Course code TUM 16
Course title Structural Reliability
Institution Technische Universität München
Course address Technische Universität München, Arcisstr. 21, 80333 München
City Munich
Minimum year of study 4th year
Minimum level of English Good
Minimum level of French None
Key words Structural reliability, probabilistic methods, stochastic mechanics, risk
Language English
Professor responsible Prof. Dr. Daniel Straub, Dr. Iason Papaioannou
Telephone +49 (89) 289 - 25038
Fax
Email iason.papaioannou@tum.de
Participating professors
Number of places Minimum: 10, Maximum: 30, Reserved for local students: 15
Objectives

Introduction to modern structural reliability methods for the evaluation of the performance of engineering systems subject to uncertainty and randomness. The course will introduce the theory and applications.

This course should enable the student to perform reliability analysis for realistic engineered structures and systems, and to interpret the results of such analyses. At the end of the course, the student will be able to:

- Formulate the reliability problem for engineering systems.

- Establish the probabilistic model for various loadings and materials.

- Compute estimates of the failure probability of engineered systems using various approximate methods.

- Assess the relative importance of random variables on the reliability.

- Assess the sensitivities of the results to model assumptions.

- Update the reliability estimates with observed data.

- Construct response surfaces for the reliability analysis of systems that are analyzed with large FEM codes.

Programme to be followed

1. Introduction and brief review of probability theory

2. First and Second Order Reliability Method

3. Monte Carlo Simulation

4. System reliability

5. Risk acceptance and target reliabilities

6. Importance sampling & Subset simulation

8. Responce surface methods (metamodels)

9. Advanced topics

Prerequisites

Good knowledge of probability theory is required.

The course is suitable for civil and mechanical engineering students.

Students must bring a laptop with either Matlab or Octave installed. (Octave is freeware).

Course exam Oral exam at the end of the week & take-home exam.
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