Loading…

Towards error bounds of the failure probability of elastic structures using reduced basis models

Summary Structural reliability methods aim at computing the probability of failure of systems with respect to prescribed limit state functions. A common practice to evaluate these limit state functions is using Monte Carlo simulations. The main drawback of this approach is the computational cost, be...

Full description

Saved in:
Bibliographic Details
Published in:International journal for numerical methods in engineering 2017-11, Vol.112 (9), p.1216-1234
Main Authors: Gallimard, L., Florentin, E., Ryckelynck, D.
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-c3614-adfd02049ef5a7a48394c200769c0b09f70e3de226af1ba4b34f7537430255c73
cites cdi_FETCH-LOGICAL-c3614-adfd02049ef5a7a48394c200769c0b09f70e3de226af1ba4b34f7537430255c73
container_end_page 1234
container_issue 9
container_start_page 1216
container_title International journal for numerical methods in engineering
container_volume 112
creator Gallimard, L.
Florentin, E.
Ryckelynck, D.
description Summary Structural reliability methods aim at computing the probability of failure of systems with respect to prescribed limit state functions. A common practice to evaluate these limit state functions is using Monte Carlo simulations. The main drawback of this approach is the computational cost, because it requires computing a large number of deterministic finite element solutions. Surrogate models, which are built from a limited number of runs of the original model, have been developed, as substitute of the original model, to reduce the computational cost. However, these surrogate models, while decreasing drastically the computational cost, may fail in computing an accurate failure probability. In this paper, we focus on the control of the error introduced by a reduced basis surrogate model on the computation of the failure probability obtained by a Monte Carlo simulation. We propose a technique to determine bounds of this failure probability, as well as a strategy of enrichment of the reduced basis, based on limiting the bounds of the error of the failure probability for a multi‐material elastic structure. Copyright © 2017 John Wiley & Sons, Ltd.
doi_str_mv 10.1002/nme.5554
format article
fullrecord <record><control><sourceid>proquest_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_hal_01633909v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1960159923</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3614-adfd02049ef5a7a48394c200769c0b09f70e3de226af1ba4b34f7537430255c73</originalsourceid><addsrcrecordid>eNp10EFLwzAUB_AgCs4p-BECXvTQ-dI07XIcYzph6mWeY5omLqNrZtI69u1NrXjz9Mh7Px4vf4SuCUwIQHrf7PSEMZadoBEBXiSQQnGKRnHEE8an5BxdhLAFIIQBHaH3tTtIXwWsvXcel65r4sMZ3G40NtLWndd4710pS1vb9tiPdC1DaxUOre9UG0HAXbDNB_a66pSucCmDDXjnKl2HS3RmZB301W8do7eHxXq-TFavj0_z2SpRNCdZIitTxVMzrg2ThcymlGcqBShyrqAEbgrQtNJpmktDSpmVNDMFo0VGIWVMFXSM7oa9G1mLvbc76Y_CSSuWs5Xoe0BySjnwLxLtzWDjxz47HVqxdZ1v4nmC8BwI4zylUd0OSnkXgtfmby0B0WctYtaizzrSZKAHW-vjv068PC9-_Dcm-n9P</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1960159923</pqid></control><display><type>article</type><title>Towards error bounds of the failure probability of elastic structures using reduced basis models</title><source>Wiley</source><creator>Gallimard, L. ; Florentin, E. ; Ryckelynck, D.</creator><creatorcontrib>Gallimard, L. ; Florentin, E. ; Ryckelynck, D.</creatorcontrib><description>Summary Structural reliability methods aim at computing the probability of failure of systems with respect to prescribed limit state functions. A common practice to evaluate these limit state functions is using Monte Carlo simulations. The main drawback of this approach is the computational cost, because it requires computing a large number of deterministic finite element solutions. Surrogate models, which are built from a limited number of runs of the original model, have been developed, as substitute of the original model, to reduce the computational cost. However, these surrogate models, while decreasing drastically the computational cost, may fail in computing an accurate failure probability. In this paper, we focus on the control of the error introduced by a reduced basis surrogate model on the computation of the failure probability obtained by a Monte Carlo simulation. We propose a technique to determine bounds of this failure probability, as well as a strategy of enrichment of the reduced basis, based on limiting the bounds of the error of the failure probability for a multi‐material elastic structure. Copyright © 2017 John Wiley &amp; Sons, Ltd.</description><identifier>ISSN: 0029-5981</identifier><identifier>EISSN: 1097-0207</identifier><identifier>DOI: 10.1002/nme.5554</identifier><language>eng</language><publisher>Bognor Regis: Wiley Subscription Services, Inc</publisher><subject>Computational efficiency ; Computer simulation ; Computing costs ; Condensed Matter ; error bounds ; Errors ; Failure ; failure probability ; finite element analysis ; Finite element method ; Materials Science ; Mathematical models ; model reduction ; Monte Carlo simulation ; Optimization algorithms ; Physics ; reduced basis ; Reliability engineering ; Structural reliability</subject><ispartof>International journal for numerical methods in engineering, 2017-11, Vol.112 (9), p.1216-1234</ispartof><rights>Copyright © 2017 John Wiley &amp; Sons, Ltd.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3614-adfd02049ef5a7a48394c200769c0b09f70e3de226af1ba4b34f7537430255c73</citedby><cites>FETCH-LOGICAL-c3614-adfd02049ef5a7a48394c200769c0b09f70e3de226af1ba4b34f7537430255c73</cites><orcidid>0000-0003-1853-5444 ; 0000-0003-1192-6733 ; 0000-0003-3268-4892</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://minesparis-psl.hal.science/hal-01633909$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Gallimard, L.</creatorcontrib><creatorcontrib>Florentin, E.</creatorcontrib><creatorcontrib>Ryckelynck, D.</creatorcontrib><title>Towards error bounds of the failure probability of elastic structures using reduced basis models</title><title>International journal for numerical methods in engineering</title><description>Summary Structural reliability methods aim at computing the probability of failure of systems with respect to prescribed limit state functions. A common practice to evaluate these limit state functions is using Monte Carlo simulations. The main drawback of this approach is the computational cost, because it requires computing a large number of deterministic finite element solutions. Surrogate models, which are built from a limited number of runs of the original model, have been developed, as substitute of the original model, to reduce the computational cost. However, these surrogate models, while decreasing drastically the computational cost, may fail in computing an accurate failure probability. In this paper, we focus on the control of the error introduced by a reduced basis surrogate model on the computation of the failure probability obtained by a Monte Carlo simulation. We propose a technique to determine bounds of this failure probability, as well as a strategy of enrichment of the reduced basis, based on limiting the bounds of the error of the failure probability for a multi‐material elastic structure. Copyright © 2017 John Wiley &amp; Sons, Ltd.</description><subject>Computational efficiency</subject><subject>Computer simulation</subject><subject>Computing costs</subject><subject>Condensed Matter</subject><subject>error bounds</subject><subject>Errors</subject><subject>Failure</subject><subject>failure probability</subject><subject>finite element analysis</subject><subject>Finite element method</subject><subject>Materials Science</subject><subject>Mathematical models</subject><subject>model reduction</subject><subject>Monte Carlo simulation</subject><subject>Optimization algorithms</subject><subject>Physics</subject><subject>reduced basis</subject><subject>Reliability engineering</subject><subject>Structural reliability</subject><issn>0029-5981</issn><issn>1097-0207</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp10EFLwzAUB_AgCs4p-BECXvTQ-dI07XIcYzph6mWeY5omLqNrZtI69u1NrXjz9Mh7Px4vf4SuCUwIQHrf7PSEMZadoBEBXiSQQnGKRnHEE8an5BxdhLAFIIQBHaH3tTtIXwWsvXcel65r4sMZ3G40NtLWndd4710pS1vb9tiPdC1DaxUOre9UG0HAXbDNB_a66pSucCmDDXjnKl2HS3RmZB301W8do7eHxXq-TFavj0_z2SpRNCdZIitTxVMzrg2ThcymlGcqBShyrqAEbgrQtNJpmktDSpmVNDMFo0VGIWVMFXSM7oa9G1mLvbc76Y_CSSuWs5Xoe0BySjnwLxLtzWDjxz47HVqxdZ1v4nmC8BwI4zylUd0OSnkXgtfmby0B0WctYtaizzrSZKAHW-vjv068PC9-_Dcm-n9P</recordid><startdate>20171130</startdate><enddate>20171130</enddate><creator>Gallimard, L.</creator><creator>Florentin, E.</creator><creator>Ryckelynck, D.</creator><general>Wiley Subscription Services, Inc</general><general>Wiley</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0003-1853-5444</orcidid><orcidid>https://orcid.org/0000-0003-1192-6733</orcidid><orcidid>https://orcid.org/0000-0003-3268-4892</orcidid></search><sort><creationdate>20171130</creationdate><title>Towards error bounds of the failure probability of elastic structures using reduced basis models</title><author>Gallimard, L. ; Florentin, E. ; Ryckelynck, D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3614-adfd02049ef5a7a48394c200769c0b09f70e3de226af1ba4b34f7537430255c73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Computational efficiency</topic><topic>Computer simulation</topic><topic>Computing costs</topic><topic>Condensed Matter</topic><topic>error bounds</topic><topic>Errors</topic><topic>Failure</topic><topic>failure probability</topic><topic>finite element analysis</topic><topic>Finite element method</topic><topic>Materials Science</topic><topic>Mathematical models</topic><topic>model reduction</topic><topic>Monte Carlo simulation</topic><topic>Optimization algorithms</topic><topic>Physics</topic><topic>reduced basis</topic><topic>Reliability engineering</topic><topic>Structural reliability</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gallimard, L.</creatorcontrib><creatorcontrib>Florentin, E.</creatorcontrib><creatorcontrib>Ryckelynck, D.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>International journal for numerical methods in engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gallimard, L.</au><au>Florentin, E.</au><au>Ryckelynck, D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Towards error bounds of the failure probability of elastic structures using reduced basis models</atitle><jtitle>International journal for numerical methods in engineering</jtitle><date>2017-11-30</date><risdate>2017</risdate><volume>112</volume><issue>9</issue><spage>1216</spage><epage>1234</epage><pages>1216-1234</pages><issn>0029-5981</issn><eissn>1097-0207</eissn><abstract>Summary Structural reliability methods aim at computing the probability of failure of systems with respect to prescribed limit state functions. A common practice to evaluate these limit state functions is using Monte Carlo simulations. The main drawback of this approach is the computational cost, because it requires computing a large number of deterministic finite element solutions. Surrogate models, which are built from a limited number of runs of the original model, have been developed, as substitute of the original model, to reduce the computational cost. However, these surrogate models, while decreasing drastically the computational cost, may fail in computing an accurate failure probability. In this paper, we focus on the control of the error introduced by a reduced basis surrogate model on the computation of the failure probability obtained by a Monte Carlo simulation. We propose a technique to determine bounds of this failure probability, as well as a strategy of enrichment of the reduced basis, based on limiting the bounds of the error of the failure probability for a multi‐material elastic structure. Copyright © 2017 John Wiley &amp; Sons, Ltd.</abstract><cop>Bognor Regis</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/nme.5554</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0003-1853-5444</orcidid><orcidid>https://orcid.org/0000-0003-1192-6733</orcidid><orcidid>https://orcid.org/0000-0003-3268-4892</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0029-5981
ispartof International journal for numerical methods in engineering, 2017-11, Vol.112 (9), p.1216-1234
issn 0029-5981
1097-0207
language eng
recordid cdi_hal_primary_oai_HAL_hal_01633909v1
source Wiley
subjects Computational efficiency
Computer simulation
Computing costs
Condensed Matter
error bounds
Errors
Failure
failure probability
finite element analysis
Finite element method
Materials Science
Mathematical models
model reduction
Monte Carlo simulation
Optimization algorithms
Physics
reduced basis
Reliability engineering
Structural reliability
title Towards error bounds of the failure probability of elastic structures using reduced basis models
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T02%3A32%3A44IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_hal_p&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Towards%20error%20bounds%20of%20the%20failure%20probability%20of%20elastic%20structures%20using%20reduced%20basis%20models&rft.jtitle=International%20journal%20for%20numerical%20methods%20in%20engineering&rft.au=Gallimard,%20L.&rft.date=2017-11-30&rft.volume=112&rft.issue=9&rft.spage=1216&rft.epage=1234&rft.pages=1216-1234&rft.issn=0029-5981&rft.eissn=1097-0207&rft_id=info:doi/10.1002/nme.5554&rft_dat=%3Cproquest_hal_p%3E1960159923%3C/proquest_hal_p%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c3614-adfd02049ef5a7a48394c200769c0b09f70e3de226af1ba4b34f7537430255c73%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1960159923&rft_id=info:pmid/&rfr_iscdi=true