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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2018-03-01
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Series: | Advances in Mechanical Engineering |
Online Access: | https://doi.org/10.1177/1687814018767682 |
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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 |
work_keys_str_mv |
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