A new Kriging-based DoE strategy and its application to structural reliability analysis

As the numerical model of engineering structure becomes more and more complicated and time consuming, efficient structural reliability analysis is badly in need. To reduce the number of calls to the performance function and iterative times during structural reliability analysis, an innovative strate...

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Main Authors: Zhenliang Yu, Zhili Sun, Jian Wang, Xiaodong Chai
Format: Article
Language:English
Published: SAGE Publishing 2018-03-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1177/1687814018767682
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spelling doaj-de384a7e70fe494781e60ae7b746ebe62020-11-25T03:36:31ZengSAGE PublishingAdvances in Mechanical Engineering1687-81402018-03-011010.1177/1687814018767682A new Kriging-based DoE strategy and its application to structural reliability analysisZhenliang YuZhili SunJian WangXiaodong ChaiAs the numerical model of engineering structure becomes more and more complicated and time consuming, efficient structural reliability analysis is badly in need. To reduce the number of calls to the performance function and iterative times during structural reliability analysis, an innovative strategy of the design of experiments (DoE) called Isomap-Clustering strategy is proposed. According to the statistical information provided by Kriging, points with the worst uncertainty for reliability analysis are on the estimated limit state. Therefore, by combining Isomap and k -means clustering algorithm, Isomap-Clustering strategy refreshes the DoE of the Kriging model with a few representative points in the vicinity of the estimated limit state each iteration and iteratively “pushes” the estimated limit state to the real one until a stopping condition is satisfied. By employing the proposed DoE strategy and sparse polynomial-Kriging model, a structural reliability analysis method is constructed, whose stopping criterion is defined by derivation. Three examples are studied. Results show that the proposed method can lower the number of calls to the performance function and remarkably reduces the iterations of structural reliability analysis.https://doi.org/10.1177/1687814018767682
collection DOAJ
language English
format Article
sources DOAJ
author Zhenliang Yu
Zhili Sun
Jian Wang
Xiaodong Chai
spellingShingle Zhenliang Yu
Zhili Sun
Jian Wang
Xiaodong Chai
A new Kriging-based DoE strategy and its application to structural reliability analysis
Advances in Mechanical Engineering
author_facet Zhenliang Yu
Zhili Sun
Jian Wang
Xiaodong Chai
author_sort Zhenliang Yu
title A new Kriging-based DoE strategy and its application to structural reliability analysis
title_short A new Kriging-based DoE strategy and its application to structural reliability analysis
title_full A new Kriging-based DoE strategy and its application to structural reliability analysis
title_fullStr A new Kriging-based DoE strategy and its application to structural reliability analysis
title_full_unstemmed A new Kriging-based DoE strategy and its application to structural reliability analysis
title_sort new kriging-based doe strategy and its application to structural reliability analysis
publisher SAGE Publishing
series Advances in Mechanical Engineering
issn 1687-8140
publishDate 2018-03-01
description As the numerical model of engineering structure becomes more and more complicated and time consuming, efficient structural reliability analysis is badly in need. To reduce the number of calls to the performance function and iterative times during structural reliability analysis, an innovative strategy of the design of experiments (DoE) called Isomap-Clustering strategy is proposed. According to the statistical information provided by Kriging, points with the worst uncertainty for reliability analysis are on the estimated limit state. Therefore, by combining Isomap and k -means clustering algorithm, Isomap-Clustering strategy refreshes the DoE of the Kriging model with a few representative points in the vicinity of the estimated limit state each iteration and iteratively “pushes” the estimated limit state to the real one until a stopping condition is satisfied. By employing the proposed DoE strategy and sparse polynomial-Kriging model, a structural reliability analysis method is constructed, whose stopping criterion is defined by derivation. Three examples are studied. Results show that the proposed method can lower the number of calls to the performance function and remarkably reduces the iterations of structural reliability analysis.
url https://doi.org/10.1177/1687814018767682
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