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Cyclic Metal Plasticity Model Parameters with Limited Information: Constrained Optimization Approach
AbstractTensile test data for structural steels are ubiquitous. However, the information monotonic loading provides with respect to the material’s characteristics is limited. Notably, features of inelastic response to cyclic loading, such as the Bauschinger effect, cannot be determined without testi...
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Published in: | Journal of engineering mechanics 2021-07, Vol.147 (7) |
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creator | Castro e Sousa, Albano de Hartloper, Alexander R Lignos, Dimitrios G |
description | AbstractTensile test data for structural steels are ubiquitous. However, the information monotonic loading provides with respect to the material’s characteristics is limited. Notably, features of inelastic response to cyclic loading, such as the Bauschinger effect, cannot be determined without testing with a load reversal protocol. This study aimed at addressing this shortcoming by formulating a constrained optimization problem that provided best-fit material parameters to a tensile test while simultaneously imposing representative cyclic properties for structural steels. Recommendations on constraints were given. Results demonstrated that improvements can be achieved when compared to: (1) direct fits to tensile data and (2) input model parameters from the same steel material but from different batches calibrated to a wide range of strain-based protocols. Given the available data, it is concluded that simpler models with one backstress tend to perform best with the proposed constraints. |
doi_str_mv | 10.1061/(ASCE)EM.1943-7889.0001922 |
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Given the available data, it is concluded that simpler models with one backstress tend to perform best with the proposed constraints.</description><subject>Bauschinger effect</subject><subject>Constraints</subject><subject>Cyclic loads</subject><subject>Mathematical models</subject><subject>Optimization</subject><subject>Parameters</subject><subject>Structural steels</subject><subject>Technical Papers</subject><subject>Tensile tests</subject><issn>0733-9399</issn><issn>1943-7889</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp1kF1LwzAUhoMoOKf_oeiNXnTmo02T3Y1SdbAyQb0OaZqyjK6dSYbMX2_qpl55deA973MOPABcIzhBkKL729lLXtwV5QTxhMQZY3wCIUQc4xMw-s1OwQhmhMSccH4OLpxbh05COR2BOt-r1qio1F620XMrnTfK-H1U9rUOgbRyo722LvowfhUtzMZ4XUfzruntRnrTd9Mo7zvnrTRdWCy3PlQ-vzfRbLu1vVSrS3DWyNbpq-Mcg7eH4jV_ihfLx3k-W8SSMOZjhCVNqzStFEaM1SilGOqKVTjjVDFFmKwTipMKE4YbSXDKpawSSHGWBCKFZAxuDnfD2_eddl6s-53twkuBU8R4RrMkC63poaVs75zVjdhas5F2LxAUg1UhBquiKMVgUAwGxdFqgOkBlk7pv_M_5P_gF_xhfAU</recordid><startdate>20210701</startdate><enddate>20210701</enddate><creator>Castro e Sousa, Albano de</creator><creator>Hartloper, Alexander R</creator><creator>Lignos, Dimitrios G</creator><general>American Society of Civil Engineers</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><orcidid>https://orcid.org/0000-0003-0682-4660</orcidid><orcidid>https://orcid.org/0000-0003-3120-1748</orcidid></search><sort><creationdate>20210701</creationdate><title>Cyclic Metal Plasticity Model Parameters with Limited Information: Constrained Optimization Approach</title><author>Castro e Sousa, Albano de ; Hartloper, Alexander R ; Lignos, Dimitrios G</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a388t-12a65b55bc2188d15620eb8b2796c8c38ad4624b2382fa3259aab406274c21503</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Bauschinger effect</topic><topic>Constraints</topic><topic>Cyclic loads</topic><topic>Mathematical models</topic><topic>Optimization</topic><topic>Parameters</topic><topic>Structural steels</topic><topic>Technical Papers</topic><topic>Tensile tests</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Castro e Sousa, Albano de</creatorcontrib><creatorcontrib>Hartloper, Alexander R</creatorcontrib><creatorcontrib>Lignos, Dimitrios G</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Journal of engineering mechanics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Castro e Sousa, Albano de</au><au>Hartloper, Alexander R</au><au>Lignos, Dimitrios G</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cyclic Metal Plasticity Model Parameters with Limited Information: Constrained Optimization Approach</atitle><jtitle>Journal of engineering mechanics</jtitle><date>2021-07-01</date><risdate>2021</risdate><volume>147</volume><issue>7</issue><issn>0733-9399</issn><eissn>1943-7889</eissn><abstract>AbstractTensile test data for structural steels are ubiquitous. However, the information monotonic loading provides with respect to the material’s characteristics is limited. Notably, features of inelastic response to cyclic loading, such as the Bauschinger effect, cannot be determined without testing with a load reversal protocol. This study aimed at addressing this shortcoming by formulating a constrained optimization problem that provided best-fit material parameters to a tensile test while simultaneously imposing representative cyclic properties for structural steels. Recommendations on constraints were given. Results demonstrated that improvements can be achieved when compared to: (1) direct fits to tensile data and (2) input model parameters from the same steel material but from different batches calibrated to a wide range of strain-based protocols. 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subjects | Bauschinger effect Constraints Cyclic loads Mathematical models Optimization Parameters Structural steels Technical Papers Tensile tests |
title | Cyclic Metal Plasticity Model Parameters with Limited Information: Constrained Optimization Approach |
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