Computation of Higher-Order Moments of Generalized Polynomial Chaos Expansions

TL;DR

This paper introduces analytical formulas for computing higher-order moments of polynomial chaos expansions, enabling quadrature-free evaluation and improving uncertainty quantification in fluid flow simulations.

Contribution

It provides a novel analytical approach for calculating moments of polynomial chaos expansions, reducing reliance on numerical quadrature methods.

Findings

Analytical formulas match Gauss quadrature results.

Quadrature-free computation reduces computational cost.

Enhanced accuracy in higher-order moment evaluation.

Abstract

Because of the complexity of fluid flow solvers, non-intrusive uncertainty quantification techniques have been developed in aerodynamic simulations in order to compute the quantities of interest required in an optimization process, for example. The objective function is commonly expressed in terms of moments of these quantities, such as the mean, standard deviation, or even higher-order moments. Polynomial surrogate models based on polynomial chaos expansions have often been implemented in this respect. The original approach of uncertainty quantification using polynomial chaos is however intrusive. It is based on a Galerkin-type formulation of the model equations to derive the governing equations for the polynomial expansion coefficients. Third-order, indeed fourth-order moments of the polynomials are needed in this analysis. Besides, both intrusive and non-intrusive approaches call for their computation provided that higher-order moments of the quantities of interest need be post-processed. In most applications they are evaluated by Gauss quadratures, and eventually stored for use throughout the computations. In this paper analytical formulas are rather considered for the moments of the continuous polynomials of the Askey scheme, so that they can be evaluated by quadrature-free procedures instead. Matlab codes have been developed for this purpose and tested by comparisons with Gauss quadratures.