Dynamischer Default-Fachbereich geändert auf INF

Module INF-14-55-M-6

Topology Optimization (M, 4.5 LP)

Module Identification

Module Number	Module Name	CP (Effort)
INF-14-55-M-6	Topology Optimization	4.5 CP (135 h)

Basedata

CP, Effort	4.5 CP = 135 h
Position of the semester	1 Sem. irreg. SuSe
Level	[6] Master (General)
Language	[DE/EN] German or English as required
Module Manager	Gauger, Nicolas, Prof. Dr. (PROF \| DEPT: INF)
Lecturers	Gauger, Nicolas, Prof. Dr. (PROF \| DEPT: INF)
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

Courses

Type/SWS	Course Number	Title	Choice in Module-Part	Presence-Time / Self-Study		SL	SL is required for exa.	PL	CP	Sem.
2V+1U	INF-14-55-K-6	Topology Optimization	P	42 h	93 h	U-Schein	ja	PL1	4.5	irreg. SuSe

About [INF-14-55-K-6]: Title: "Topology Optimization"; Presence-Time: 42 h; Self-Study: 93 h
About [INF-14-55-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: 61455 ("Topology Optimization")

Evaluation of grades

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

From [INF-14-55-K-6] Topology Optimization:

Linear elastic equations and its discretization
Sizing optimization (Optimale Dimensionierung)
Shape optimization (Formoptimierung)
Topology optimization
Material distribution problems
Optimal microstructures
Bubble method
Derivation and characteristics of topological gradients

Competencies / intended learning achievements

While questioning specific structural design problems, the students learn how to model and compute structures (e.g. bridges, components, micro structures) and their characteristics (e.g. compliance) and how to set up discrete models for the structural design. The final goal is to enable the students to treat topology optimization problems for structures, while the methods for topology optimization make also use of sizing and shape design methodologies (as in case of bubble methods). In tutorials based on MATLAB and open source software, the students will get hands on the derived methods for topology optimization. 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.

Literature

From [INF-14-55-K-6] Topology Optimization:

Will be announced in the lecture.

Requirements for attendance (informal)

None

Requirements for attendance (formal)