- 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
Topology Optimization (M, 4.5 LP)
|Module Number||Module Name||CP (Effort)|
|INF-14-55-M-6||Topology Optimization||4.5 CP (135 h)|
|CP, Effort||4.5 CP = 135 h|
|Position of the semester||1 Sem. irreg. SuSe|
|Level|| Master (General)|
|Language||[DE/EN] German or English as required|
|Area of study||[INF-VIS] Visualisation and Scientific Computing|
|Reference course of study||[INF-88.79-SG] M.Sc. Computer Science|
|Type/SWS||Course Number||Title||Choice in |
|SL||SL is |
required for exa.
|P||42 h||93 h||
- 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.
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.
Will be announced in the lecture.
Requirements for attendance (informal)
Requirements for attendance (formal)
References to Module / Module Number [INF-14-55-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|