The optimal control of problems that are constrained by partial differential equations with uncertainties and with uncertain controls is addressed. The Lagrangian that defines the problem isâ€¦ (More)

We consider the numerical solution of time-dependent partial differential equations with random coefficients. A spectral approach, called stochastic finite element method, is used to compute theâ€¦ (More)

This paper presents an overview and comparison of iterative solvers for linear stochastic partial differential equations (PDEs). A stochastic Galerkin finite element discretization is applied toâ€¦ (More)

Partial differential equations with random coefficients appear for example in reliability problems and uncertainty propagation models. Various approaches exist for computing the stochasticâ€¦ (More)

This talk focuses on the direct solution of large complex indefinite unsymmetric systems, that arise in acoustic, vibro-acoustic and aero-acoustic simulations. These systems are structurallyâ€¦ (More)

Mathematical models of physical systems often contain parameters with an imprecisely known and uncertain character. It is quite common to represent these parameters by means of random variables.â€¦ (More)

A study of the relationship between images of the future and aspirations of nonworking adolescents was undertaken to test the hypothesis that pessimism about the future results in reduced studyâ€¦ (More)

The stochastic Galerkin and stochastic collocation method are two state-of-the-art methods for solving partial differential equations (PDE) containing random coefficients. While the latter method,â€¦ (More)

This paper considers the analysis of partial differential equations (PDE) containing multiple random variables. Recently developed collocation methods enable the construction of high-order stochasticâ€¦ (More)