A novel surrogate for extremes of random functions

Hui Xu, Mircea D. Grigoriu and Kurtis R. Gurley

Reliability Engineering and System Safety, 2023, vol. 239, issue C

Abstract: Numerical solutions of stochastic problems require the representation of random functions in their definitions by finite dimensional (FD) models, i.e., deterministic functions of time and finite sets of random variables. It is common to represent the coefficients of these FD surrogates by polynomial chaos (PC) models. We propose a novel model, referred to as the polynomial chaos translation (PCT) model, which matches exactly the marginal distributions of the FD coefficients and approximately their dependence. PC- and PCT-based FD models are constructed for a set of test cases and a wind pressure time series recorded at the boundary layer wind tunnel facility at the University of Florida. The PCT-based models capture the joint distributions of the FD coefficients and the extremes of target times series accurately while PC-based FD models do not have this capability.

Keywords: Extremes; Finite dimensional (FD) models; Polynomial chaos (PC); Polynomial chaos translation (PCT); FD surrogates (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:239:y:2023:i:c:s0951832023004076

DOI: 10.1016/j.ress.2023.109493

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