Module Description

Module: Design optimization and probabilistic approaches in structural analysis

Courses:

TitleTypeHrs/WeekPeriod
Design Optimization and Probabilistic Approaches in Structural AnalysisLecture2Summer Semester
Design Optimization and Probabilistic Approaches in Structural AnalysisRecitation Section (large)2Summer Semester

Module Responsibility:

Prof. Benedikt Kriegesmann

Admission Requirements:

None

Recommended Previous Knowledge:

  • Technical mechanics
  • Higher math

Educational Objectives:

Professional Competence

Theoretical Knowledge
  • Design optimization
    • Gradient based methods
    • Genetic algorithms
    • Optimization with constraints
    • Topology optimization
  • Reliability analysis
    • Stochastic basics
    • Monte Carlo methods
    • Semi-analytic approaches
  • robust design optimization
    • Robustness measures
    • Coupling of design optimization and reliability analysis
Capabilities
  • Application of optimization algorithms and probabilistic methods in the design of structures
  • Programming with Matlab
  • Implementation of algorithms
  • Debugging

Personal Competence

Social Competence
  • Team work
  •  Oral explanation of the the work
Autonomy
  • Application of methods learned in the framework of a home work
  • Familiarizing with source code provided
  • Description of approaches and results

ECTS-Credit Points Module:

6 ECTS

Examination:

Written elaboration

Workload in Hours:

Independent Study Time: 124, Study Time in Lecture: 56


Course: Design Optimization and Probabilistic Approaches in Structural Analysis (Lecture)

Lecturer:

Benedikt Kriegesmann

Language:

German

Period:

Summer Semester

Content:

In the course the theoretic basics for design optimization and reliability analysis are taught, where the focus is on the application of such methods. The lectures will consist of presentations as well as computer exercises. In the computer exercises, the methods learned will be implemented in Matlab for understanding the practical realization.

The following contents will be considered:

  • Design optimization
    • Gradient based methods
    • Genetic algorithms
    • Optimization with constraints
    • Topology optimization
  • Reliability analysis
    • Stochastic basics
    • Monte Carlo methods
    • Semi-analytic approaches
  • robust design optimization
    • Robustness measures
    • Coupling of design optimization and reliability analysis

Literature:

[1] Arora, Jasbir. Introduction to Optimum Design. 3rd ed. Boston, MA: Academic Press, 2011.
[2] Haldar, A., and S. Mahadevan. Probability, Reliability, and Statistical Methods in Engineering Design. John Wiley & Sons New York/Chichester, UK, 2000.


Course: Design Optimization and Probabilistic Approaches in Structural Analysis (Recitation Section (large))

Lecturer:

Benedikt Kriegesmann

Language:

German

Period:

Summer Semester

Content:

Matlab exercises complementing the lecture

Literature:

siehe Vorlesung