Module Handbook

  • Dynamischer Default-Fachbereich geändert auf MV

Notes on the module handbook of the department Mechanical and Process Engineering

Die hier dargestellten veröffentlichten Studiengang-, Modul- und Kursdaten des Fachbereichs Maschinenbau und Verfahrenstechnik ersetzen die Modulbeschreibungen im KIS und wuden mit Ausnahme folgender Studiengänge am 28.10.2020 verabschiedet.

Ausnahmen:

Module MV-TM-M135-M-7

Engineering Optimization (M, 3.0 LP)

Module Identification

Module Number Module Name CP (Effort)
MV-TM-M135-M-7 Engineering Optimization 3.0 CP (90 h)

Basedata

CP, Effort 3.0 CP = 90 h
Position of the semester 1 Sem. in SuSe
Level [7] Master (Advanced)
Language [DE] German
Module Manager
Lecturers
Area of study [MV-LTM] Applied Mechanics
Reference course of study [MV-88.808-SG] M.Sc. Computational Engineering
Livecycle-State [NORM] Active

Courses

Type/SWS Course Number Title Choice in
Module-Part
Presence-Time /
Self-Study
SL SL is
required for exa.
PL CP Sem.
2V MV-LTM-86009-K-7
Engineering Optimization
P 28 h 62 h - - PL1 3.0 SuSe
  • About [MV-LTM-86009-K-7]: Title: "Engineering Optimization"; Presence-Time: 28 h; Self-Study: 62 h

Examination achievement PL1

  • Form of examination: oral examination (30-45 Min.)
  • Examination Frequency: each semester
  • Examination number: 10135 ("Engineering Optimization")

Evaluation of grades

The grade of the module examination is also the module grade.


Contents

The basic concepts and fundamental quantities of mathematical optimization are presented, in which a focus is put on aspects which are of foremost importance for structural optimization problems. As part of an introduction, basic knowledge of mathematical terms and aspects of optimization is imparted. Afterwards optimization problems without constraints as well as problems with constraints are considered. Based on this, alternative formulations of an optimization problem (so-called Lagrange duality) are presented with the help of Lagrange functions. Subsequently approximation methods, optimality criteria methods and multi-criteria optimization are considered. Finally, outlooks on other areas such as shape optimization and topology optimization are given.

Competencies / intended learning achievements

  • Students are familiar with basic concepts and fundamental quantities of mathematical optimization
  • Students are able to explain different optimization strategies
  • Students are able to compare and rate different optimization strategies
  • Students are able to formulate (primal and dual) optimization problems
  • Students are able to implement and use numerical optimization techniques

Literature

  • Harzheimer, L.: Strukturoptimierung - Grundlagen und Anwendungen, Verlag Harri Deutsch 2008
  • Spellucci, P.: Numerische Verfahren der nichtlinearen Optimierung, Birkhäuser Verlag 1993
  • Reinhard, R.; Hoffmann, A.; Gerlach T.: Nichtlineare Optimierung, Springer Verlag 2013
  • Schumacher, A.: Optimierung mechanischer Strukturen - Grundlagen und industrielle Anwendungen, Springer-Verlag 2005

Requirements for attendance (informal)

Basic knowledge in technical mechanics and higher mathematics

Requirements for attendance (formal)

None

References to Module / Module Number [MV-TM-M135-M-7]

Course of Study Section Choice/Obligation
[MV-88.808-SG] M.Sc. Computational Engineering Pflichtmodule [P] Compulsory
Module-Pool Name
[MV-ALL-MPOOL-6] Wahlpflichtmodule allgemein
[MV-MBINFO-MPOOL-6] Wahlpflichtmodule Maschinenbau mit angewandter Informatik
[MV-PE-MPOOL-6] Wahlpflichtmodule Produktentwicklung im Maschinenbau