Master‘s Program Computational Engineering · Content Curriculum.....3 Compulsory Courses CE-P01 – CE-P07.....4 CE-P01: Mathematical Aspects of Differential Equations and Numerical

Master‘s ProgramComputational Engineering

Module Handbook

CurriculumModule description

Content Curriculum ............................................................................................................................ 3

Compulsory Courses CE-P01 – CE-P07 ............................................................................. 4

CE-P01: Mathematical Aspects of Differential Equations and Numerical Mathematics ....... 5

CE-P02: Mechanical Modeling of Materials ......................................................................... 7

CE-P03: Computer-based Analyses of Steel Structures ..................................................... 9

CE-P04: Modern Programming Concepts in Engineering.................................................. 11

CE-P05: Finite Element Methods in Linear Structural Mechanics ...................................... 13

CE-P06: Fluid Dynamics ................................................................................................... 15

CE-P07: Continuum Mechanics ........................................................................................ 17

Compulsory Optional Courses CE-WP01 – CE-WP28 ...................................................... 19

CE-WP01: Variational Calculus and Tensor Analysis ........................................................ 20

CE-WP03: Dynamics and Adaptronics .............................................................................. 22

CE-WP04: Advanced Finite Element Methods .................................................................. 25

CE-WP05: Computational Fluid Dynamics ........................................................................ 27

CE-WP06: Finite Element Method for Nonlinear Analyses of Materials and Structures ..... 30

CE-WP08: Numerical Methods and Stochastics ............................................................... 32

CE-WP09: Numerical Simulation in Geotechnics and Tunneling ....................................... 34

CE-WP10: Object-oriented Modelling and Implementation of Structural Analysis Software .... 36

CE-WP11: Dynamics of Structures ................................................................................... 38

CE-WP12: Computational Plasticity .................................................................................. 40

CE-WP13: Advanced Control Methods for Adaptive Mechanical Systems ........................ 42

CE-WP14: Computational Wind Engineering .................................................................... 44

CE-WP15: Design Optimization ........................................................................................ 47

CE-WP16: Parallel Computing .......................................................................................... 49

CE-WP17: Adaptive Finite Element Methods .................................................................... 51

CE-WP18: Safety and Reliability of Engineering Structures .............................................. 54

CE-WP19: Computational Fracture Mechanics ................................................................. 56

CE-WP20: Materials for Aerospace Applications .............................................................. 58

CE-WP24: Case Study A .................................................................................................. 60

CE-WP25: High-Performance Computing on Multi- and Manycore Processors ................. 62

CE-WP26: High-Performance Computing on Clusters ...................................................... 64

Master's program Computational Engineering - Module Handbook

1 last updated october 2020

CE-WP28: Machine Learning: Supervised Methods .......................................................... 66

Optional Courses CE-W01 – CE-W08 ................................................................................ 68

CE-W01: Training of Competences (Part 1) ...................................................................... 69

CE-W02: Training of Competences (Part 2) ...................................................................... 71

CE-W03: Case Study B .................................................................................................... 72

CE-W05: Simulation of Incompressible Turbulent Flows with the Finite Volume Method .. 74

CE-W06: Advanced Constitutive Models for Geomaterials ................................................ 76

CE-W07: Applied Finite Element Method .......................................................................... 78

CE-W08: Quantum Computing.......................................................................................... 80

Master Thesis CE-M .......................................................................................................... 82

CE-M: Master Thesis ........................................................................................................ 83



CE-P01 Mathematical Aspects of Differential Equations and Numerical Mathematics 4 6 1

CE-P02 Mechanical Modeling of Materials 4 6 1

CE-P03 Computer-based Analysis of Steel Structures 4 6 1

CE-P04 Modern Programming Concepts in Engineering 4 6 1

CE-P05 Finite Element Methods in Linear Structural Mechanics 4 6 1

CE-P06 Fluid Dynamics 2 3 2

CE-P07 Continuum Mechanics 4 6 2

39

CE-WP01 Variational Calculus and Tensor Analysis 3 4 1

CE-WP03 Dynamics and Adaptronics 4 6 2

CE-WP04 Advanced Finite Element Methods 4 6 2

CE-WP05 Computational Fluid Dynamics 4 6 2

CE-WP06 Finite Element Methods for Nonlinear Analyses of Materials and Structures 2 3 2

CE-WP08 Numerical Methods and Stochastics 4 6 2

CE-WP09 Numerical Simulation in Geotechnics and Tunnelling 4 6 2

CE-WP10 Object-oriented Modelling and Implementation of Structural Analysis Software 2 3 2

CE-WP16 Parallel Computing 4 6 2

CE-WP25 High-Performance Computing on Multi- and Manycore Processors 4 6 2

CE-WP28 Machine Learning: Supervised Methods 4 6 2

CE-WP11 Dynamics of Structures 4 6 3

CE-WP12 Computational Plasticity 3 4 3

CE-WP13 Advanced Control Methods for Adaptive Mechanical Systems 4 6 3

CE-WP14 Computational Wind Engineering 2 3 3

CE-WP15 Design Optimization 4 6 3

CE-WP17 Adaptive Finite Element Methods 4 6 3

CE-WP18 Safety and Reliabilty of Engineering Structures 4 6 3

CE-WP19 Computational Fracture Mechanics 4 6 3

CE-WP20 Materials for Aerospace Applications 4 6 3

CE-WP26 High-Performance Computing on Clusters 4 6 3

CE-WP24 Case Study A 2 3 2+3

35

CE-W01 Training of Competences (part 1) 4 4 1

CE-W07 Applied Finite Element Method 2 2 1

CE-W02 Training of Competences (part 2) 4 4 2

CE-W06 Advanced Constitutive Models for Geomaterials 2 3 2

CE-W05 Simulation of Incompressible Turbulent Flows with the Finite Volume Method 2 3 3

CE-W08 Quantum Computing 2 3 3

CE-W03 Case Study B 2 3 2+3

other relevant courses of the faculty or from engineering faculties of other universites 1+2+3

16

30

39

35

16

30

120

4

1s

t , 2

nd &

3rd

sem

este

r

Minimum Subtotal CP: Compulsory optional courses

Minimum Subtotal CP: Optional Courses

Subtotal CP: Compulsory CoursesSubtotal CP: Compulsory optional courses

Subtotal CP: Optional courses

Sum CP in total:

CE-M Master Thesis

1s

t , 2

nd &

3rd

sem

este

r4

th

Sem

este

r

Subtotal CP: Master Thesis

Subtotal CP: Master Thesis

WPCompulsory

Optional

Courses

35 CP

MMaster-Thesis

WOptional

Courses

16 LP

PCompulsory

Courses

39 CP

- 30

1s

t & 2

nd s

em

este

r

Master's Program Computational Engineering

Code Module Namehours

per

week

Subtotal CP: Compulsory Courses

SemesterCP

Curriculum



Compulsory Courses

CE-P01 – CE-P07



Study course: Master’s Program Computational Engineering

Module name: CE-P01: Mathematical Aspects of Differential Equations and Numerical Mathematics

Abbreviation, if applicable: MADENM

Sub-heading, if applicable: -

Module Coordinator(s): Prof. Dr. G. Röhrle

Classification within the curriculum:

Master’s Program Computational Engineering: compulsory course, 1st semester This course is not offered in any other study program.

Courses included in the module, if applicable:

Mathematical Aspects of Differential Equations and Numerical Mathematics

Semester/term: 1st Semester / Winter term

Lecturer(s): Prof. Dr. B. Bramham

Language: English

Requirements: No prior knowledge or preliminary modules. Basic calculus and experience with matrices.

Teaching format / class hours per week during the semester:

Lectures: 2h Exercises: 2h Remark: Due to the mixed background of the students, the exercise sessions often amount to additional lectures.

Study/exam achievements: Written examination / 180 minutes

Workload [h / LP]: 180 / 6

Thereof face-to-face teaching [h] 60

Preparation and post-processing (including examination) [h]

90

Seminar papers [h] -

Homework [h] 30

Credit points: 6



Learning goals / competences:

The course will focus on the mathematical formulation of differential equations with applications to elastic theory and fluid mechanics. It gives an introduction to geometric linear algebra with emphasis on function spaces, coupled with the elementary aspects of partial differential equations. The students should learn to understand the mathematics side of the Finite Element Method for elliptic PDE in low dimensions, appropriate Sobolev geometries, the FEM for Dirichlet and Neumann problems. For that reason, the basic principles in methods of error estimation are described to realize the understanding of fast and efficient solvers for the resulting matrix equations. As overall learning goal, the students should attain familiarity with modern methods and concepts for the numerical solution of complicated mathematical problems.

Content:

Linear algebra: Basic concepts and techniques for finite- and infinite-dimensional function spaces stressing the role of linear differential operators. Numerical algorithms for solving linear systems. The mathematics of the finite element method in the context of elliptic partial differential equations (model problems) in dimension two.

Forms of media: Blackboard presentations, one-to-one discussions and discussions in small groups.

Literature: Claes Johnson, Numerical solution of partial differential equations by the finite element method, Cambridge 1987




Module name: CE-P02: Mechanical Modeling of Materials

Abbreviation, if applicable: MECHMOD


Module co-ordinator(s): Prof. Dr.-Ing. D. Balzani

Classification within the Curriculum:

Master’s Program Computational Engineering: compulsory course, 1st semester

This course is not offered in any other study program.

Courses included in the module, if applicable: Mechanical Modeling of Materials


Lecturer(s): Prof. Dr.-Ing. D. Balzani, Assistants

Language: English

Requirements: Basic knowledge in Mathematics and Mechanics (Statics, Dynamics and Strength of Materials)


Lecture: 2h Exercise: 2h


Workload [h / CP]: 180 / 6

thereof face-to-face teaching [h]

60

Preparation and post processing (including examination) [h]

120

Seminar Papers [h] -

Homework [h] -

Credit points: 6




The objective of this course is to present advanced issues of mechanics and the continuum-based modeling of materials starting with basic rheological models. The concepts introduced will be applied to numerous classes of materials. Basic constitutive formulations will be discussed numerically.

Content:

Several advanced issues of the mechanical behavior of materials are addressed in this course. More precisely, the following topics will be covered:

Basic concepts of continuum mechanics (introduction) Introduction to the rheology of materials Theoretical concepts of constitutive modeling 1-dimensional constitutive approaches for

o Elasticity, hyperelasticity o Inelasticity (plasticity, damage, viscoelasticity)

3-dimensional generalization of material modeling concepts

Simple boundary and initial value problems

Forms of media: Computer projector (tablet PC); additional material can be downloaded

Literature: N.S. Ottosen: The Mechanics of Constitutive Modelling, Elsevier, 2005. A. Bertram: Elasticity and Plasticity of Large Deformations: An Introduction, Springer, 2008. A.F. Bower: Applied Mechanics of Solids, CRC Press, 2009..




Module name: CE-P03: Computer-based Analyses of Steel Structures

Abbreviation, if applicable: CbASS


Module Coordinator(s): Prof. Dr. M. Knobloch


Master’s Program Computational Engineering: compulsory course, 1st Semester This course is not offered in any other study program.


- Basics of Analysis and Design, Numerical simulations in Steel Design, Fundamentals for Computer- oriented Structural Analysis and Design assisted by Finite Element Analysis - Stability Behaviour – Members and Plated Structural Elements - Structural Durability


Lecturer(s): Prof. Dr. M. Knobloch, Assistants

Language: English

Requirements: Fundamental knowledge in mechanics and strength of materials


Lecture: 2h Exercise: 2h The course is partially conducted in the Inverted-Classroom format.

Study/exam achievements: Written examination for the total module / 180 minutes




90


Homework [h] 45

Credit points: 6




This course will introduce students to the fundamental structural and fatigue behaviour of steel structures, numerical solution procedures and modelling details. The course aims to achieve a basic understanding of applied mechanics approaches to modelling member behaviour in steel structure problems. The course is addressed to young engineers, who will face the necessity of numerical analysis and applied mechanics more often in their design practice. The purpose of this course is to bridge the gap between applied mechanics and structural steel design using state-of-the-art tools. The students shall become familiar with computer-oriented analyses and assessment methods by using the example of steel constructions. The course will also convey to students the ability to use numerical tools and software packages for the solution of practical problems in engineering.

Content: This course is introductory – by no means does it claim completeness in such dynamically developing fields as numerical analysis of slender steel structures and structural durability. The course intends to achieve a basic understanding of applied mechanics approaches to slender steel structure modelling and structural durability, which can serve as a foundation for the exploration of more advanced theories and analyses of different kind of structures.

Basics of the Analysis, Design and Fundamentals for Computer-Based Calculations Basic principles of structural design Beam theory and torsion Finite elements for beams and plates Software for analyses

Stability Behaviour of Slender Structures and Second Order Theory Geometric non-linear design of structures -

second order analysis Buckling of linear members and frames Lateral buckling and lateral torsional buckling Eigenvalues and –shapes Numerical methods for plate buckling

Structural Durability Fatigue Modern Concepts of Fatigue Strength Design Local Strain Concept Crack Propagation Concept

Forms of media: Video and overhead projector, computer, blackboard, lecture notes

Literature: Kindmann/Kraus: „Computer-oriented Design of Steel Structures“; Ernst & Sohn; 2011 Ballio/Mazzolani: Theory and Design of Steel Structures; Spon Press, 2Rev Ed 2007

Lecture notes




Module name: CE-P04: Modern Programming Concepts in Engineering

Abbreviation, if applicable: MPCE


Module Coordinator(s): Prof. Dr.-Ing. M. König


Master’s Program Computational Engineering: compulsory course, 1st Semester. This course is not offered in any other study program.

Courses included in the module, if applicable: Modern Programming Concepts in Engineering


Lecturer(s): Prof. Dr.-Ing. M. König, Dr.-Ing. K. Lehner

Language: English

Requirements: -


Lectures: 2h Exercises: 2h

Study/exam achievements:

- Written examination / 120 minutes (70%) - Homework (30%)

Workload [h / KP]: 180 / 6



80


Homework [h] 40 (2x20)

Credit points: 6




In this course, students acquire fundamental skills for the development of software solutions for engineering problems. This comprises the capability to analyze a problem with respect to its structure such that adequate object-oriented software concepts, data structures and algorithms can be applied and implemented. In this course Java is used as a programming language. The conveyed solution techniques can be easily transferred to other programming languages.

Content:

Lectures and exercises cover the following topics:

Principles of object-oriented modelling o Encapsulation o Polymorphism o Inheritance

Unified Modelling Language (UML)

Basic programming constructs

Fundamental data structures

Implementation of efficient algorithms o Vector and matrix operations o Solving systems of linear equations o Grid generation techniques

Using software libraries o View3d a visualization toolkit o Packages for graphical user interfaces

During the exercises, students practice object-oriented programming techniques in the computer lab on the basis of fundamental engineering problems.

Forms of media: Data projector, blackboard, demo programs, computer lab

Literature: M. König, Modern Programming Concepts in Engineering, Slides of the lectures C.S. Horstmann and G. Cornell, Core Java. Volume I – Fundamentals, Prentice Hall, 2007 M. T. Goodrich and R. Tomassia, Data Structures and Algorithms in Java, John Wiley & Sons, 2005 M. Fowler, UML Distilled: A Brief Guide to the Standard Object Modeling Language, Addison-Wesley, 2003




Module name: CE-P05: Finite Element Methods in Linear Structural

Mechanics

Abbreviation, if applicable: FEM-I


Module Coordinator: Prof. Dr. techn. G. Meschke


Master’s Program Computational Engineering: compulsory course, 1st Semester Master’s Program ‘Bauingenieurwesen’: compulsory course, 1st Semester

Courses included in the module, if applicable: Finite Element Methods in Linear Structural Mechanics


Lecturer(s): Prof. Dr. techn. G. Meschke, Assistants

Language: English

Requirements: Basics in Mathematics, Mechanics and Structural Analysis (Bachelor level)




- Written examination / 180 minutes (85%) - Seminar papers (15%)




60

Seminar papers [h] 60

Homework [h] -

Credit points: 6




The main goal of this course is to qualify students to numerically solve linear engineering problems by providing a sound methodological basis of the finite element method. In addition to numerical analysis of trusses, beams and plates, the spectrum of possible applications includes analyses of transport processes such as heat conduction and pollutant transport. In seminar papers the students shall apply the basics of the Linear Finite Element Methods learnt in the lectures and solve structural-mechanical problems by means of hand calculations. Furthermore the students are required to program and validate problems in structural analysis and transport processes.

Content:

Introduction to the finite element method in the framework of linear elastodynamics. Based upon the weak form of the boundary value problem principles of spatial discretization using the finite element method are explained step by step. First, one-dimensional isoparametric p-truss elements are used to explain the fundamentals of the finite element method. Afterwards the same methodology is used to develop two- (plane stress and plane strain) and three-dimensional isoparametric p-finite elements for linear structural mechanics. In addition to analyses related to structural mechanics, the application of the finite element method to the spatial discretization of problems associated with transport processes within structures (e.g. heat conduction, pollutant transport, moisture transport, coupled problems) is demonstrated. The second part of the lecture is concerned with finite element models for beams and plates. In this context aspects of element locking and possible remedies are discussed. The lectures are supplemented by exercises to promote the understanding of the underlying theory and to demonstrate the application of the finite element method for the solution of selected examples. Furthermore, practical applications of the finite element method are demonstrated by means of a commercial finite element program.

Forms of media: Blackboard, transparencies, beamer presentations

Literature: Manuscript and Lecture Notes J. Fish and T. Belytschko, A First Course in Finite Elements, Wiley, 2007 K.-J. Bathe, Finite Element Procedures, Prentice Hall, 1996 T.J.R. Hughes, The Finite Element Method. Linear Static and Dynamic Finite Element Analysis, Prentice Hall, 1987 O.C. Zienkiewicz, R.L. Taylor, The Finite Element Method. Part I: Basis and Fundamentals, Elsevier Science & Technology, 2005




Module name: CE-P06: Fluid Dynamics

Abbreviation, if applicable: FD


Module Coordinator(s): Prof. Dr.-Ing. R. Höffer


Master’s Program Computational Engineering: compulsory course, 2nd Semester This course is not offered in any other study program.

Courses included in the module, if applicable: Fluid Dynamics

Semester/term: 2nd Semester / Summer term

Lecturer(s): Prof. Dr.-Ing. R. Höffer, Assistants

Language: English

Requirements: Mathematical Aspects of Differential Equations and Numerical Methods (CE-P01)

Mechanical Modeling of Materials (CE-P02)

Fluid Mechanics (Bachelor level)







30


Homework [h] Course-related, connected homework, individual or group work upon agreement with the lecturers: 30 h.

Credit points: 3




The students shall acquire consolidated skills of the basic laws of hydraulics, potential theory, flow dynamics and turbulence theory. The students shall be enabled to assess and to solve technical problems related to flow dynamics in hydraulics and in aerodynamics.

Content:

The technical basics of dynamic fluid flows are introduced, studied and recapitulated as well as related problems which are relevant for practical applications and solution procedures with an emphasis put on computational aspects. The lectures and exercises contain the following topics: Short review of hydrostatics and dynamics of incompressible flows involving friction (conservation of mass, energy and momentum, Navier-Stokes equations) Potential flow Isotropic turbulence and turbulence in a boundary layer flow Flow over streamlined and bluff bodies The students are guided in the exercises to working out assessment and solution strategies for related, typical technical problems in fluid dynamics.

Forms of media: Blackboard, beamer, overheads, visit to the laboratory; exercises with examples; regular consultations and discussion of homework

Literature: Höffer, R. et al.: Lecture Notes Gersten, K.: Einführung in die Strömungsmechanik. Aktuelle Auflage, Friedrich Vieweg & Sohn Verlag, Braunschweig, Wiesbaden Fox R. W., McDonald A. T. : Introduction to Fluid Mechanics (SI Version), John Wiley & Sons, Inc., 5th Edition, ISBN 0-471-59274-9, 1998 Spurk J. H. : Fluid Mechanics, Springer Verlag , Berlin Heidelberg New York, ISBN 3 – 540 – 61651 -9, 1997




Module name: CE-P07: Continuum Mechanics

Abbreviation, if applicable: CM


Module Coordinator(s): Prof. Dr. rer. nat. K. Hackl


Master’s Program Computational Engineering: compulsory course, 2nd Semester This course is not offered in any other study program.

Courses included in the module, if applicable: Continuum Mechanics


Lecturer(s): Prof. Dr. rer. nat. K. Hackl, Prof. Dr. rer. nat. K.C. Le

Language: English

Requirements: Mathematical Aspects of Differential Equations and Numerical Methods (CE-P01)








120


Homework [h] -

Credit points: 6




Extended knowledge in continuum-mechanical modelling and solution techniques as a prerequisite for computer-oriented structural analysis.

Content:

The course starts with an introduction to the advanced analytical techniques of linear elasticity theory, then moves on to the continuum-mechanical concepts of nonlinear elasticity and ends with the discussion of material instabilities and microstructures. Numerous examples and applications will be given.

Advanced Linear Elasticity Beltrami equation Navier equation Stress-functions Scalar- and vector potentials Galerkin-vector Love-function Solution of Papkovich - Neuber Nonlinear Deformation Strain tensor Polar descomposition Stress-tensors Equilibrium Strain-rates Nonlinear Elastic Materials Covariance and isotropy Hyperelastic materials Constrained materials Hypoelastic materials Objective rates Material stability Microstructures

Forms of media: Blackboard and beamer presentations

Literature: Pei Chi Chou, Nicholas J. Pagano, Elasticity, Dover, 1997 T.C. Doyle, J.L. Ericksen, Nonlinear Elasticity Advances in Appl. Mech. IV, Academic Press, New York, 1956 C. Truesdell, W. Noll, The nonlinear field theories Handbuch der Physik (Flügge Hrsg.), Bd. III/3, Springer-Verlag, Berlin, 1965 J.E. Marsden, T.J.R. Hughes, Mathematical foundation of elasticity, Prentice Hall, 1983 R.W. Ogden, Nonlinear elastic deformation, Wiley & Sons, 1984



Compulsory Optional Courses

CE-WP01 – CE-WP28




Module name: CE-WP01: Variational Calculus and Tensor Analysis

Abbreviation, if applicable: VarTens


Module Coordinator(s): Prof. Dr.-Ing. D. Balzani


Master’s program Computational Engineering: Compulsory optional course, 1st Semester This course is not offered in any other study program.

Courses included in the module, if applicable: Variational Calculus and Tensor Analysis


Lecturer(s): Prof. Dr. rer. nat. K.C. Le

Language: English

Requirements: Basic knowledge in Mathematics and Mechanics







60


Homework [h] 15

Credit points: 4




The objective of this course is to present basic issues of variational methods and tensor analysis. The course will address the basic mathematical aspects and links them to the fundamental framework of continuum mechanics.

Content:

The course covers the following topics:

Motivation: Why do we need variations and tensors in mechanics?

Tensor Analysis:

Vector and tensor notation

Vector and tensor algebra

Dual bases, coordinates in Euclidean space

Differential calculus

Scalar invariants and spectral analysis

Isotropic functions Variational Calculus:

First variation

Boundary conditions

PDEs: Weak and strong form

Constrained minimization problems, Lagrange multipliers

Applications to continuum mechanics

Forms of media: Blackboard or Computer projector. Digital supplementary material.

Literature: B. van Brunt: The Calculus of Variations, Springer, 2010 M. Giaquinta: Calculus of Variations I, Springer, 2010 R.M. Bowen: Introduction to Vectors and Tensors, Dover, 2009. M. Itskov: Tensor Algebra and Tensor Analysis for Engineers: With Applications to Continuum Mechanics, Springer, 2009.




Module name: CE-WP03: Dynamics and Adaptronics

Abbreviation, if applicable: DA


Module Coordinator(s): Prof. Dr. rer. nat. K. C. Le, Prof. Dr.-Ing. T. Nestorović


Master’s Program Computational Engineering: compulsory optional course, 2nd Semester This course is not offered in any other study program.

Courses included in the module, if applicable: Dynamics and Adaptronics


Lecturer(s): Prof. Dr.-Ing. T. Nestorović, Prof. Dr. rer. nat. K. C. Le

Language: English

Requirements:

Mathematical Aspects of Differential Equations and Numerical Methods (CE-P01)


Basic knowledge in Structural Mechanics, Control Theory and Active Mechanical Structures




Written examination / 150 minutes




75


Homework [h] 45

Credit points: 6




First principles in dynamics of discrete and continuous mechanical systems, methods for the solution of dynamical problems and their application to structural dynamics and active vibration control. Acquiring knowledge in fundamental control methods, structural mechanics and modelling and their application to the active control of mechanical structures.

Content:

The course introduces the first principles of the dynamics of discrete and continuous mechanical systems: Newton laws and Hamilton variational principles. The force and energy methods for deriving the equation of motion for systems with a finite number of degrees of freedom as well as for continuous systems are demonstrated. The energy conservation law for conservative systems and the energy dissipation law for dissipative systems are studied. Various exact and approximate methods for solving dynamical problems, along with the Laplace transform method, the method of normal mode for coupled systems, and the Rayleigh method are developed for free and forced vibrations. Various practical examples and applications to resonance and active vibration control are shown. Further, an overall insight of the modelling and control of active structures is given within the course. The terms and definitions as well as potential fields of application are introduced. For the purpose of the controller design for active structural control, the basics of the control theory are introduced: development of linear time invariant models, representation of linear differential equations systems in the state-space form, controllability, observability and stability conditions of control systems. The parallel description of the modelling methods in structural mechanics enables the students to understand the application of control approaches. For actuation/sensing purposes multifunctional active materials (piezo ceramics) are introduced as well as the basics of the numerical model development for structures with active materials. Control methods include time-continuous and discrete-time controllers in the state space for multiple-input multiple-output systems, as well as methods of the classical control theory for single-input single output systems. Differences and analogies between continuous and discrete time control systems are specified and highlighted on the basis of a pole placement method. Closed-loop controller design for active structures is explained. Different application examples and problem solutions show the feasibility and importance of the control methods for structural development. Within this course the students learn computer aided controller design and simulation using Matlab/Simulink software.

Forms of media: Blackboard and beamer presentations, computer exercises



Literature: Le K. C.: Energy Methods in Dynamics, Springer, 2011 Timoshenko S.: Vibration Problems in Engineering, third edition, D. van Nostrand Company, 1956 Fuller C. R., Elliott S. J., Nelson P. A.: Active Control of Vibration, Academic Press Ltd, London, 1996 Franklin G. F., Powell J. D., Emami-Naeini A.: Feedback Control of Dynamic Systems, second edition, Addison-Wesley Publishing Company, 1991 Franklin G. F., Powell J. D., Workman M. L.: Digital Control of Dynamic Systems, third edition, Addison-Wesley Longman, Inc., 1998 Preumont A.: Vibration Control of Active Structures: An Introduction, Kluwer Academic Publishers, Dordrecht, Boston, London, 1997




Module name: CE-WP04: Advanced Finite Element Methods

Abbreviation FEM-II




Master’s Program Computational Engineering: compulsory optional course, 2nd Semester Master’s Program ‘Bauingenieurwesen’: optional course, 2nd Semester

Courses included in the module, if applicable: Advanced Finite Element Methods



Language: English

Requirements: Finite Element Methods in Linear Structural Mechanics (CE-P05)

Basic knowledge in Structural Mechanics, Control Theory and Active Mechanical Structures Basics in Mathematics, Mechanics and Structural Analysis (Bachelor)


Lectures: 2 h Exercises: 2 h


- Written examination / 120 minutes (85%) - Seminar papers & PC exercise / Homework (15%)




60


Homework [h] 60

Credit points: 6




The main goal of this course is to qualify students to numerically solve nonlinear problems in engineering sciences by providing the methodological basis of the geometrically and physically nonlinear finite element method. In seminar papers the students shall apply the basics of the Advanced Finite Element Methods and solve nonlinear structural-mechanical problems by means of hand calculations. Furthermore the students are required to program and validate problems in geometrically and physically nonlinear structural analysis.

Contents:

Based upon a brief summary of non-linear continuum mechanics the weak form of non-linear elastodynamics, its consistent linearization and its finite element discretization are discussed and, in a first step, specialized to one-dimensional spatial truss elements to understand the principles of the formulation of geometrically nonlinear finite elements. In addition, an overview of nonlinear constitutive models including elasto-plastic and damage models is given. The second part of the lecture focuses on algorithms to solve the resulting non-linear equilibrium equations by load- and arc-length controlled Newton-type iteration schemes. Finally, the non-linear finite element method is used for the non-linear stability analysis of structures. The lectures are supplemented by exercises to support the understanding of the underlying theory and to demonstrate the application of the non-linear finite element method for the solution of selected examples. Furthermore, practical applications of the non-linear finite element method are demonstrated by means of a commercial finite element program.

Forms of media: Blackboard, transparencies, beamer presentations

Literature: Manuscript and Lecture notes T. Belytschko and W.K.Liu, Nonlinear Finite Elements for Continua and Structures, Wiley, 2000 O.C. Zienkiewicz, R.L. Taylor, The Finite Element Method for Solid and Structural Mechanics, Elsevier, 2005




Module name: CE-WP05: Computational Fluid Dynamics

Abbreviation, if applicable: CFD


Module Coordinator(s): Prof. Dr. R. Verfürth



Courses included in the module, if applicable: Computational Fluid Dynamics


Lecturer(s): Prof. Dr. R. Verfürth, Assistants

Language: English

Requirements: Basic knowledge of: partial differential equations and their variational formulation, finite element methods, numerical methods for the solution of large linear and non-linear systems of equations


Lectures: 4h per week including approximately 2h exercise per week





90


Homework [h] 30

Credit points: 6




Students should become familiar with modern methods for the numerical solution of complicated flow problems. This includes: finite element and finite volume discretizations, a priori and a posteriori error analysis, adaptivity, advanced solution methods of the discrete problems including particular multigrid techniques

Content:

1st week: Modelization Velocity, Lagrangian / Eulerian representation; transport theorem, Cauchy theorem; conservation of mass, momentum and energy; compressible Navier-Stokes / Euler equations; nonstationary incompressible Navier-Stokes equations; stationary incompressible Navier-Stokes equations; Stokes equations; boundary conditions 2nd week: Notations and auxiliary results Differential operators; Sobolev spaces and their norms; properties of Sobolev spaces; finite element partitions and their properties; finite element spaces; nodal bases 3rd week: FE discretization of the Stokes equations. 1st attempt Stokes equations; variational formulation in {div u = 0}; non-existence of low-order finite element spaces in {div u = 0}; remedies 4th to 5th week: Mixed finite element discretization of the Stokes equations Mixed variational formulation; general structure of finite element approximation; an example of an instable low-order element; inf-sup condition; motivation via linear systems; catalogue of stable elements; error estimates; structure of discrete problem 6th week: Petrov-Galerkin stabilization Idea: consistent penalty term; general structure; catalogue of stabilizations; connection with bubble elements; structure of discrete problem; error estimates; choice of stabilization parameters 7th week: Non-conforming methods Idea; most important example; error estimates; local solenoidal bases 8th week: Streamline formulation Stream function; connection to bi-Laplacian; FE discretizations 9th week Numerical solution of the discrete problems General structure and difficulty; Uzawa algorithm; improved version of Uzawa algorithm; multigrid; conjugate gradient variants 10th week: Adaptivity Aim of a posteriori error estimation and adaptivity; residual estimator; local Stokes problems; choice of refinement zones; refinement rules 11th week: FE discretization of the stationary incompressible Navier-Stokes equations

variational problem; finite elements discretization; error estimates; streamline-diffusion stabilization; upwinding



12th week: Solution of the algebraic equations Newton iteration and its relatives; path tracking; non-linear Galerkin methods; multigrid 13th week: Adaptivity Error estimators; type of estimates; implementation 14th week: Finite element discretization of the instationary incompressible Navier-Stokes equations Variational problem; time-discretization; space discretization; numerical solution; projection schemes; characteristics; adaptivity 14th week: Space-time adaptivity Overview; residual a posteriori error estimator; time adaptivity; space adaptivity 14th week: Discretization of compressible and inviscid problems Systems in divergence form; finite volume schemes; construction of the partitions; relation to finite element methods; construction of numerical fluxes

Forms of media: Blackboard and beamer presentation

Literature: Lecture Notes available online at: http://www.rub.de/num1/files/lectures/CFD.pdf M. Ainsworth, J. T. Oden: A Posteriori Error Estimation in Finite Element Analysis. Wiley, 2000 V. Girault, P.-A. Raviart: Finite Element Approximation of the Navier-Stokes Equations. Computational Methods in Physics, Springer, Berlin, 2nd edition, 1986 R. Glowinski: Finite Element Methods for Incompressible Viscous Flows. Handbook of Numerical Analysis Vol. IX, Elsevier 2003 E. Godlewski, P.-A. Raviart: Numerical Approximation of Hyperbolic Systems of Conservation Laws. Springer, 1996 D. Gunzburger, R. A. Nicolaides: Incompressible CFD - Trends and Advances. Cambridge University Press, 1993 D. Kröner: Numerical Schemes for Conservation Laws. Teubner-Wiley, 1997 R. LeVeque: Finite Volume Methods for Hyperbolic Problems. Springer, 2002 O. Pironneau: Finite Element Methods for Fluids. Wiley, 1989 R. Temam: Navier-Stokes Equations. 3rd edition, North Holland, 1984 R. Verfürth: A Posteriori Error Estimation Techniques for Finite Element Methods. Oxford University Press, Oxford, 2013




Module name: CE-WP06: Finite Element Method for Nonlinear Analyses of Materials and Structures

Abbreviation FEM-III




Master’s Program Computational Engineering: compulsory optional course, 2nd Semester Master’s Program ‘Bauingenieurwesen’: optional course, 2nd Semester


Finite Element Method for Nonlinear Analyses of Inelastic Materials and Structures



Language: English

Requirements: Basic knowledge of tensor analysis, continuum mechanics and linear Finite Element Methods is required; participation in the lecture ,,Advanced Finite Element Methods’’ (CE-WP04) is strongly recommended


Lectures including exercises: 2 h


Project work (implementation of nonlinear material models) and final student presentation within the scope of a seminar (100%)




-


Homework [h] -

Credit points: 3




The goal of the course is to convey to students the ability to formulate and to implement inelastic material models for ductile and brittle materials within the context of the finite element method and to perform nonlinear ultimate load structural analyses.

Contents:

The course is concerned with inelastic material models including their algorithmic formulation and implementation in the framework of nonlinear finite element analyses. Special attention will be paid to efficient algorithms for physically nonlinear structural analyses considering elastoplastic models for metals, soils and concrete as well as damaged based models for brittle materials. As a final assignment, the formulation and implementation of inelastic material models into an existing finite element program and its application to nonlinear structural analyses will be performed in autonomous teamwork by the participants.

Forms of media: Blackboard, Beamer presentations, Computer lab

Literature: Manuscript and handouts J.C. Simo and T.J.R. Hughes, “Computational Inelasticity”, Springer, New York, 1998




Module name: CE-WP08: Numerical Methods and Stochastics

Abbreviation, if applicable: NMS


Module Coordinator(s): Prof. Dr. H. Dehling, Prof. Dr. R. Verfürth



Courses included in the module, if applicable: Numerical Methods and Stochastics


Lecturer(s): Prof. Dr. H. Dehling, Assistants Prof. Dr. R. Verfürth, Assistants

Language: English

Requirements: Basic knowledge of: partial differential equations, numerical methods and stochastics


Lectures: 4h per week including approximately 1h exercises per week





90


Homework [h] 30

Credit points: 6




Students should become familiar with modern numerical and stochastic methods

Content:

Numerical Methods:

Boundary value problems for ordinary differential equations (shooting, difference and finite element methods)

Finite element methods (brief retrospection as a basis for further material)

Efficient solvers (preconditioned conjugate gradient and multigrid algorithms)

Finite volume methods (systems in divergence form, discretization, relation to finite element methods)

Nonlinear optimization (gradient-type methods, derivative-free methods, simulated annealing)

Stochastics:

Fundamental concepts of probability and statistics: (multivariate) densities, extreme value distributions, descriptive statistics, parameter estimation and testing, confidence intervals, goodness of fit tests

Time series analysis: trend and seasonality, ARMA models, spectral density, parameter estimation, prediction

Multivariate statistics: correlation, principal component analysis, factoranalysis

Linear models: multiple linear regression, F-test for linear hypotheses, Analysis of Variance


Literature: To be announced in the first lecture




Module name: CE-WP09: Numerical Simulation in Geotechnics and Tunneling

Abbreviation, if applicable: NSGT


Module Coordinator(s): Prof. Dr. techn. G. Meschke



Courses included in the module, if applicable: Numerical Simulation in Geotechnics and Tunnelling


Lecturer(s): Prof. Dr. techn. G. Meschke, Dr.-Ing. A. A. Lavasan, Assistants

Language: English

Requirements: Fundamental knowledge in soil mechanics and FEM


Lecture: 2 h

Exercise: 2 h

Study/exam achievements: Study work (100 %)




75


Homework [h] 45

Credit points: 6




Acquiring knowledge in fundamentals of the finite element method in the modelling, design and control for geotechnical structures and tunneling problems. The course provides effective methodologies to generate proper models to predict soil-structure interactions by performing nonlinear analysis.

Content: Numerical Simulation in Geotechnics The course gives an overall insight to the numerical simulation of geotechnical and tunneling problems by using the finite element method including constructional details, staged excavation processes and support measures. This encompasses material modeling, discretization in space and time and the evaluation of numerical results. The terms and expressions for creating proper numerical models showing appropriate mesh shapes, boundary and initial conditions are introduced. Different constitutive models with their parameters and potential fields of application for different materials are presented in order to show how accurate results can be obtained. To control the reliability of numerical models, the basics of constitutive parameter calibration, model validation and verification techniques are explained. In connection with the possibilities of 2D and 3D discretization, the basics of invariant model development are explained. To achieve a better understanding of the soil-water interactions in drained, undrained and consolidation analyses, fully coupled hydromechanical finite element solutions are described. Basics of local and global sensitivity analyses are introduced to address the effectiveness of the contributing constitutive parameters as well as constructional aspects within the sub-systems. To perform global sensitivity analyses, which usually requires a vast number of test runs, the meta modeling technique as a method for surrogate model generation is presented. All these methods are consequently applied in the context of a reference case study on a tunneling-related topic. Numerical Simulation in Tunneling This tutorial provides an overview of the most important aspects of realistic numerical simulations of tunnel excavation using the Finite Element Method including staged excavation processes and support measures. This encompasses material modeling, discretization in space and time and the evaluation of numerical results. In the framework of the exercises nonlinear numerical analyses in tunneling will be performed by the participants in autonomous teamwork in the computer lab.

Forms of media: Blackboard and beamer presentations, computer lab

Literature: ChapmanD., Metje,N., StärkA.: Introduction to Tunnel Construction, Spon Press Ltd, New York, 2010. PottsD., AxelssonK., GrandeL., Schweiger H., Long M.: Guidelines for the use of advanced num. analysis, Telford Ltd, London,2002. ChenW.F.: Non-linear Analysis in Soil Mechanics, Elsevier,1990. Muir Wood, D.: Soil Behaviour and Critical State Soil Mechanics, Cambridge University Press, 1990. Handouts and lecture notes




Module name: CE-WP10: Object-oriented Modelling and Implementation of Structural Analysis Software

Abbreviation: OOFEM

Sub-heading, if applicable:

-



Master’s Program Computational Engineering: compulsory optional course, 2nd Semester

Courses included in the module, if applicable: -


Lecturer(s): Prof. Dr.-Ing. M. Baitsch, Assistants

Language: English

Requirements: Finite Element Methods in Linear Structural Mechanics and Modern Programming Concepts in Engineering


Block seminar / equiv. to 2h lecture

Study/exam achievements: Study project and oral examination


Thereof face-to-face teaching [h]

30


-


Homework [h] 30

Credit points: 3




The main goal of the seminar is to enable students to implement the theories and methods taught in ‘Finite Element Methods in Linear Structural Mechanics’ in an object-oriented finite element program for the analysis of engineering structures.

Content:

The seminar links the theory of finite element methods with object-oriented programming in the sense that the finite element theory is applied within a finite element program developed by the students. In order to gain insights into both topics – object-oriented programming and finite element theory – students implement an object-oriented finite element program for the analysis of spatial truss structures. This combination of the theory of numerical methods with object-oriented programming provides an inspiring basis for the successful study of computational engineering. In the lecture, the fundamentals of the finite element method and object-oriented programming are briefly summarized. The programming part of the course comprises two parts. In the first part, the topic is fixed: Students individually develop an object-oriented finite element program for the linear analysis of spatial truss structures. The program is verified by means of the static analysis of a representative benchmark and afterwards applied for the numerical analysis of an individually designed spatial truss structure. In the second part, students can choose between different options. Either, the application developed in the first part is extended to more challenging problems (nonlinear analysis, other element types, etc.) or students switch to an existing object-oriented finite element package (e.g. Kratos) and develop an extension of that software.

Forms of media: Beamer presentations, blackboard, computer pool work

Literature: M. Baitsch, D. Kuhl, Object-Oriented Modeling and Implementation of Structural Analysis Software, Seminar Notes, 2006

C.S. Horstmann, G. Cornell, Core Java. Volume I – Fundamentals, Prentice Hall, 2001 O.C. Zienkiewicz, R.L. Taylor, The Finite Element Method ITS Basis and Fundamentals, Elsevier Science & Technology, 2005 T. Anderson, A Quick Introduction to C++, http://homes.cs.washington.edu/~tom/c++example/c++.pdf P. Dadvand, A framework for developing finite element codes for multi-disciplinary applications. Phd thesis. 4/2007. B. Stroustrup, The Design and Evolution of C++, Addison-Wesley, 5/1994.




Module name: CE-WP11: Dynamics of Structures

Abbrevation, if applicable: DoS


Module Coordinator(s): Prof. Dr.-Ing. R. Höffer, Prof. Dr. techn. G. Meschke


Master’s Program Computational Engineering: compulsory optional course, 3rd Semester Master’s Program ‘Bauingenieurwesen’: optional course, 3rd Semester


- Structural basics of structural dynamics

- Linear computational dynamics

Semester/ term: 3rd Semester, Winter term

Lecturer(s): Prof. Dr.-Ing. R. Höffer, Prof. Dr. techn. G. Meschke, Assistants

Language: English

Requirements: Finite Element Methods in Linear Structural Mechanics (CE-P05)

Recommended: Dynamics and Adaptronics (CE-WP03)

Teaching format/ class hours per week during the semester:

Lectures: 2h

Exercises: 2h

Study/ exam achievements: Written examination for the total module / 120 minutes

Workload [h/ LP]: 180 / 6

Therefore face-to-face teaching [h]: 60

Preparation and post processing (including examination) [h]:

60

Seminar papers [h]: Course-related, connected seminar papers, individual or group work upon agreement with the lecturers: 60 h.

Homework [h]: -

Credit points: 6



Learning goals/ competences:

The ability to create suitable structural models for dynamically excited structures and to perform dynamic structural analyses through engineering calculations, especially using the Finite Element Method, in time and frequency domains.

Content:

Part I: Basics of Structural Dynamics

Modelling of structures as single- and multi-degree-of-freedom systems

Statistical description of random vibrations Spectral method for stationary broad-banded excitation

mechanisms, especially for wind excitation Response spectrum method for earthquake loading

Part II: Linear Computational Structural Dynamics

Basics of linear Elastodynamics and Finite Element Methods in Structural Dynamics

Explicit and implicit integration methods with emphasis on generalized Newmark-methods

Accuracy, stability and numerical dissipation Overview on Finite Element Methods for modal analyses Computer lab: Implementation of algorithms into Finite

Element programs Homework: Dynamic analysis of a structural system. The results of the project have to be summarized in a poster and a presentation.

Format of media: Blackboard Beamer presentations, Computer lab, internet computing

Literature: Lecture notes D. Thorby, „Structural Dynamics and Vibrations in Practice –

An Engineering Handbook“, Elsevier, 2008. R.W. Clough, J. Penzien, „Dynamics of Structures“, McGraw-

Hill Inc., New York, 1993 K. Meskouris, „Structural Dynamics“, Ernst & Sohn, 2000. OC. Zienkiewicz, R. L. Taylor, ,,The Finite Element Method’’,

Vol. 1, Butterworth-Heinemann, 2000. T.J.R. Hughes, “Analysis of Transient Algorithms with

Particular Reference to Stability Behavior”, in T. Belytschko

and T.J.R. Hughes “Computational Methods for Transient

Analysis”, North-Holland, Amsterdam, 1983




Module name: CE-WP12: Computational Plasticity

Abbreviation, if applicable: -




Master’s Program Computational Engineering: compulsory optional course, 3rd Semester Master course “Maschinenbau”: optional course, 2nd Semester.

Courses included in the module, if applicable: Computational Plasticity

Semester/term: 3rd Semester / Winter term

Lecturer(s): Dr.-Ing. U. Hoppe

Language: English

Requirements: Basic knowledge of continuum mechanics (CE-P07) is required.


Lectures including exercises: 3h





75


Homework [h] -

Credit points: 4




Fundamentals of the computational modeling of inelastic materials with emphasis on rate independent plasticity. A sound basis for approximation methods and the finite element method. Understanding of different methodologies for the discretization of time evolution problems, and rate independent elasto-plasticity in particular.

Content:

Introduction: Physical Motivation. Rate Independent Plasticity. Rate Dependence. Creep. Rheological Models. 1-D Mathematical Model: Yield Criterion. Flow Rule. Loading / Unloading Conditions. Isotropic and Kinematic Hardening Models. Computational Aspects of 1-D Elasto-Plasticity: Integration Algorithms for 1-D Elasto-Plasticity. Operator Split. Return Mapping. Incremental Elasto-Plastic BVP. Consistent Tangent Modulus. Classical Model of Elasto-Plasticity: Physical Motivation. Classical Mathematical Model of Rate-Independent. Elasto-Plasticity: Yield Criterion. Flow Rule. Loading / Unloading Conditions. Computational Aspects of Elasto-Plasticity: Integration Algorithms for Elasto-Plasticity. Operator Split. The Trial Elastic State. Return Mapping. Incremental Elasto-Plastic BVP. Consistent Tangent Modulus. Integration Algorithms for Generalized Elasto-Plasticity: Stress Integration Algorithm. Computational Aspects of Large Strain Elasto-Plasticity: Multiplicative Elasto-Plastic Split. Yield Criterion. Flow Rule. Isotropic Hardening Operator Split. Return Mapping. Exponential Map. Incremental Elasto-Plastic BVP.

Forms of media: Lecture: Blackboard and beamer presentations Programming Exercises: Computer Lab

Literature: Lecture notes M.A. Crisfield: Basic plasticity Chapter 5. in: Non-linear Finite Element Analysis of Solids and Structures. Volume1: Essentials, John Wiley, Chichester, 1991 J. C. Simo and T. J. R. Hughes, Computational Inelasticity, Springer, 1998 F. Dunne, N. Petrinic, Introduction to Computational Plasticity, Oxford University Press, 2005 E.A. de Souza Neto, D. Peric, D.R.J. Owen, Computational Methods for Plasticity: Theory and Applications, Wiley, 2008




Module name: CE-WP13: Advanced Control Methods for Adaptive

Mechanical Systems

Abbreviation, if applicable: ACMAMS


Module Coordinator(s): Prof. Dr.-Ing. T. Nestorović


Master’s Program Computational Engineering: compulsory optional course, 3rd Semester This course is not offered in any other study program.

Courses included in the module, if applicable: Advanced Control Theory, Structural Control


Lecturer(s): Prof. Dr.-Ing. T. Nestorović, Assistants

Language: English

Requirements:

Dynamics and Adaptronics (WP-WP03)

Control theory, structural control

This course is recommended for the students planning to attend the course Structural Health Monitoring (CE-WP27)




- Written examination / 120 minutes (70%) - Seminar paper (30%)




60


Homework [h] 15

Credit points: 6




Extended knowledge in adaptive mechanical systems, advanced control methods and their application for the active control of structures.

Content:

Advanced methods for the control of adaptive mechanical systems are introduced in the course. This involves the recapitulation of the fundamentals of active structural control and an extension to advanced control. Observer design is introduced as a tool for the estimation of system states. In addition to numerical modelling using the finite element approach, system identification is explained as an experimental approach. Theoretical backgrounds of the experimental structural modal analysis are introduced along with the terms and definitions used in signal processing. Experimental modal analysis is explained using the Fast Fourier Transform. Advanced closed loop control methods involving optimal discrete-time control, introduction of additional dynamic approaches for the compensation of periodic excitations and basic adaptive control algorithms are explained and pragmatically applied for solving problems of vibration suppression in civil and mechanical engineering.

Forms of media: Blackboard and beamer presentations, computer exercises, practical experimental exercises

Literature: Preumont A.: Vibration Control of Active Structures: An Introduction, Kluwer Academic Publishers, Dordrecht, Boston, London, 1997 Vaccaro R. J.: Digital Control: A State-Space Approach, McGraw-Hill, Inc., 1995 Van Overschee P., De Moor B.: Subspace Identification for Linear Systems: Theory, Implementation, Applications, Kluwer Academic Publishers, Boston 1996 Meirovitch L.: Dynamics and control of structures, Wiley 1990 Lecture notes Advanced control methods for adaptive mechanical systems, T. Nestorović




Module name: CE-WP14: Computational Wind Engineering

Abbreviation, if applicable: CWE


Module Coordinator(s): Prof. Dr.-Ing. R. Höffer



Courses included in the module, if applicable: Computational Wind Engineering


Lecturer(s): Prof. Dr.-Ing. R. Höffer, Dipl.-Ing. U. Winkelmann

Language: English

Requirements: Modern Programming Concepts in Engineering (CE-P04)

Fluid Dynamics (CE-P06)

Recommended: Computational Fluid Dynamics (CE-WP05)







60


Homework [h] -

Credit points: 3




The students acquire advanced skills of CFD methods for the computation of wind engineering problems such as mean wind parameters and turbulence characteristics for the

assessment of local wind climates (incl. wind farm locations), wind pressures at surfaces for the determination of wind loads

at structures, and gaseous transport in the atmospheric boundary layer for the

prediction of the dispersion of exhausts and particles The students shall be enabled to assess the available numerical tools and to solve the relevant technical problems by choosing the appropriate CFD method.

Content:

This course introduces the details and guidelines for the application of CFD methods in the field of wind engineering. Relevant problems for practical applications and solution procedures are investigated. The theoretical background is taught in the obligatory Fluid Dynamics course while this course aims at the practical application of CFD methods on various wind engineering problems. In general, the steady state RANS approach and the time dependent LES approach are used. The lectures and exercises include all necessary steps of a CFD simulation ranging from the creation of the geometry of the problem to the assessment and presentation of the results. During the semester the commercial software package ANSYS CFX and the open source software OpenFOAM are used. The following working steps are explained and carried out:

Generation of simple geometries and block structured grids and analysis of the influence of the quality of the mesh on the results of the simulation.

Generation of complex geometries and unstructured numerical grids.

Setting up simulations (Pre-Processing): - ◦ Choosing the right boundary conditions. ◦ Choosing the correct turbulence models. ◦ Deciding on the parameters of the finite volume method

such as interpolation schemes for the convective term of the Navier-Stokes equation.

◦ Adding source terms of exhaust for the investigation of pollution in the atmosphere.

Application of the numerical solvers including parallel processing.

Post processing of the most important characteristics of wind engineering flows and presenting them in an adequate manner: ◦ Analysis of mean velocity vector fields around structures. ◦ Analysis of mean and time dependent pressure

distributions on the surface of structures that are exposed to wind to estimate the load due to wind.

◦ Analysis of the aerodynamic forces of lift and drag.



◦ Gaseous transport and dispersion in the atmospheric boundary layer for the prediction of the dispersion of exhausts and particles.

Procedures for quality assurance in CFD simulations -Validation and verification methods.

Forms of media: Blackboard, beamer, visit to CIP-Pool and guided introduction to program systems; exercises with examples

Literature: Versteeg, H.K., Malalasekera, W., 2007. An Introduction to Computational Fluid Dynamics, 2nd Edition. ed. Harlow. https://doi.org/10.2514/1.22547 Ferziger, J.H., Peric, M., 2002. Computational methods for fluid dynamics, 3rd Edition. ed. Springer-Verlag




Module name: CE-WP15: Design Optimization

Abbreviation, if appli-cable: DO

Sub-heading, if appli-cable: -



Master’s Program Computational Engineering: compulsory optional course, 3rd Semester

Courses included in the module, if applicable: Design Optimization


Lecturer(s): Prof. Dr.-Ing. M. König, Dr.-Ing. K. Lehner, Assistants

Language: English

Requirements: -



Study/exam achievements: Homework (Presentation) -100%




120


Homework [h] -

Credit points: 6




Goals are the acquisition of skills in design optimization and the ability to model, solve and evaluate optimization problems for moderately complex technical systems. The programming project increases the social skills that are necessary to successfully complete a team project. Also, the programming project allows students to transfer theoretical knowledge gained from the lecture into practical solutions solved with software.

Content:

Introduction: Definition of optimization problems

Design as a process: Conventional design, optimization as a design tool

Optimization from a mathematical viewpoint: Numerical approaches, linear optimization, convex domains, partitioned domains

Categories of opt. variables: Explicit design variables, synthesis and analysis, discrete and continuous variables, shape variables

Dependant design variables

Realization of constraints: Explicit and implicit constraints, constraint transformation, equality constraints

Optimization criterion: Objectives in structural engineering

Application of design optimization in structural engineering: trusses and beams, framed structures, plates and shells, mixed structures

Solution techniques: Direct and indirect methods, gradients, Hessian Matrix, Kuhn-Trucker conditions

Team Programming Project in Design Optimization (seminar paper)

Forms of media: PowerPoint slides, animations, black board usage.

Literature: Lecture notes in German and English, available online „Design“ by J. Arora, Mc GrawHill




Module name: CE-WP16: Parallel Computing

Abbreviation, if applicable: PC




Master’s Program Computational Engineering: compulsory optional course, 2nd Semester

Courses included in the module, if applicable: Parallel Computing


Lecturer(s): Prof. Dr.-Ing. M. König , Dr.-Ing. K. Lehner, Assistants

Language: English

Requirements: Modern Programming Concepts in Engineering



Study/exam achievements: Homework (Presentation) - 100%




-


Homework [h] 120

Credit points: 6




The goal is the acquisition of knowledge and skills of constructing parallel algorithms, and of implementing parallel computational methods of engineering practice on various contemporary parallel computers.

Content:

* Introduction to parallel computing o Examples of simple parallel computational problems

* Concepts of parallel computing o Levels of parallelism o Interconnection networks o Parallel computer architectures o Operating systems o Interaction of parallel processes o Parallel programming with shared memory and

distributed memory * Performance of parallel computing: speedup, efficiency, redundancy, utilization * Parallel programming for shared memory using the programming interfaces OpenMP in Fortran and C/C++, and JOMP in Java * Parallel programming for distributed memory with the programming interfaces MPI in Fortran and C/C++, and mpiJava in Java

Forms of media: PowerPoint-presentations, for students available on the internet (Blackboard), classroom board and overhead

Literature: A. Jennings, Matrix Computation for Engineers and Scientists, J. Wiley and Sons, Chichester, England, 1977. M. Papadrakakis (Editor), Solving Large Scale Problems in chanics, J. Wiley and Sons, Chichester, England, 1993. OpenMP Application Program Interface, Version 2.5, ©1997 – 2005, OpenMP Architecture Review Board, May 2005. OpenMP Application Program Interface, Version 3.0, ©1997 – 2008, OpenMP Architecture Review Board, May 2008. J.M. Bull, M.E. Kambites, JOMP – an OpenMP-like Interface for Java, Edinburgh Parallel Computing Centre (EPCC), University of Edinburgh, Mayfield Road, Edinburgh EH9 3JZ, Scotland, U.K., 2000. ([email protected]) M. Snir, S. Otto, S. Huss-Lederman, D. Walker, and J. Dongarra, MPI: The Complete Reference, The MIT Press, Cambridge, Massachusetts, London, England, 1996. Carpenter, B., Fox, G., Ko, S.-M., Lim S., mpiJava 1.2: API specification, Northeast Parallel Architectures Center, Syracuse University, Syracuse, New York 13244-410, 2000. {debc, gcf, shko, slim}npac.syr.edu




Module name: CE-WP17: Adaptive Finite Element Methods

Abbreviation, if applicable: AFEM


Module Coordinator(s): Prof. Dr. R. Verfürth



Courses included in the module, if applicable: Adaptive Finite Element Methods


Lecturer(s): N.N. (Faculty of Mathematics)

Language: English

Requirements: Basic knowledge of: partial differential equations and their variational formulation, finite element methods, numerical methods for the solution of large linear and non-linear systems of equations







90


Homework [h] 30

Credit points: 6




Students should become familiar with advanced finite element methods for the numerical solution of differential equations and of advanced solution techniques for the resulting discrete problems in particular multigrid techniques

Content:

1st week: Introduction Need for efficient solvers; drawbacks of classical solvers; need for error estimation; drawbacks of classical a priori error estimates; need for adaptivity; outline 2nd week – 4th week: Notation Model differential equations; variational formulation; Sobolev spaces, their norms and properties; finite element partitions and basic assumptions; finite element spaces; review of most important examples; review of a priori error estimates 5th – 6th week: Basic a posteriori error estimates Equivalence of error and residual; representation of the residual; upper bounds on the residual; lower bounds on the residual; local and global bounds; review of general structure; application to particular examples 7th week: A catalogue of error estimators Residual estimator; estimators based on local problems with prescribed traction; estimators based on local problems with prescribed displacement: hierarchical estimates; estimators based on recovery techniques; equilibrated residuals; comparison of estimators 8th week: Mesh adaptation General structure of adaptive algorithms; marking strategies; subdivision of elements; avoiding hanging node; convergence of adaptive algorithms 9th -10th week: Data structures Local and global enumeration of elements and nodes; enumeration of edges and faces; neighbourhood relation; hierarchy of grids; refinement types; derived structures for higher order elements and for matrix assembly 11th – 12th week: Stationary iterative solvers Review of classical methods and of their drawbacks; taking advantage of adaptivity; conjugate gradients; need for preconditioning; suitable preconditioners 13th – 14th week: Multigrid methods Why do classical methods fail; spectral decomposition of errors and consequences for iterative solutions; multigrid idea; generic structure of multigrid algorithms; basic ingredients of multigrid algorithms; role of smoothers; examples of suitable smoothers




Literature: Lecture Notes are available online at: http://www.rub.de/num1/files/lectures/AdaptiveFEM.pdf M. Ainsworth, J. T. Oden: A Posteriori Error Estimation in Finite Element Analysis. Wiley, 2000 D. Braess: Finite elements: Theory, Fast Solvers and Applications in Solid Mechanics. Cambridge University Press, 2001 R. Verfürth: A Posteriori Error Estimation Techniques for Finite Element Methods. Oxford University Press, Oxford, 2013 R. Verfürth: A review of a posteriori error estimation techniques for elasticity problems. Comput. Meth. Appl. Mech. Engrg. 176, 419 – 440 (1999) ALF demo applet and user guide (http://www.rub.de/num1/demoappletsE.html)




Module name: CE-WP18: Safety and Reliability of Engineering Structures

Abbreviation, if applicable: SRES


Module Coordinator(s): PD Dr.-Ing. M. Kasperski


Master’s Program Computational Engineering: compulsory optional course, 3rd Semester Master’s Program ‘Bauingenieurwesen’: optional course, 3rd Semester

Courses included in the module, if applicable: Safety and Reliability of Engineering Structures

Semester/term: 3rd Semester, Winter term

Lecturer(s): PD Dr.-Ing. M. Kasperski

Language: English

Requirements: Basic knowledge in structural engineering


- 2 hours per week lecture

- 2 hours per week exercise


- Written examination / 120 minutes (85%)

- Project work on simulation techniques (15%)




75


Homework [h] 45

Credit points: 6




Students should obtain the following qualifications / competences: Basic knowledge of statistics and probability, a deeper understanding of the basic principles of reliability analysis in structural engineering, basic knowledge on how codes try to meet the reliability demands in regard to structural safety and serviceability, basic knowledge in simulation techniques.

Content:

Introduction - causes of failures

Basic definitions - safety, reliability, probability, risk

Basic demands for the design and appropriate target reliability values: Structural safety, Serviceability, Durability, Robustness

Formulation of the basic design problem: R > E

Descriptive statistics: position (mean value, median value), dispersion (range, standard deviation, variation coefficient), shape: (skewness, peakedness)

Theoretical distributions: Discrete distributions (Bernoulli and Poisson Distribution), Continuous distributions (Rectangular, Triangular, Beta, Normal, Log-Normal, Exponential, Extreme Value Distributions)

Failure probability and basic design concept

Code concept - level 1 approach

First Order Reliability Method (FORM) - level 2 approach

Full reliability analysis - level 3 approach

Probabilistic models for actions: dead load, imposed loads, snow and wind loads, combination of loads

Probabilistic models for resistance: cross section - structure

Further basic variables: geometry, model uncertainties

Non-linear methods and Monte-Carlo Simulation

Forms of media: Blackboard and overhead

Literature: Melchers, R.E. Structural reliability, analysis and prediction J. Wiley & Sons, New York, 1999 (2nd ed.), ISBN 0471983241




Module name: CE-WP19: Computational Fracture Mechanics

Abbreviation, if applicable: CFM


Module Coordinator(s): Prof. Dr.-Ing. A. Hartmaier


Master’s Program Computational Engineering: compulsory optional course, 3rd Semester Master’s Program “Maschinenbau”: optional course, 2nd Semester Master’s Program “Materials Science and Simulation”: optional course, 3rd Semester

Courses included in the module, if applicable: Computational Fracture Mechanics


Lecturer(s): Prof. Dr.-Ing. A. Hartmaier, Assistants

Language: English

Requirements: Mechanical Modeling of Materials (CE-P02)

Finite Element Methods in Linear Structural Mechanics (CE-P05)



Study/exam achievements: Written examination / 120 minutes (100%)




60


Homework [h] 60

Credit points: 6




The students attain the ability to independently simulate fracture including plasticity for a wide range of materials and geometries. Based on the acquired understanding of the different types of brittle fracture and ductile failure of materials, they are enabled to choose appropriate fracture models and to implement them in a finite element environment. They gain sufficient knowledge about the theoretical background of the different types of fracture models, to study the relevant literature independently. On an engineering level, the students are able to discriminate between situations, where cracks in a structure or component can be tolerated or under which conditions cracks are not admissible, respectively.

Content:

Phenomenology of fracture/Fracture on the atomic scale

Concepts of linear elastic fracture mechanics

Concepts of elastic-plastic fracture mechanics

R curve behavior of materials

Concepts of cohesive zones (CZ), extended finite elements (XFEM) and damage mechanics

Finite element based fracture simulations for static and dynamic cracks

Application to brittle fracture & ductile failure for different geometries and loading situations

Forms of media: Personal computer, blackboard, beamer presentations

Literature: H.L. Ewalds and R.J.H. Wanhill, „Fracture Mechanics”, Edward Arnold Ltd, 1984, ISBN 0713135158 D. Gross, T. Seelig, „Bruchmechanik“, Springer, 2001, ISBN 3-540-42203 T. L. Anderson, „Fracture Mechanics: Fundamentals and Applications”, CRC PR Inc., 2005, ISBN 0849316561




Module name: CE-WP20: Materials for Aerospace Applications

Abbreviation, if applicable: MAA




Master’s Program Computational Engineering: compulsory optional course, 3rd Semester Master’s Program ‘Maschinenbau’: optional course, 2nd Semester.

Courses included in the module, if applicable: Materials for Aerospace Application

Semester/term: 3rd Semester/ Winter term

Lecturer(s): Prof. Dr.-Ing. M. Bartsch, Assistans

Language: English

Requirements: -



Study/exam achievements: Written examination / 120 minutes (100%)




120


Homework [h] -

Credit points: 6




Learning goals:

Students will gain a comprehensive overview of high performance materials for aerospace applications, which includes the established materials and material systems as well as new developments and visionary concepts. They understand how materials and material systems are designed to be ‘light and reliable’ under extreme service conditions such as fatigue loading, high temperatures, and harsh environments. The students will know about degradation and damage mechanisms and learn how characterization and testing methods are used for qualifying materials and joints for aerospace applications. They learn about concepts and methods for lifetime assessment.

Competences:

General understanding of procedures in selecting and developing material systems for aerospace applications; overview of manufacturing technologies and characterization methods for qualifying materials and joints for aerospace applications; understanding of methods for the evaluation of material systems for aerospace applications

Content:

The substantial requirements on materials for aerospace applications are „light and reliable“, which have to be fulfilled in most cases under extreme service conditions. Therefore, specifically designed materials and material systems are in use. Furthermore, joining technologies play an important role for the weight reduction and reliability of the components. Manufacturing technologies and characterization methods for qualifying materials and joints for aerospace applications will be discussed. Topics are: Loading conditions for components of air- and spacecrafts

(structures and engines) Development of materials and material systems for specific

service conditions in aerospace applications (e.g. for aero-engines, rocket engines, thermal protection shields for reentry vehicles, light weight structures for airframes, wings, and satellites)

Degradation and damage mechanisms of aerospace material systems under service conditions

Characterization and testing methods for materials and joints for aerospace applications

Concepts and methods for lifetime assessment


Literature: script




Module name: CE-WP24: Case Study A



Module Coordinator(s): All lecturers of the course


Master’s Program Computational Engineering: compulsory optional course, 2nd or 3rd Semester


Semester/term: 2nd Semester / Summer term or 3rd Semester / Winter term

Lecturer(s): Professors and Assistants of the program

Language: English

Requirements: -


The topic of a project paper is devised by a lecturer of the course or an assistant who supervises the exercises. The student - or a small group of students - conducts a project independently and presents the results in the form of a written report and optionally, an oral presentation (upon agreement with the respective lecturer).


The project paper and presentation will be graded. For this purpose, the individual achievements of the students within the project groups are separately evaluated. The evaluation includes: - Written project paper / 75% (100% without a final presentation) - Final presentation / 25% (optional)

Forms of media: Independent work in seminar rooms and computer labs; testing plants, where applicable.


Thereof face-to-face teaching [h] -


-

Credit points: 3




Project work allows students to work on a problem individually or in small groups. Project groups organize and Coordinate the assignment of tasks independently, while the lecturers take the role of both an advisor and supervisor of the respective project. Further, they check the students’ results at regular intervals. After completion of the project, the students should present their results before the class. The necessity of such a presentation should, however, be agreed upon with the respective supervisor. Project work serves to qualify students to structure Computational Engineering problems, to solving them in teams, and to illustrate the results in the form of a report and a presentation. After completion of the project, the students should have gathered new information and insights into the activities of practicing engineers while acquiring skills in innovative research fields. In the end, the students will be able to present technical projects, and to develop problem solution strategies and will hence also obtain worthwhile communication skills.

Contents:

The project topic is usually determined by the respective lecturer or one of his/her assistants. In addition to this, students may also conduct project work on topics defined by companies from industry or official authorities. However, the project work must be completed under the supervision of one of the course’s lecturers. The projects are usually devised so as to integrate interdisciplinary aspects such as

o Noticing problems and describing them o Formulating envisaged goals o Team-oriented problem solutions o Organizing and optimizing one's time and work plan o Interdisciplinary problem solutions o Literature research and evaluation as well as the consultation

of experts o Documentation, illustration and presentation of results

Literature: The relevant literature will be announced along with the project topic.



Study Course: Master’s Program Computational Engineering

Module name: CE-WP25: High-Performance Computing on Multi- and Manycore Processors

Abbreviation, if applicable: HPCM


Module co-ordinator(s): Jun.-Prof. Dr. Andreas Vogel


Master’s Course Computational Engineering: compulsory optional course

Courses included in the module, if applicable: High-Performance Computing on Multi- and Manycore Processors

Semester/term: 2nd Semester, summer term

Lecturer: Jun.-Prof. Dr. Andreas Vogel

Language: English

Requirements: -


Lecture: 2 h

Exercise: 2 h

Examination: Homework (Presentation) - 100%

Workload [h / CP]: 180 h / 6


60


-


Homework [h] 120

Credit Points: 6



Learning Goals / Professional Skills:

In this module, the students acquire professional skills to program multi- and manycore processors employing multi-threaded execution and handling shared-memory access patterns. Theoretical properties are conveyed as well as practical implementation. Via presentations of selected topics, students attain the ability to survey and acquire knowledge on advanced scientific topics independently and are qualified to illustrate such topics in the form of a presentation and numerical examples.

Content:

The lecture addresses parallelization for multi- and manycore processors. Thread-based programming concepts (pthreads, C++11 threads, OpenMP, OpenCL) are introduced and best-practice implementation aspects are highlighted based on applications from scientific computing.

In the first part, the lecture provides an overview on relevant data structures, solver techniques and programming patterns from scientific computing. An introduction to multi-threading programming on multicore systems is then provided with special attention to shared-memory aspects. Parallelization patterns are discussed and highlighted. Numerical experiments and self-developed software implementations are used to discuss and illustrate the presented content.

In the second part, students are assigned advanced topics for shared-memory computation from the engineering science including finite element methods and artificial intelligence. Based on a scientific paper, students present their topic to the lecture audience in form of a beamer presentation and numerical illustrations.

Media Formats: Beamers, computer lab, numerical experiments

Literature: G. Hager, G. Wellein, Introduction to High Performance Computing for Scientists and Engineers, CRC Press, 2010

T. Rauber, G. Rünger, Parallel Programming: for Multicore and Cluster Systems, Springer, 2013

OpenMP Application Programming Interface (2015), www.openmp.org/wp-content/uploads/openmp-4.5.pdf

OpenCL Appilication Programming Interface (2014), www.khronos.org/registry/OpenCL/specs/opencl-1.2.pdf

(additional literature will be announced in the lecture)




Module name: CE-WP26: High-Performance Computing on Clusters

Abbreviation, if applicable: HPCC


Module co-ordinator(s): Jun.-Prof. Dr. A. Vogel


Master’s Course Computational Engineering: compulsory optional course

Courses included in the module, if applicable: High-Performance Computing on Clusters



Language: English

Requirements: -


Lecture: 2 h

Exercise: 2 h

Examination: Written examination / 120 Minutes



60


120


Homework [h] -

Credit Points: 6


In this module, the students acquire professional skills to program and employ parallel computing clusters. Theoretical properties of



distributed-memory systems and programming patterns are conveyed as well as the practical implementation.

Content:

The lecture deals with the parallelization on cluster computers. Distributed-memory programming concepts (MPI) are introduced and best-practice implementation is presented based on applications from scientific computing including the finite element method and machine learning.

Special attention is paid to scalable solvers for systems of equations on distributed-memory systems, focusing on iterative schemes such as simple splitting methods (Richardson, Jacobi, Gauß-Seidel, SOR), Krylov-methods (Gradient descent, CG, BiCGStab) and, in particular, the multigrid method. The mathematical foundations for iterative solvers are reviewed, suitable object-oriented interface structures are developed and an implementation of these solvers for modern parallel computer architectures is developed.

Numerical experiments and self-developed software implementations are used to discuss and illustrate the theoretical results.

Media Formats: Beamer, computer lab, numerical experiments

Literature: W. Hackbusch, Iterative Solution of Large Sparse Systems of Equations, Springer, 1994

Y. Saad, Iterative Methods for Sparse Linear Systems, SIAM, 2003

MPI Application Programming Interface (2015), www.mpi-forum.org/docs/mpi-3.1/mpi31-report.pdf

W. Gropp, E. Lusk, A. Skjellum, Using MPI, MIT Press, 2014

S. Snir, S. Otto. S. Huss-Lederman, D. Walker, J. Dongarra, MPI – The Complete Reference, MIT Press, 1998

T. Rauber, G. Rünger, Parallel Programming: for Multicore and Cluster Systems, Springer, 2013

C. Douglas, G. Haase, U. Langer, A Tutorial on Elliptic PDE Solvers and Their Parallelization, SIAM, 2003





Module name: CE-WP28: Machine Learning: Supervised Methods



Module Coordinator(s): Prof. Dr. Tobias Glasmachers


Master’s Program Computational Engineering: compulsory course, 2nd semester

Courses included in the module, if applicable: Machine Learning: Supervised Methods


Lecturer(s): Prof. Dr. Tobias Glasmachers, Assistants

Language: English

Requirements: The course requires basic mathematical tools from linear algebra, calculus, and probability theory. More advanced mathematical material will be introduced as needed. The practical sessions involve programming exercises in Python. Participants need basic programming experience. They are expected to bring their own devices (laptops).


The course applies a flipped classroom format. The sessions plan is largely based on the following caltech lectures: http://work.caltech.edu/telecourse.html

Study/exam achievements: Written Examination / 90 minutes




80


Homework [h] 40

Credit points: 6




The participants understand statistical learning theory. They have basic experience with machine learning software, and they know how to work with data for supervised learning. They are able to apply this knowledge to new problems and data sets.

Content:

The field of machine learning constitutes a modern approach to artificial intelligence. It is situated in between computer science, neuroscience, statistics, and robotics, with applications ranging all over science and engineering, medicine, economics, etc. Machine learning algorithms automate the process of learning, thus allowing prediction and decision making machines to improve with experience. This lecture will cover a contemporary spectrum of supervised learning methods. All lecture material will be in English. The course will use the flipped classroom concept. Students work through the relevant lecture material at home. The material is then consolidated in a 4 hours/week practical session.

Forms of media: Video lectures, ipython notebooks

Literature: Yaser S. Abu-Mostafa, Learning from Data



Optional Courses

CE-W01 – CE-W08




Module name: CE-W01: Training of Competences (Part 1)



Module Coordinator(s): University Language Center (ZFA) of Ruhr-University Bochum


Master’s Program Computational Engineering: optional course, special offer for foreign students of the course.

Courses included in the module, if applicable: German Language course for beginners, Training of Competences


Advisor: Lecturers of ZFA

Language: German (as foreign language)

Requirements: -







40


Homework [h] 20

Credit points: 4




The learning goals of this German language course fulfill the special requirements of foreign students majoring in a subject that uses English as a teaching language. The main focus of the course lies on action oriented speaking, listening, reading and writing comprehension so that the students manage more easily to cope with everyday situations of their life in Germany. With this course students reach a minimum level of all four skills (speaking, listening, reading and writing) in familiar universal contexts or shared knowledge situations such as greeting, small talk, shopping, making appointments, eating out, orientation, biography, healthcare etc. The classes consist of small groups, ensuring that students have ample opportunity to speak as well as having their individual needs attended to. All of our instructors are university graduates experienced in teaching DaF (Deutsch als Fremdsprache - German as a foreign language) and have been selected for their experience in working with students and their ability to make language learning an active and rewarding process. An optional intensive block course after the winter semester helps to activate and to intensify the newly acquired language skills.




Module name: CE-W02: Training of Competences (Part 2)



Module Coordinator(s): University Language Center (ZFA) of Ruhr-University Bochum


Master’s Program Computational Engineering: optional course, special offer for foreign students of the course.


German Language course (higher level), Training of Competences (higher order)


Advisor: Lecturers of ZFA

Language: German (as foreign language)

Requirements: Participation on CE-W01 is obligatory.







40


Homework [h] 20

Credit points: 4


This module is for students who already have previous knowledge of the German language. This course continues the learning goals of module CE-W01. With the participation, the students reach a medium level of all four skills (speaking, listening, reading and writing).




Module name: CE-W03: Case Study B



Module Coordinator(s): All lecturers of the course


Master’s Program Computational Engineering: optional course.


Semester/term: 2nd Semester / Summer term or 3rd Semester / Winter term

Lecturer(s): Professors and Assistants of the course

Language: English

Requirements: -


The topic of a project paper is formulated by a lecturer of the course or an assistant who supervises the exercises. The student - or a small group of students - conducts a project independently and presents the results in the form of a written report and optionally, an oral presentation (upon agreement with the respective lecturer).


The project paper and presentation will be graded. For this purpose, the individual achievements of the students within the project groups are separately evaluated. The evaluation includes: - Written project paper / 75% (100% without a final presentation) - Final presentation / 25% (optional)

Forms of media: Independent work in seminar rooms and computer labs; testing plants, where applicable.


Thereof face-to-face teaching [h] -


-

Credit points: 3




Project work allows students to work on a problem individually or in small groups. Project groups organize and Coordinate the assignment of tasks independently, while the lecturers take the role of both an advisor and supervisor of the respective project. Further, they check the students’ results at regular intervals. After completion of the project, the students should present their results before the class. The necessity of such a presentation should, however, be agreed upon with the respective supervisor. Project work serves to qualify students to structure Computational Engineering problems, to solving them in teams, and to illustrate the results in the form of a report and a presentation. After completion of the project, the students should have gathered new information and insights into the activities of practicing engineers while acquiring skills in innovative research fields. In the end, the students will be able to present technical projects, and to develop problem solution strategies and will hence also obtain worthwhile communication skills.

Contents:

The project topic is usually determined by the respective lecturer or one of his/her assistants. In addition to this, students may also conduct project work on topics defined by companies from industry or official authorities. However, the project work must be completed under the supervision of one of the course’s lecturers. The projects are usually devised so as to integrate interdisciplinary aspects such as

o Noticing problems and describing them o Formulating envisaged goals o Team-oriented problem solutions o Organizing and optimizing one's time and work plan o Interdisciplinary problem solutions o Literature research and evaluation as well as the consultation

of experts o Documentation, illustration and presentation of results

Literature: The relevant literature will be announced along with the project topic.



Study course: Master Course Computational Engineering

Module name: CE-W05: Simulation of Incompressible Turbulent Flows with the Finite Volume Method

Abbreviation, if applicable: SITFFVM


Module co-ordinator(s): Prof. Dr. rer. nat. K. Hackl


Master of Science course Computational Engineering: optional course. This course is not taught in any other study course.


Simulation of incompressible turbulent flows with the Finite Volume method


Lecturer(s): Dr.-Ing. J. Franke

Language: English

Requirements: Basic knowledge in Fluid Mechanics and Computational Fluid Dynamics




Pass of the final oral test to award the certificate of attendance


thereof face-to-face teaching [h] 45


45


Homework [h] -

Credit points: 3




Acquiring new theoretical and practical knowledge and extending existing theoretical and practical knowledge on simulation of incompressible turbulent flows with commercial software systems.

Content:

The lecture provides an overall insight into the modelling and simulation of incompressible turbulent flows within current commercial software tools. The Reynolds averaged equations of incompressible fluid dynamics are discussed together with the most common turbulence models used for closure, with emphasis on the physical assumptions applied in the derivations. Then the numerical solution of these equations with the Finite Volume method is recapitulated. Different meshing approaches and approximation schemes are discussed with focus on unstructured grids and so called high resolution schemes as applied in the flow solver Ansys Fluent. The choice of suitable boundary conditions for different application fields is presented too. In the computer exercises the students will learn to create meshes with Ansys ICEMCFD with focus on unstructured meshes. Flow simulations will be performed with Ansys Fluent. Emphasis is put on the influence of different numerical approximations on the computed flow physics.

Forms of media: Blackboard and beamer presentations, computer exercises

Literature: Durbin, P. A., & Reif, B. P.: Statistical theory and modeling for turbulent flows. John Wiley & Sons, 2011. Ferziger, J. H., & Peric, M.: Computational methods for fluid dynamics. Springer Science & Business Media, 2012. Versteeg, H. K., & Malalasekera, W.: An introduction to computational fluid dynamics: the finite volume method. Pearson Education, 2007.



Study course: Master course Computational Engineering

Module name: CE-W06: Advanced Constitutive Models for Geomaterials

Abbreviation, if applicable: ACMG


Module co-ordinator(s): Dr. A.A. Lavasan


Master of Science course Computational Engineering: Optional Course, 2nd semester


Semester/term: 2nd Semester, summer term

Lecturer(s): Dr. A.A. Lavasan / Assistants

Language: English

Requirements: Fundamental knowledge in soil mechanics and numerical simulation in Geotechnics


Lecture: 1 h Exercise: 1 h

Study/exam achievements: Oral examination / 30 minutes


thereof face-to-face teaching [h] 30


45


Homework [h] 15

Credit points: 3




Within the module CE-WP09 (Numerical Simulation in Geotechnics and Tunneling), some basic and advanced constitutive models for geomaterials are introduced. In this course, further advanced constitutive models will be introduced and their relevance for different geotechnical applications will be discussed. One main objective of this course is to study the influence of different constitutive models on the numerical results for various geotechnical applications.

Content: Advanced Constitutive Models Hardening Soil Small strain (HSS) model Modified Cam-Clay (MCC) model Hoek-Brown (HB) model Hypoplasticity model Calibration of advanced constitutive models

Influence of the constitutive model on numerical simulations in Geotechnics for

Flat foundations Retaining walls Tunneling

Forms of media: video and overhead projector, computer, blackboard, lecture notes

Literature: Benz, T. (2006). Small-Strain Stiffness of Soils and its Numerical Consequences, PhD Thesis, Universität Stuttgart, Germany. Hoek, E., Carranza-Torres, C., & Corkum, B. (2002). Hoek-Brown failure criterion-2002 edition. Proceedings of NARMS-Tac, 1(1), 267-273. Kolymbas, D., Herle, I., & Von Wolffersdorff, P. A. (1995). Hypoplastic constitutive equation with internal variables. International Journal for Numerical and Analytical Methods in Geomechanics, 19(6), 415-436. Wood, D. M. (1990). Soil behaviour and critical state soil mechanics. Cambridge university press. Lecture notes




Module name: CE-W07: Applied Finite Element Method

Abbreviation, if applicable: FEA


-

Module co-ordinator(s): Prof. Dr. techn. G. Meschke


Master’s Course Computational Engineering: Optional Course, 1st semester

Courses included in the module, if applicable: Finite Element Analysis

Semester/term: 1st Semester, winter term

Lecturer: Prof. Dr. techn. G. Meschke, Assistants

Language: English

Requirements: Basics of CAD modeling and Finite Element Method


Lecture: 1 h

Exercise: 1 h

Examination: Final Project + Presentation - 100%



20


20


Homework [h] 20

Credit Points: 2




In this module, the students acquire skills to apply the finite element method on various structural problems using a multi-physics commercial software (ABAQUS). This course is designed to equip students with the necessary tools to apply the theoretical concepts learned in the Finite Element Methods course (CE-P05), on real-world problems.

The course covers the details of the structural analysis procedures: such as creating geometries; defining material properties, loads and boundary conditions; checking and solving the problems; analyzing and interpreting the results.

Content:

In this course FEM simulations are performed to analyze the quasi-static response of 1D, 2D and 3D structures. In addition to that, a brief introduction is given for contact modeling, heat conduction as well as thermo-mechanical coupling.

Media Formats: Moodle, Software tutorials on Beamer

Literature: K.-J. Bathe, Finite Element Procedures, Prentice Hall, 1996

Abaqus Analysis User's Guide




Module name: CE-W08: Quantum Computing

Abbreviation, if applica-ble: QC

Sub-heading, if applica-ble:

-

Module co-ordinator(s): Jun.-Prof. Dr. Andreas Vogel


Master’s Course Computational Engineering: optional course

Courses included in the module, if applicable: Quantum Computing

Semester/term: 3rd Semester, Winter term


Language: English

Requirements: -



Examination: Study project and oral examination


Thereof face-to-face teaching [h]

30


30


Homework [h] 30

Credit Points: 3



Learning Goals / Pro-fessional Skills:

After successfully completing the module the students

are enabled to design and create programs for quantum computers

can critically evaluate quantum systems and quantum algo-rithms

can assess the benefit of using quantum effects in computa-tions

Content:

The lecture covers the theory and application of quantum computing from a computer science perspective with a focus on the usage of today’s quantum hardware.

The relevant basics of quantum mechanics including superposition, measurement, interference, entanglement and mathematical nota-tion are introduced. The characteristics of quantum bits and registers are discussed, and the construction and properties of quantum gates and quantum circuits presented. Prominent examples for quantum algorithms are surveyed including algorithms based on quantum Fourier transformation (e.g. Shor’s factoring), quantum search (e.g. Grover), quantum solution of linear systems of equations (e.g. HHL) and quantum machine learning. Current quantum computer hardware as well as quantum error correction are discussed.

An introduction to quantum programming languages and environ-ments will be provided. Hands-on programming exercises and self-implemented quantum circuits in study projects are used to discuss and illustrate the theoretical content. Implementations are tested on quantum simulators and cloud-based quantum hardware.

Media Formats: Beamer, computer lab, cloud computing

Literature: M. Nielsen, I. Chuang (2000), Quantum Computation and Quantum Information, Cambridge University Press




Master Thesis

CE-M



Study course: Master‘s Program Computational Engineering

Module name: CE-M: Master Thesis


Module co-ordinator(s): All lecturers of the course


Master’s Program Computational Engineering: Compulsory


Semester/term: 4th semester / Summer term

Advisor: Professors, Docents and experienced Assistants of the course together with a Professor or Docent

Language: English

Requirements: Students can start their master’s thesis if six from seven compulsory courses have successfully been completed and a minimum of 70 credits has been collected.


Master Thesis / Presentation of 30 Minutes (obligatory)


Required: a research report supervised by the respective advisor, which describes a detailed research investigation and its results. Furthermore an oral presentation of the results is obligatory.


thereof face-to-face teaching [h] -


-


Homework [h] -

Credit points: 30




With the completion of their master thesis, students acquire the ability to plan, organize, develop, operate and present complex problems in Computational Engineering. The master thesis qualifies students to work independently in a Computational Engineering subject under the supervision of an advisor. The associated presentation serves to promote the students’ ability to deal with subject-specific problems and to present them in an appropriate and comprehensible manner. Further, it serves to prove whether the students have acquired the profound specialised knowledge, which is required to take the step from their studies to professional life, whether they have developed the ability to deal with problems from their in-depth subject by applying scientific methods, and to apply their scientific knowledge.

Contents: The master thesis can either be theoretically, practically, constructively or organisationally-oriented. Its topic is determined by the respective supervisor. The results should both be visualised and illustrated in writing in a detailed manner. This particularly includes a summary, an outline and a list of the references used within a specific thesis and obligatory, an oral presentation.



Documents

Master‘s Program Computational Engineering · Content Curriculum.....3 Compulsory Courses CE-P01 – CE-P07.....4 CE-P01: Mathematical Aspects of Differential Equations and Numerical