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dc.contributor.authorLong, Houmin
dc.contributor.authorFan, Shenggang
dc.contributor.authorWang, Weiyong
dc.contributor.authorWu, Yiwen
dc.date.accessioned2026-08-20T11:44:05Z
dc.date.available2026-08-20T11:44:05Z
dc.date.copyright2026/04/21
dc.date.issued2026
dc.identifier.otherJMCEE7.MTENG-21862.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312600
dc.description.abstractAbstractThe development of structural engineering is closely tied to innovations in building materials. Austenitic stainless steel materials, known for their excellent corrosion resistance, durability, and high plasticity, are drawing growing attention ...A research framework for predicting the mechanical properties and constitutive model of austenitic stainless steel. It covers data preparation (chemical compositions, temperatures, mechanical properties, and stress–strain curves), methods (prediction of ...
dc.publisherAmerican Society of Civil Engineers
dc.titleMachine Learning–Based Prediction of the Constitutive Model of Austenitic Stainless Steels at Room and Elevated Temperatures
dc.typeJournal Article
dc.journal.volume38
dc.journal.issue7
dc.journal.titleJournal of Materials in Civil Engineering
dc.identifier.doi10.1061/JMCEE7.MTENG-21862
dc.journal.fristpage04026171-1
dc.journal.lastpage04026171-14
dc.page14
dc.treeJournal of Materials in Civil Engineering:;2026:;Volume ( 038 ):;issue: 007
dc.contenttypeFulltext


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