Variance-based sensitivity analysis for time-dependent processes

被引：35

作者：

Alexanderian, Alen ^{[1
]}

Gremaud, Pierre A. ^{[1
]}

Smith, Ralph C. ^{[1
]}

机构：

[1] North Carolina State Univ, Dept Math, Raleigh, NC 27695 USA

来源：

RELIABILITY ENGINEERING & SYSTEM SAFETY | 2020年 / 196卷

基金：

美国国家科学基金会;

关键词：

Global sensitivity analysis; Sobol' Indices; Karhunen-Loeve expansion; Time-dependent processes; Surrogate models; Polynomial chaos; Uncertainty quantification; POLYNOMIAL CHAOS EXPANSIONS; EFFICIENT COMPUTATION; SOBOL INDEXES; APPROXIMATION; MODELS;

D O I：

10.1016/j.ress.2019.106722

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The global sensitivity analysis of time-dependent processes requires history-aware approaches. We develop for that purpose a variance-based method that leverages the correlation structure of the problems under study and employs surrogate models to accelerate the computations. The errors resulting from fixing unimportant uncertain parameters to their nominal values are analyzed through a priori estimates. We illustrate our approach on a harmonic oscillator example and on a nonlinear dynamic cholera model.

引用

页数：17

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