|
abstract:
We briefly review the goals of our project of investigating and clarifying the mathematical underpinnings of stochastic Galerkin methods, currently one of the key approaches for approximating the solution of PDEs with random data, as well as developing efficient computational solution methods. We will split our presentation between the two subprojects. The first, presented by Antje Mugler, will discuss the approximation of input and solution random fields using multivariate polynomials. The second, presented by Elisabeth Ullmann, will give a progress report on linear solvers for stochastic Galerkin discretizations. |
