Surrogate based method for evaluation of failure probability under multiple constraints
type: Item
instance of: scholarly article
zbMATH Open document ID: 1306.65012
DOI: 10.1137/120877192
author: Jing Li
author: Dongbin Xiu
published in: SIAM Journal on Scientific Computing
publication date: 2014-08-13T00:00:00Z
Mathematics Subject Classification ID: 65C50
Mathematics Subject Classification ID: 65C05
zbMATH DE Number: 6329832
zbMATH Keywords: failure probability
zbMATH Keywords: reliability analysis
zbMATH Keywords: uncertainty quantification
zbMATH Keywords: surrogate model
zbMATH Keywords: response surfaces
zbMATH Keywords: algorithm
zbMATH Keywords: Monte Carlo sampling
zbMATH Keywords: stochastic system
zbMATH Keywords: convergence
zbMATH Keywords: numerical example
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1137/120877192
OpenAlex ID: W1977133516
title: Surrogate based method for evaluation of failure probability under multiple constraints
review text: The authors study the problem of computing the failure probability subject to multiple constraints. In particular, the case of surrogate models, also known as response surfaces, is considered for the available constraints. An efficient numerical algorithm based on Monte Carlo sampling is presented, where a large portion of the samples is evaluated using the surrogates and only a small portion using the underlying stochastic system. Convergence analysis of the algorithm for multiple constraints is presented and its efficiency is demonstrated through numerical examples.
description: scientific article; zbMATH DE number 6329832