A De-Nesting Hybrid Reliability Analysis Method and Its Application in Marine Structure
In recent years, marine structures have been widely used in the world, making significant contributions to the utilization of marine resources. In the design of marine structures, there is a hybrid reliability problem arising from aleatory uncertainty and epistemic uncertainty. In many cases, episte...
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Veröffentlicht in: | Journal of marine science and engineering 2024-12, Vol.12 (12), p.2221 |
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description | In recent years, marine structures have been widely used in the world, making significant contributions to the utilization of marine resources. In the design of marine structures, there is a hybrid reliability problem arising from aleatory uncertainty and epistemic uncertainty. In many cases, epistemic uncertainty is estimated by interval parameters. Traditional methods for hybrid reliability analysis usually require a nested optimization framework, which will lead to too many calls to the limit state function (LSF) and result in poor computational efficiency. In response to this problem, this paper proposes a de-nesting hybrid reliability analysis method creatively. Firstly, it uses the p-box model to describe the epistemic uncertainty variables, and then the linear approximation (LA) model and the two-point adaptive nonlinear approximation (TANA) model are combined to approximate the upper and lower bounds of LSF with epistemic uncertainty. Based on the first-order reliability method (FORM), an iterative operation is used to obtain the interval of the non-probability hybrid reliability index. The traditional nested optimization structure is effectively eliminated by the above approximation method, which efficiently reduces the times of LSF calls and increases the calculation speed while preserving sufficient accuracy. Finally, one numerical example and two engineering examples are provided to show the greater effectiveness of this method than the traditional nested optimization method. |
doi_str_mv | 10.3390/jmse12122221 |
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In the design of marine structures, there is a hybrid reliability problem arising from aleatory uncertainty and epistemic uncertainty. In many cases, epistemic uncertainty is estimated by interval parameters. Traditional methods for hybrid reliability analysis usually require a nested optimization framework, which will lead to too many calls to the limit state function (LSF) and result in poor computational efficiency. In response to this problem, this paper proposes a de-nesting hybrid reliability analysis method creatively. Firstly, it uses the p-box model to describe the epistemic uncertainty variables, and then the linear approximation (LA) model and the two-point adaptive nonlinear approximation (TANA) model are combined to approximate the upper and lower bounds of LSF with epistemic uncertainty. Based on the first-order reliability method (FORM), an iterative operation is used to obtain the interval of the non-probability hybrid reliability index. The traditional nested optimization structure is effectively eliminated by the above approximation method, which efficiently reduces the times of LSF calls and increases the calculation speed while preserving sufficient accuracy. Finally, one numerical example and two engineering examples are provided to show the greater effectiveness of this method than the traditional nested optimization method.</description><identifier>EISSN: 2077-1312</identifier><identifier>DOI: 10.3390/jmse12122221</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Approximation ; Approximation method ; approximation model ; Collaboration ; de-nesting ; Engineering ; Epistemology ; FORM ; Iterative methods ; Limit states ; Lower bounds ; Marine resources ; marine structure ; Nesting ; Offshore structures ; Optimization ; Parameter estimation ; Parameter uncertainty ; Random variables ; Reliability ; Reliability analysis ; Structural reliability ; Uncertainty ; Uncertainty analysis</subject><ispartof>Journal of marine science and engineering, 2024-12, Vol.12 (12), p.2221</ispartof><rights>2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,864,2102,27924,27925</link.rule.ids></links><search><creatorcontrib>Li, Chenfeng</creatorcontrib><creatorcontrib>Jin, Tenglong</creatorcontrib><creatorcontrib>Chen, Zequan</creatorcontrib><creatorcontrib>Guanchen Wei</creatorcontrib><title>A De-Nesting Hybrid Reliability Analysis Method and Its Application in Marine Structure</title><title>Journal of marine science and engineering</title><description>In recent years, marine structures have been widely used in the world, making significant contributions to the utilization of marine resources. In the design of marine structures, there is a hybrid reliability problem arising from aleatory uncertainty and epistemic uncertainty. In many cases, epistemic uncertainty is estimated by interval parameters. Traditional methods for hybrid reliability analysis usually require a nested optimization framework, which will lead to too many calls to the limit state function (LSF) and result in poor computational efficiency. In response to this problem, this paper proposes a de-nesting hybrid reliability analysis method creatively. Firstly, it uses the p-box model to describe the epistemic uncertainty variables, and then the linear approximation (LA) model and the two-point adaptive nonlinear approximation (TANA) model are combined to approximate the upper and lower bounds of LSF with epistemic uncertainty. Based on the first-order reliability method (FORM), an iterative operation is used to obtain the interval of the non-probability hybrid reliability index. The traditional nested optimization structure is effectively eliminated by the above approximation method, which efficiently reduces the times of LSF calls and increases the calculation speed while preserving sufficient accuracy. Finally, one numerical example and two engineering examples are provided to show the greater effectiveness of this method than the traditional nested optimization method.</description><subject>Approximation</subject><subject>Approximation method</subject><subject>approximation model</subject><subject>Collaboration</subject><subject>de-nesting</subject><subject>Engineering</subject><subject>Epistemology</subject><subject>FORM</subject><subject>Iterative methods</subject><subject>Limit states</subject><subject>Lower bounds</subject><subject>Marine resources</subject><subject>marine structure</subject><subject>Nesting</subject><subject>Offshore structures</subject><subject>Optimization</subject><subject>Parameter estimation</subject><subject>Parameter uncertainty</subject><subject>Random variables</subject><subject>Reliability</subject><subject>Reliability analysis</subject><subject>Structural reliability</subject><subject>Uncertainty</subject><subject>Uncertainty analysis</subject><issn>2077-1312</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNotkM1KxDAYRYMgOIyz8wECrqv5kjZNlmX8mQFHwR9cli9pOqZ02pq0i3l7q-PdXLiLA_cQcgXsRgjNbptDdMCBz4EzsuAszxMQwC_IKsaGzVFcApML8lnQO5c8uzj6bk83RxN8RV9d69H41o9HWnTYHqOPdOfGr76i2FV0O0ZaDEPrLY6-76jv6A6D7xx9G8Nkxym4S3JeYxvd6r-X5OPh_n29SZ5eHrfr4impQHBIhJNK2rSuHWgBzGCqldIOjVJppkFoaWxuGHJQXDBja5kyZlxaq5znVZWJJdmeuFWPTTkEf8BwLHv05d_Qh32JYfS2daWdzRitM2Qc0swiGmZljpwZgBzUL-v6xBpC_z3NSsqmn8L8P5YCUi2lyGUqfgCwvGkm</recordid><startdate>20241201</startdate><enddate>20241201</enddate><creator>Li, Chenfeng</creator><creator>Jin, Tenglong</creator><creator>Chen, Zequan</creator><creator>Guanchen Wei</creator><general>MDPI AG</general><scope>7ST</scope><scope>7TN</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>H96</scope><scope>HCIFZ</scope><scope>L.G</scope><scope>L6V</scope><scope>M7S</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>SOI</scope><scope>DOA</scope></search><sort><creationdate>20241201</creationdate><title>A De-Nesting Hybrid Reliability Analysis Method and Its Application in Marine Structure</title><author>Li, Chenfeng ; Jin, Tenglong ; Chen, Zequan ; Guanchen Wei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-d1321-3e686c4ffe19310ba49889eab884591396bc7b0a218230bcf6400be4f8727dd53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Approximation</topic><topic>Approximation method</topic><topic>approximation model</topic><topic>Collaboration</topic><topic>de-nesting</topic><topic>Engineering</topic><topic>Epistemology</topic><topic>FORM</topic><topic>Iterative methods</topic><topic>Limit states</topic><topic>Lower bounds</topic><topic>Marine resources</topic><topic>marine structure</topic><topic>Nesting</topic><topic>Offshore structures</topic><topic>Optimization</topic><topic>Parameter estimation</topic><topic>Parameter uncertainty</topic><topic>Random variables</topic><topic>Reliability</topic><topic>Reliability analysis</topic><topic>Structural reliability</topic><topic>Uncertainty</topic><topic>Uncertainty analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Chenfeng</creatorcontrib><creatorcontrib>Jin, Tenglong</creatorcontrib><creatorcontrib>Chen, Zequan</creatorcontrib><creatorcontrib>Guanchen Wei</creatorcontrib><collection>Environment Abstracts</collection><collection>Oceanic Abstracts</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Environment Abstracts</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Journal of marine science and engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Chenfeng</au><au>Jin, Tenglong</au><au>Chen, Zequan</au><au>Guanchen Wei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A De-Nesting Hybrid Reliability Analysis Method and Its Application in Marine Structure</atitle><jtitle>Journal of marine science and engineering</jtitle><date>2024-12-01</date><risdate>2024</risdate><volume>12</volume><issue>12</issue><spage>2221</spage><pages>2221-</pages><eissn>2077-1312</eissn><abstract>In recent years, marine structures have been widely used in the world, making significant contributions to the utilization of marine resources. In the design of marine structures, there is a hybrid reliability problem arising from aleatory uncertainty and epistemic uncertainty. In many cases, epistemic uncertainty is estimated by interval parameters. Traditional methods for hybrid reliability analysis usually require a nested optimization framework, which will lead to too many calls to the limit state function (LSF) and result in poor computational efficiency. In response to this problem, this paper proposes a de-nesting hybrid reliability analysis method creatively. Firstly, it uses the p-box model to describe the epistemic uncertainty variables, and then the linear approximation (LA) model and the two-point adaptive nonlinear approximation (TANA) model are combined to approximate the upper and lower bounds of LSF with epistemic uncertainty. Based on the first-order reliability method (FORM), an iterative operation is used to obtain the interval of the non-probability hybrid reliability index. The traditional nested optimization structure is effectively eliminated by the above approximation method, which efficiently reduces the times of LSF calls and increases the calculation speed while preserving sufficient accuracy. Finally, one numerical example and two engineering examples are provided to show the greater effectiveness of this method than the traditional nested optimization method.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/jmse12122221</doi><oa>free_for_read</oa></addata></record> |
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subjects | Approximation Approximation method approximation model Collaboration de-nesting Engineering Epistemology FORM Iterative methods Limit states Lower bounds Marine resources marine structure Nesting Offshore structures Optimization Parameter estimation Parameter uncertainty Random variables Reliability Reliability analysis Structural reliability Uncertainty Uncertainty analysis |
title | A De-Nesting Hybrid Reliability Analysis Method and Its Application in Marine Structure |
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