
  • asymmetric failure calculation
    • symmetric components
    • calculation of asymmetric failures
  • control in networks and power stations
  • insulation coordination and protection
  • grid planning
  • power economy fundamentals
Literature

K. Heuck, K.-D. Dettmann, D. Schulz: "Elektrische Energieversorgung", Vieweg + Teubner, 9. Auflage, 2014

A. J. Schwab: "Elektroenergiesysteme", Springer, 3. Auflage, 2012

R. Flosdorff: "Elektrische Energieverteilung" Vieweg + Teubner, 9. Auflage, 2005

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
Examination Written exam
Examination duration and scale
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
Mechatronics: Core qualification: Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective 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 M1242: Quantum Mechanics for Engineers

Courses
Title Typ Hrs/wk CP
Quantum Mechanics for Engineers (L1686) Lecture 2 3
Quantum Mechanics for Engineers (L1688) Recitation Section (small) 2 3
Module Responsible Prof. Wolfgang Hansen
Admission Requirements None
Recommended Previous Knowledge
  • Knowledge in physics, particularly in optics and wave phenomena;
  • knowledge in mathematics, particularly linear algebra, vector calculus, complex numbers and Fourier expansion
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students are able to describe and explain basic terms and principles of quantum mechanics.  They can distinguish commons and differences to classical physics and know, in which situations quantum mechanical phenomena may be expected.
Skills The students get the ability to apply concepts and methods of quantum mechanics to simple problems and systems. Vice versa, they are also able to comprehend requirements and principles of quantum mechanical devices.
Personal Competence
Social Competence The students discuss contents of the lectures and present solutions to simple quantum mechanical problems in small groups during the exercises.
Autonomy The students are able to independently find answers to simple questions on quantum mechanical systems. The students are able to independently comprehend literature to more complex subjects with quantum mechanical background.  
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula Computer Science: Specialisation Computational Mathematics: Elective Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Core qualification: Elective Compulsory
Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory
Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory
Course L1686: Quantum Mechanics for Engineers
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Wolfgang Hansen
Language DE
Cycle WiSe
Content

This lecture introduces into fundamental concepts, methods, and definitions in quantum mechanics, which are needed in modern material and device science. Applications will be discussed using examples in the field of electronic and optical devices.

Central topics are:

Schrödinger equation, wave function, operators, eigenstates, eigenvalues, quantum wells, harmonic oscillator, tunnel processes, resonant tunnel diode, band structure, density of states, quantum statistics,  Zener-diode, stationary perturbation calculation with the quantum-confined Stark effect as an example, Fermi’s golden rule and transition matrix elements, heterostructure laser, quantum cascade laser, many-particle physics, molecules and exchange interaction, quantum bits and quantum cryptography.

Literature

Autor

Titel

Verlag

ISBN-Nr.

Jahr

David K. Ferry

Quantum Mechanics

IOP Publishing Ltd

0-7503-0327-1 (hbk)
0-7503-0328-X (pbk)

1995

M. Jaros

Physics and Applications of Semiconductor Microstructures

Clarendon Press

0-19-851994-X
0-19-853927-4 (Pbk)

1989

Randy Harris

Moderne Physik
Lehr- und Übungsbuch
2., aktualisierte Auflage

Kapitel 3-10

Pearson Deutschland GmbH

978-3-86894-115-9

2013

Course L1688: Quantum Mechanics for Engineers
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Wolfgang Hansen
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

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
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 M0748: Materials in Electrical Engineering

Courses
Title Typ Hrs/wk CP
Electrotechnical Experiments (L0714) Lecture 1 1
Materials in Electrical Engineering (L0685) Lecture 2 3
Materials in Electrical Engineering (Problem Solving Course) (L0687) Recitation Section (small) 2 2
Module Responsible Prof. Manfred Eich
Admission Requirements None
Recommended Previous Knowledge Highschool level physics and mathematics
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the composition and the structural properties of materials used in electrical engineering. Students can explicate the relevance of mechanical, electrical, thermal, dielectric, magnetic and chemical properties of materials in view of their applications in electrical engineering.

Skills

Students can identify appropriate descriptive models and apply them mathematically. They can derive approximative solutions and judge factors influential on the performance of materials in electrical engineering applications.


Personal Competence
Social Competence

Students can jointly solve subject related problems in groups. They can present their results effectively within the framework of the problem solving course.


Autonomy

Students are capable to extract relevant information from the provided references and to relate this information to the content of the lecture. They can reflect their acquired level of expertise with the help of lecture accompanying measures such as exam typical exam questions. Students are able to connect their knowledge with that acquired from other lectures.


Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Written exam
Examination duration and scale 60 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 Engineering Sciences: Elective Compulsory
Course L0714: Electrotechnical Experiments
Typ Lecture
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dr. Wieland Hingst
Language DE
Cycle SoSe
Content

Agenda:

- Natural sources of electricity

- Oscilloscope

- Characterizing signals

- 2 terminal circuit elements

- 2-ports

- Power

- Matching

- Inductive coupling

- Resonance

- Radio frequencies

- Transistor circuits

- Electrical measurement

- Materials for the EE

- Electrical fun


Literature

Tietze, Schenk: "Halbleiterschaltungstechnik", Springer


Course L0685: Materials in Electrical Engineering
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Manfred Eich
Language DE
Cycle SoSe
Content

The Hamiltonian approach to classical mechanics. Analysis of a simple oscillator.
Analysis of vibrations in a one-dimensional lattice.
Phononic bandgap
Introduction to quantum mechanics
Wave function, Schrödinger’s equation, observables and measurements.
Quantum mechanical harmonic oscillator and spectral decomposition.
Symmetries, conserved quantities, and the labeling of states.
Angular momentum
The hydrogen atom
Waves in periodic potentials
Reciprocal lattice and reciprocal lattice vectors
Band gap
Band diagrams
The free electron gas and the density of states
Fermi-Dirac distribution
Density of charge carriers in semiconductors
Conductivity in semiconductors. Engineering conductivity through doping.
The P-N junction (diode)
Light emitting diodes
Electromagnetic waves interacting with materials
Reflection and refraction
Photonic band gaps
Origins of magnetization
Hysteresis in ferromagnetic materials
Magnetic domains

Literature

1.Anikeeva, Beach, Holten-Andersen, Fink, Electronic, Optical and Magnetic Properties of Materials,
Massachusetts Institute of Technology (MIT), 2013

2.Hagelstein et al., Introductory Applied Quantum and Statistical Mechanics, Wiley 2004

3.Griffiths, Introduction to Quantum Mechanics, Prentice Hall, 1994

4.Shankar, Principles of Quantum Mechanics, 2nd ed., Plenum Press, 1994

5.Fick, Einführung in die Grundlagen der Quantentheorie, Akad. Verlagsges., 1979

6.Kittel, Introduction to Solid State Physics, 8th ed., Wiley, 2004

7.Ashcroft, Mermin, Solid State Physics, Harcourt, 1976

8.Pierret, Semiconductor Fundamentals Vol. 1, Addison Wesley, 1988

9.Sze, Physics of Semiconductor Devices, Wiley, 1981

10.Saleh, Teich, Fundamentals of Photonics, 2nd ed., 2007

11.Joannopoulos, Johnson, Winn Meade, Photonic Crystals, 2nd ed., Princeton Universty Press, 2008

12.Handley, Modern Magnetic Materials, Wiley, 2000

13.Wikipedia, Wikimedia

Course L0687: Materials in Electrical Engineering (Problem Solving Course)
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Manfred Eich
Language DE
Cycle SoSe
Content
  • Atom structure and periodic system
  • Atom binding and crystal structure
  • Structure and properties of alloys:
    diffusion, phase diagrams, phase separation and grain boundaries
  • Material properties:
    Mechanical, thermal, electrical, dielectric properties
  • Metals
  • Semiconductors
  • Ceramics and glasses
  • Polymers
  • Magnetic materials
  • Electrochemistry
    Oxidation numbers, electrolysis, batteries, fuel cells
Literature

H. Schaumburg: Einführung in die Werkstoffe der Elektrotechnik, Teubner (1993)

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
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale
Assignment for the Following Curricula Computer Science: Specialisation Computational Mathematics: Elective Compulsory
Electrical Engineering: Core qualification: Elective Compulsory
Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory
Technomathematics: Specialisation II. Informatics: Elective Compulsory
Technomathematics: Core qualification: 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

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) Problem-based Learning 4 3
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 medical technology and its principles, including imaging systems, computer aided surgery, medical sensor systems, medical information systems. They are able to give an overview of regulatory affairs and standards in medical technology.

Skills

The students are able to apply principles of medical technology to solving actual problems.


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 96, Study Time in Lecture 84
Credit points 6
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
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 Problem-based Learning
Hrs/wk 4
CP 3
Workload in Hours Independent Study Time 34, Study Time in Lecture 56
Lecturer Prof. Alexander Schlaefer
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0610: Electrical Machines

Courses
Title Typ Hrs/wk CP
Electrical Machines (L0293) Lecture 3 4
Electrical Machines (L0294) Recitation Section (large) 2 2
Module Responsible Prof. Günter Ackermann
Admission Requirements none
Recommended Previous Knowledge

Basics of mathematics, in particular complexe numbers, integrals, differentials

Basics of electrical engineering and mechanical engineering

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

Students can to draw and  explain the basic principles of electric and magnetic fields. 

They can describe the function of the standard types of electric machines and present the corresponding equations and characteristic curves. For typically used drives they can explain the major parameters of the energy efficiency of the whole system from the power grid to the driven engine.

Skills

Students arw able to calculate two-dimensional electric and magnetic fields in particular ferromagnetic circuits with air gap. For this they apply the usual methods of the design auf electric machines.

They can calulate the operational performance of electric machines from their given characteristic data and selected quantities and characteristic curves. They apply the usual equivalent circuits and graphical methods.


Personal Competence
Social Competence none
Autonomy

Students are able independently to calculate electric and magnatic fields for applications. They are able to analyse independently the operational performance of electric machines from the charactersitic data and theycan calculate thereof selected quantities and characteristic curves.


Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Written exam
Examination duration and scale 120 Minuten
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (German program): Specialisation Mechanical Engineering: Elective Compulsory
General Engineering Science (German program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering: Elective Compulsory
Electrical Engineering: Core qualification: Elective 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: Elective Compulsory
General Engineering Science (English program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering: Elective Compulsory
Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory
Logistics and Mobility: Specialisation Engineering Science: Elective Compulsory
Mechanical Engineering: Core qualification: Elective Compulsory
Mechatronics: Core qualification: Compulsory
Course L0293: Electrical Machines
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Günter Ackermann
Language DE
Cycle SoSe
Content

Electric field: Coulomb´s law, flux (field) line, work, potential, capacitor, energy, force

Magnetic field: force, flux line, Ampere´s law, field at bounderies, flux, magnetic circuit, hysteresis, induction, self-induction, mutual inductance, transformer

DC-Machines: Construction and layout, torque generation mechanismen, torque vs speed characteristics, commutation,

Asynchronous Machines. Magnetic field, construction and layout, equivalent single line diagram, complex stator current diagram (Heylands´diagram), torque vs. speed characteristics, rotor layout (Squirrelcage vs. sliprings),

Synchronous machines, construction and layout, equivalent single line diagrams, no-load and short-cuircuit characteristics, vector diagrams, motor and generator operation

drives with variable speed, inverter fed operation, special drives, step motors,



Literature

Hermann Linse, Roland Fischer: "Elektrotechnik für Maschinenbauer", Vieweg-Verlag; Signatur der Bibliothek der TUHH: ETB 313

Ralf Kories, Heinz Schmitt-Walter: "Taschenbuch der Elektrotechnik"; Verlag Harri Deutsch; Signatur der Bibliothek der TUHH: ETB 122

"Grundlagen der Elektrotechnik" - anderer Autoren

Fachbücher "Elektrische Maschinen"

Course L0294: Electrical Machines
Typ Recitation Section (large)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Günter Ackermann
Language DE
Cycle SoSe
Content

Exercises to the application of electric and magnetic fields.

Excercises to the operational performance of eletric machines.

Literature

Hermann Linse, Roland Fischer: "Elektrotechnik für Maschinenbauer", Vieweg-Verlag; Signatur der Bibliothek der TUHH: ETB 313

Ralf Kories, Heinz Schmitt-Walter: "Taschenbuch der Elektrotechnik"; Verlag Harri Deutsch; Signatur der Bibliothek der TUHH: ETB 122

"Grundlagen der Elektrotechnik" - anderer Autoren

Fachbücher "Elektrische Maschinen"

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

The students can solve problems by their own and are able to acquire skills from the lecture and the literature. They are able to test their knowledge using computer animations. They can test their level of knowledge by answering short questions and tests during the lecture. They are able to relate their acquired knowledge to other lectures (e.g. Electrical Engineering I-III and Mathematics I-III). They can familiarize themselves with a research topic and can prepare a presentation.


Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Credit points 6
Examination Written exam
Examination duration and scale
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 Engineering Sciences: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Course L0571: Research Seminar Electrical Engineering, Computer Science, Mathematics
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Dozenten des SD E, Siavash Ahmadi Barogh
Language DE/EN
Cycle SoSe
Content

Seminar talk on a given subject


Literature Themenabhängig / subject related
Course L0570: Transmission Line Theory
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Arne Jacob
Language DE
Cycle SoSe
Content

- Wave propagation along transmission lines

- Transient behavior of transmission lines

- Transmission lines in steady state

- Impedance transformation and Smith chart

- Equivalent circuits

- Coupled transmission lines and symmetrical components


Literature

- Unger, H.-G., "Elektromagnetische Wellen auf Leitungen", Hüthig Verlag (1991)


Course L0572: Transmission Line Theory
Typ Recitation Section (large)
Hrs/wk 2
CP 1
Workload in Hours Independent Study Time 2, Study Time in Lecture 28
Lecturer Prof. Arne Jacob
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Thesis

Module M-001: Bachelor Thesis

Courses
Title Typ Hrs/wk CP
Module Responsible Professoren der TUHH
Admission Requirements
  • According to General Regulations §24 (1):

    At least 126 ECTS credit points have to be achieved in study programme. The examinations board decides on exceptions.

Recommended Previous Knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • The students can select, outline and, if need be, critically discuss the most important scientific fundamentals of their course of study (facts, theories, and methods).
  • On the basis of their fundamental knowledge of their subject the students are capable in relation to a specific issue of opening up and establishing links with extended specialized expertise.
  • The students are able to outline the state of research on a selected issue in their subject area.
Skills
  • The students can make targeted use of the basic knowledge of their subject that they have acquired in their studies to solve subject-related problems.
  • With the aid of the methods they have learnt during their studies the students can analyze problems, make decisions on technical issues, and develop solutions.
  • The students can take up a critical position on the findings of their own research work from a specialized perspective.


Personal Competence
Social Competence
  • Both in writing and orally the students can outline a scientific issue for an expert audience accurately, understandably and in a structured way.
  • The students can deal with issues in an expert discussion and answer them in a manner that is appropriate to the addressees. In doing so they can uphold their own assessments and viewpoints convincingly.


Autonomy
  • The students are capable of structuring an extensive work process in terms of time and of dealing with an issue within a specified time frame.
  • The students are able to identify, open up, and connect knowledge and material necessary for working on a scientific problem.
  • The students can apply the essential techniques of scientific work to research of their own.
Workload in Hours Independent Study Time 360, Study Time in Lecture 0
Credit points 12
Examination according to Subject Specific Regulations
Examination duration and scale laut FSPO
Assignment for the Following Curricula General Engineering Science (German program): Thesis: Compulsory
General Engineering Science (German program, 7 semester): Thesis: Compulsory
Civil- and Environmental Engineering: Thesis: Compulsory
Bioprocess Engineering: Thesis: Compulsory
Computer Science: Thesis: Compulsory
Electrical Engineering: Thesis: Compulsory
Energy and Environmental Engineering: Thesis: Compulsory
General Engineering Science (English program): Thesis: Compulsory
General Engineering Science (English program, 7 semester): Thesis: Compulsory
Computational Science and Engineering: Thesis: Compulsory
Logistics and Mobility: Thesis: Compulsory
Mechanical Engineering: Thesis: Compulsory
Mechatronics: Thesis: Compulsory
Naval Architecture: Thesis: Compulsory
Technomathematics: Thesis: Compulsory
Process Engineering: Thesis: Compulsory