Module Handbook

  • Dynamischer Default-Fachbereich geändert auf INF

Module INF-14-56-M-6

Optimization in Fluid Mechanics (M, 4.5 LP)

Module Identification

Module Number Module Name CP (Effort)
INF-14-56-M-6 Optimization in Fluid Mechanics 4.5 CP (135 h)


CP, Effort 4.5 CP = 135 h
Position of the semester 1 Sem. irreg. SuSe
Level [6] Master (General)
Language [EN] English
Module Manager
Area of study [INF-VIS] Visualisation and Scientific Computing
Reference course of study [INF-88.79-SG] M.Sc. Computer Science
Livecycle-State [NORM] Active


Type/SWS Course Number Title Choice in
Presence-Time /
SL SL is
required for exa.
PL CP Sem.
2V+1U INF-14-56-K-6
Optimization in Fluid Mechanics
P 42 h 93 h
ja PL1 4.5 irreg. SuSe
  • About [INF-14-56-K-6]: Title: "Optimization in Fluid Mechanics"; Presence-Time: 42 h; Self-Study: 93 h
  • About [INF-14-56-K-6]: The study achievement [U-Schein] proof of successful participation in the exercise classes (ungraded) must be obtained. It is a prerequisite for the examination for PL1.

Examination achievement PL1

  • Form of examination: oral examination (20-60 Min.)
  • Examination Frequency: Examination only within the course
  • Examination number: 61456 ("Optimization in Fluid Mechanics")

Evaluation of grades

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


  • State equations in fluid mechanics
  • Reynolds-averaging and turbulence modeling
  • Finite Volume Method
  • Cost functions and constraints in fluid mechanics
  • Shape optimization
  • Optimal active flow control
  • Continuous and discrete adjoint methods
  • One-shot methods

Competencies / intended learning achievements

While questioning specific design and control problems in fluid mechanics, the students derive efficient methods (e.g. adjoint-based and one-shot methods) and learn how to set-up appropriate design chains to solve them.

In tutorials based on the open-source CFD code SU2, the students will get hands on the derived methods for optimization and control in fluid mechanics. The lecture is furthermore valuable for getting introduced to more general lectures on optimization with PDEs. For those students who have heard already lectures on optimization with PDEs, the lecture gives a specific problem and application oriented insight into this class of optimization problems.


Will be announced in the lecture.

Requirements for attendance (informal)


Requirements for attendance (formal)


References to Module / Module Number [INF-14-56-M-6]

Course of Study Section Choice/Obligation
[INF-88.79-SG] M.Sc. Computer Science Specialization 1 [WP] Compulsory Elective
[MAT-88.105-SG] M.Sc. Mathematics Applied Mathematics [WP] Compulsory Elective
[MAT-88.706-SG] M.Sc. Mathematics International Applied Mathematics [WP] Compulsory Elective
[MAT-88.118-SG] M.Sc. Industrial Mathematics Computer Science and Computational Methods [WP] Compulsory Elective