Loading…
A recursive dimension-reduction method for high-dimensional reliability analysis with rare failure event
A new dimension-reduction method (DRM), called ’subset active subspace method (SASM)’, is proposed to compute small failure probabilities encountered in high-dimensional reliability analysis of engineering systems. The basic idea is to introduce a recursive procedure to improve the efficiency, accur...
Saved in:
Published in: | Reliability engineering & system safety 2021-09, Vol.213, p.107710, Article 107710 |
---|---|
Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c328t-a53393a97cf2f9b54167f73a54036623588caff138c44ebf582dec9e5081b7f63 |
---|---|
cites | cdi_FETCH-LOGICAL-c328t-a53393a97cf2f9b54167f73a54036623588caff138c44ebf582dec9e5081b7f63 |
container_end_page | |
container_issue | |
container_start_page | 107710 |
container_title | Reliability engineering & system safety |
container_volume | 213 |
creator | Jiang, Zhong-ming Feng, De-Cheng Zhou, Hao Tao, Wei-Feng |
description | A new dimension-reduction method (DRM), called ’subset active subspace method (SASM)’, is proposed to compute small failure probabilities encountered in high-dimensional reliability analysis of engineering systems. The basic idea is to introduce a recursive procedure to improve the efficiency, accuracy and applicability of the conventional active subspace method (ASM). For the reliability problems with a rare event, SASM firstly transfers the original high-dimensional reliability problem into a low-dimensional reliability problem in a proper failure domain. Then, a simplified low-dimensional surrogate model is built in order to improve the result of reliability analysis by increasing significantly the samples with a minimum additional computational effort. The proposed method is verified by three nonlinear numerical examples, including theoretical and industrial, explicit and implicit performance functions. Besides, some other existing methods are also investigated and compared to the proposed method. It is found that the proposed method can keep the trade-off between accuracy and efficiency.
•A recursive reduction procedure is introduced for reliability problem with rare event.•Active subspace method is employed to solve high-dimensional problem.•Kriging method is used to fit the data into a robust low-dimensional surrogate model. |
doi_str_mv | 10.1016/j.ress.2021.107710 |
format | article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2553568954</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0951832021002453</els_id><sourcerecordid>2553568954</sourcerecordid><originalsourceid>FETCH-LOGICAL-c328t-a53393a97cf2f9b54167f73a54036623588caff138c44ebf582dec9e5081b7f63</originalsourceid><addsrcrecordid>eNp9kEtLxDAUhYMoOI7-AVcB1x3zaNoU3AyDLxhwo-uQpjc2pdOOSToy_94MFZeuzuVwzuXwIXRLyYoSWtx3Kw8hrBhhNBllSckZWlBZVhmRvDhHC1IJmknOyCW6CqEjhOSVKBeoXWMPZvLBHQA3bgdDcOOQeWgmE9OFdxDbscF29Lh1n232l9F9avZO16538Yh1Mo7BBfztYou99oCtdv2UFA4wxGt0YXUf4OZXl-jj6fF985Jt355fN-ttZjiTMdOC84rrqjSW2aoWOS1KW3ItcsKLgnEhpdHWUi5NnkNthWQNmAoEkbQubcGX6G7-u_fj1wQhqm6cfBoXFBOCi0JWIk8pNqeMH0PwYNXeu532R0WJOhFVnToRVSeiaiaaSg9zCdL-gwOvgnEwGGhcYhhVM7r_6j9s6oC-</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2553568954</pqid></control><display><type>article</type><title>A recursive dimension-reduction method for high-dimensional reliability analysis with rare failure event</title><source>ScienceDirect Freedom Collection</source><creator>Jiang, Zhong-ming ; Feng, De-Cheng ; Zhou, Hao ; Tao, Wei-Feng</creator><creatorcontrib>Jiang, Zhong-ming ; Feng, De-Cheng ; Zhou, Hao ; Tao, Wei-Feng</creatorcontrib><description>A new dimension-reduction method (DRM), called ’subset active subspace method (SASM)’, is proposed to compute small failure probabilities encountered in high-dimensional reliability analysis of engineering systems. The basic idea is to introduce a recursive procedure to improve the efficiency, accuracy and applicability of the conventional active subspace method (ASM). For the reliability problems with a rare event, SASM firstly transfers the original high-dimensional reliability problem into a low-dimensional reliability problem in a proper failure domain. Then, a simplified low-dimensional surrogate model is built in order to improve the result of reliability analysis by increasing significantly the samples with a minimum additional computational effort. The proposed method is verified by three nonlinear numerical examples, including theoretical and industrial, explicit and implicit performance functions. Besides, some other existing methods are also investigated and compared to the proposed method. It is found that the proposed method can keep the trade-off between accuracy and efficiency.
•A recursive reduction procedure is introduced for reliability problem with rare event.•Active subspace method is employed to solve high-dimensional problem.•Kriging method is used to fit the data into a robust low-dimensional surrogate model.</description><identifier>ISSN: 0951-8320</identifier><identifier>EISSN: 1879-0836</identifier><identifier>DOI: 10.1016/j.ress.2021.107710</identifier><language>eng</language><publisher>Barking: Elsevier Ltd</publisher><subject>Accuracy ; Computer applications ; Dimension reduction ; Dimensional analysis ; Failure analysis ; High-dimensional reliability ; Rare failure event ; Reduction ; Reliability analysis ; Reliability engineering ; Subset active subspace ; Subspace methods</subject><ispartof>Reliability engineering & system safety, 2021-09, Vol.213, p.107710, Article 107710</ispartof><rights>2021 Elsevier Ltd</rights><rights>Copyright Elsevier BV Sep 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c328t-a53393a97cf2f9b54167f73a54036623588caff138c44ebf582dec9e5081b7f63</citedby><cites>FETCH-LOGICAL-c328t-a53393a97cf2f9b54167f73a54036623588caff138c44ebf582dec9e5081b7f63</cites><orcidid>0000-0002-0146-5518</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Jiang, Zhong-ming</creatorcontrib><creatorcontrib>Feng, De-Cheng</creatorcontrib><creatorcontrib>Zhou, Hao</creatorcontrib><creatorcontrib>Tao, Wei-Feng</creatorcontrib><title>A recursive dimension-reduction method for high-dimensional reliability analysis with rare failure event</title><title>Reliability engineering & system safety</title><description>A new dimension-reduction method (DRM), called ’subset active subspace method (SASM)’, is proposed to compute small failure probabilities encountered in high-dimensional reliability analysis of engineering systems. The basic idea is to introduce a recursive procedure to improve the efficiency, accuracy and applicability of the conventional active subspace method (ASM). For the reliability problems with a rare event, SASM firstly transfers the original high-dimensional reliability problem into a low-dimensional reliability problem in a proper failure domain. Then, a simplified low-dimensional surrogate model is built in order to improve the result of reliability analysis by increasing significantly the samples with a minimum additional computational effort. The proposed method is verified by three nonlinear numerical examples, including theoretical and industrial, explicit and implicit performance functions. Besides, some other existing methods are also investigated and compared to the proposed method. It is found that the proposed method can keep the trade-off between accuracy and efficiency.
•A recursive reduction procedure is introduced for reliability problem with rare event.•Active subspace method is employed to solve high-dimensional problem.•Kriging method is used to fit the data into a robust low-dimensional surrogate model.</description><subject>Accuracy</subject><subject>Computer applications</subject><subject>Dimension reduction</subject><subject>Dimensional analysis</subject><subject>Failure analysis</subject><subject>High-dimensional reliability</subject><subject>Rare failure event</subject><subject>Reduction</subject><subject>Reliability analysis</subject><subject>Reliability engineering</subject><subject>Subset active subspace</subject><subject>Subspace methods</subject><issn>0951-8320</issn><issn>1879-0836</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kEtLxDAUhYMoOI7-AVcB1x3zaNoU3AyDLxhwo-uQpjc2pdOOSToy_94MFZeuzuVwzuXwIXRLyYoSWtx3Kw8hrBhhNBllSckZWlBZVhmRvDhHC1IJmknOyCW6CqEjhOSVKBeoXWMPZvLBHQA3bgdDcOOQeWgmE9OFdxDbscF29Lh1n232l9F9avZO16538Yh1Mo7BBfztYou99oCtdv2UFA4wxGt0YXUf4OZXl-jj6fF985Jt355fN-ttZjiTMdOC84rrqjSW2aoWOS1KW3ItcsKLgnEhpdHWUi5NnkNthWQNmAoEkbQubcGX6G7-u_fj1wQhqm6cfBoXFBOCi0JWIk8pNqeMH0PwYNXeu532R0WJOhFVnToRVSeiaiaaSg9zCdL-gwOvgnEwGGhcYhhVM7r_6j9s6oC-</recordid><startdate>202109</startdate><enddate>202109</enddate><creator>Jiang, Zhong-ming</creator><creator>Feng, De-Cheng</creator><creator>Zhou, Hao</creator><creator>Tao, Wei-Feng</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TB</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0002-0146-5518</orcidid></search><sort><creationdate>202109</creationdate><title>A recursive dimension-reduction method for high-dimensional reliability analysis with rare failure event</title><author>Jiang, Zhong-ming ; Feng, De-Cheng ; Zhou, Hao ; Tao, Wei-Feng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c328t-a53393a97cf2f9b54167f73a54036623588caff138c44ebf582dec9e5081b7f63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Accuracy</topic><topic>Computer applications</topic><topic>Dimension reduction</topic><topic>Dimensional analysis</topic><topic>Failure analysis</topic><topic>High-dimensional reliability</topic><topic>Rare failure event</topic><topic>Reduction</topic><topic>Reliability analysis</topic><topic>Reliability engineering</topic><topic>Subset active subspace</topic><topic>Subspace methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jiang, Zhong-ming</creatorcontrib><creatorcontrib>Feng, De-Cheng</creatorcontrib><creatorcontrib>Zhou, Hao</creatorcontrib><creatorcontrib>Tao, Wei-Feng</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Environment Abstracts</collection><jtitle>Reliability engineering & system safety</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jiang, Zhong-ming</au><au>Feng, De-Cheng</au><au>Zhou, Hao</au><au>Tao, Wei-Feng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A recursive dimension-reduction method for high-dimensional reliability analysis with rare failure event</atitle><jtitle>Reliability engineering & system safety</jtitle><date>2021-09</date><risdate>2021</risdate><volume>213</volume><spage>107710</spage><pages>107710-</pages><artnum>107710</artnum><issn>0951-8320</issn><eissn>1879-0836</eissn><abstract>A new dimension-reduction method (DRM), called ’subset active subspace method (SASM)’, is proposed to compute small failure probabilities encountered in high-dimensional reliability analysis of engineering systems. The basic idea is to introduce a recursive procedure to improve the efficiency, accuracy and applicability of the conventional active subspace method (ASM). For the reliability problems with a rare event, SASM firstly transfers the original high-dimensional reliability problem into a low-dimensional reliability problem in a proper failure domain. Then, a simplified low-dimensional surrogate model is built in order to improve the result of reliability analysis by increasing significantly the samples with a minimum additional computational effort. The proposed method is verified by three nonlinear numerical examples, including theoretical and industrial, explicit and implicit performance functions. Besides, some other existing methods are also investigated and compared to the proposed method. It is found that the proposed method can keep the trade-off between accuracy and efficiency.
•A recursive reduction procedure is introduced for reliability problem with rare event.•Active subspace method is employed to solve high-dimensional problem.•Kriging method is used to fit the data into a robust low-dimensional surrogate model.</abstract><cop>Barking</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.ress.2021.107710</doi><orcidid>https://orcid.org/0000-0002-0146-5518</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0951-8320 |
ispartof | Reliability engineering & system safety, 2021-09, Vol.213, p.107710, Article 107710 |
issn | 0951-8320 1879-0836 |
language | eng |
recordid | cdi_proquest_journals_2553568954 |
source | ScienceDirect Freedom Collection |
subjects | Accuracy Computer applications Dimension reduction Dimensional analysis Failure analysis High-dimensional reliability Rare failure event Reduction Reliability analysis Reliability engineering Subset active subspace Subspace methods |
title | A recursive dimension-reduction method for high-dimensional reliability analysis with rare failure event |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-22T18%3A32%3A33IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20recursive%20dimension-reduction%20method%20for%20high-dimensional%20reliability%20analysis%20with%20rare%20failure%20event&rft.jtitle=Reliability%20engineering%20&%20system%20safety&rft.au=Jiang,%20Zhong-ming&rft.date=2021-09&rft.volume=213&rft.spage=107710&rft.pages=107710-&rft.artnum=107710&rft.issn=0951-8320&rft.eissn=1879-0836&rft_id=info:doi/10.1016/j.ress.2021.107710&rft_dat=%3Cproquest_cross%3E2553568954%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c328t-a53393a97cf2f9b54167f73a54036623588caff138c44ebf582dec9e5081b7f63%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2553568954&rft_id=info:pmid/&rfr_iscdi=true |