Schedule: Wednesday 11:00 - 13:00

Room: INF 293 / SR 215

SWS: 2

CP: 4

Language: English

Muesli: https://www.mathi.uni-heidelberg.de/muesli/lecture/view/514

Topics:

Knowledge in mathematical modelling in numerical quantification of parametric uncertainty propagation for differential equations:

1. Fundamentals in probability theory
2. Karhunen-Löve decomposition
3. Generalized polynomial chaos expension
4. Monte-Carlo and Quasi-Monte-Carlo methods
5. Stochastic collocation method
6. Stochastic Galerkin method
7. Inverse uncertainty Quantification

Recommended literature:

• O.P. Le Maitre an Knio: Spectral methods for uncertainty quantification: with applications to fluid flow, Springer, 2010
• R. Ghanem and P. Spanos: Stochastic Finite-Elements: A spectral approach, Dover, 2013

Recommended preliminaries:

• Knowledge in probability theory, Analysis I,II and III
• Knowledge in Numerics for ordinary and partial differential equations

Exam: 

TBA