YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • ASCE
    • Journal of Materials in Civil Engineering
    • View Item
    •   YE&T Library
    • ASCE
    • Journal of Materials in Civil Engineering
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    Machine Learning–Based Prediction of the Constitutive Model of Austenitic Stainless Steels at Room and Elevated Temperatures

    Source: Journal of Materials in Civil Engineering:;2026:;Volume ( 038 ):;issue: 007::page 04026171-1
    Author:
    Long, Houmin
    ,
    Fan, Shenggang
    ,
    Wang, Weiyong
    ,
    Wu, Yiwen
    DOI: 10.1061/JMCEE7.MTENG-21862
    Publisher: American Society of Civil Engineers
    Abstract: AbstractThe 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 ...
    • Download: (2.255Mb)
    • Show Full MetaData Hide Full MetaData
    • Get RIS
    • Item Order
    • Go To Publisher
    • Statistics

      Machine Learning–Based Prediction of the Constitutive Model of Austenitic Stainless Steels at Room and Elevated Temperatures

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/4312600
    Collections
    • Journal of Materials in Civil Engineering

    Show full item record

    contributor authorLong, Houmin
    contributor authorFan, Shenggang
    contributor authorWang, Weiyong
    contributor authorWu, Yiwen
    date accessioned2026-08-20T11:44:05Z
    date available2026-08-20T11:44:05Z
    date copyright2026/04/21
    date issued2026
    identifier otherJMCEE7.MTENG-21862.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312600
    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 ...
    publisherAmerican Society of Civil Engineers
    titleMachine Learning–Based Prediction of the Constitutive Model of Austenitic Stainless Steels at Room and Elevated Temperatures
    typeJournal Article
    journal volume38
    journal issue7
    journal titleJournal of Materials in Civil Engineering
    identifier doi10.1061/JMCEE7.MTENG-21862
    journal fristpage04026171-1
    journal lastpage04026171-14
    page14
    treeJournal of Materials in Civil Engineering:;2026:;Volume ( 038 ):;issue: 007
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian