Past Event: Oden Institute Seminar

Numerical Simulations with Uncertainty: Prediction and Estimation

Dongbin Xiu, Department of Mathematics, Purdue University

Abstract

There has been growing interest in developing numerical methods for stochastic computations. This is motivated by the need to conduct uncertainty quantification in simulations, where uncertainty is ubiquitous and exists in parameter values, initial and boundary conditions, geometry, etc. In this talk we review and discuss a class of fast numerical algorithms based on generalized polynomial chaos (gPC) expansion. The methods are highly efficient, compared to other traditional ones, and suitable for stochastic simulations of complex systems. In addition to the forward stochastic problem solvers, we also discuss gPC-based methods for addressing \