Ph.D. course on

Random Partial Differential Equations

LP1 2017/18

Chalmers University of Technology & University of Gothenburg


News

29/8: The schedule is fixed and an email was sent to all participants. Please choose a topic that you want to present by 31/8.
22/8: The first meeting is scheduled for Tuesday, August 29, 10:00 in MVL:14

Teacher

Course coordinator: Annika Lang
Email: annika.lang@chalmers.se
Office: MVL2086

Course description

Random partial differential equations (RPDE) are partial differential equations where some
of the parameters suffer under uncertainty. The uncertainty can be due to the lack of know-
ledge, measurement errors, or the complexity of exact deterministic model. Possible uncertain
parameters can influence the right hand side of the equation, the operator, the boundary, or
the initial condition. The goal of this course is to discuss existence and uniqueness of solutions
to RPDE and to derive efficient approximation methods to estimate solutions which includes
the numerical analysis of the convergence behavior of the considered schemes.

The course will start in the end of August and run twice a week (4 hours) until the end of
October (LP1 2017/18). The schedule will be decided by the participants at an introductory
meeting.

Course literature

will be updated continuously and still depends on the interest of the audience

Schedule

Tuesday 29/8
10-12
MVL:14
Introduction
Discussion of the schedule
(Annika)
Tuesday 5/9
13-15
MVL:14
Preliminaries in Functional Analysis and Probability Theory
(Annika)
Thursday 7/9
13-15
MVL:14
Introduction to elliptic PDE and equations with stochastic rhs (LN 3.1, 3.2(.0))
(Annika)
Tuesday 12/9
13-15
MVL:14
Galerkin approximation of moments (LN 3.2.1)
(Fardin)
Thursday 14/9
13-15
MVL:14
Galerkin approximation of moments (LN 3.2.1)
(Fardin)
Tuesday 19/9
13-15
MVL:14
Sparse tensor approximations (LN 3.2.2)
(Alice)
Thursday 21/9
13-15
MVL:14
Sparse tensor approximations (LN 3.2.2)
(Alice)
Tuesday 26/9
13-15
MVL:14
Introduction to elliptic PDE with stochastic operator and finite element approximation (LN 3.3, 3.3.1,3.3.1.1)
(Per)
Thursday 28/9
13-15
MVL:14
Introduction to elliptic PDE with stochastic operator and finite element approximation (LN 3.3, 3.3.1,3.3.1.1)
(Per)
Tuesday 3/10
13-15
MVL:15
Introduction to multilevel Monte Carlo and approximation of moments (LN 3.3.1.2)
(Anders)
Tuesday 10/10
13-15
MVL:15
Polynomial chaos expansions (LN 3.3.2.1)
(Helga)
Thursday 12/10
13-15
MVL:14
Polynomial chaos expansions (LN 3.3.2.1)
(Helga)
Tuesday 17/10
13-15
MVL:15
Equivalent formulation/transformation (LN 3.3.2.2)
(Milo)
Friday 20/10
13-15
MVL:15
Approximation of Legendre chaos expansions (LN 3.3.2.3)
(Milo)
Thursday 26/10
13-15
MVL:14
Project presentations

Examination

There will be exercises, an individual project, presentations, and lectures given by the students. The grading scale comprises Fail, (U), Pass (G), and successful completion of the course will be rewarded by 7.5 hp credit points.

Mailing list

If you want to receive information on the course by email, please contact annika.lang@chalmers.se