Smart Design and Manufacturing the Welded Q350 Steel Frames via Lifecycle Management Strategy of Digital Twin

作     者：Letian Fan Xinchao Wang Yongsheng Chen Li Wang Shumi Liu Yuanfei Wang Xinwei Li Kun Du Jia Zhang Xingyu Gao Feng Sun Haifeng Song William Yi Wang Jinshan Li Letian Fan;Xinchao Wang;Yongsheng Chen;Li Wang;Shumi Liu;Yuanfei Wang;Xinwei Li;Kun Du;Jia Zhang;Xingyu Gao;Feng Sun;Haifeng Song;William Yi Wang;Jinshan Li

作者机构：R&D CenterCRRC Tangshan Co.Ltd.Tangshan 063035HebeiChina Innovation CentreNPU ChongqingChongqing 401135China State Key Laboratory of Solidification ProcessingNorthwestern Polytechnical UniversityXi’an 710072China Western Superconducting Technologies Co.Ltd.Xi’an 710018China Chongqing Ti-master Co.LtdChongqing 401135China Laboratory of Computational PhysicsInstitute of Applied Physics and Computational MathematicsBeijing 100088China 

出 版 物：《Journal of Beijing Institute of Technology》 (北京理工大学学报（英文版）)

年 卷 期：2023年第32卷第4期

页      面：385-395页

核心收录：

学科分类：12[管理学] 080503[工学-材料加工工程] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 080201[工学-机械制造及其自动化] 

基　　金：supported by the National Basic Scientific Research Project of China (No.JCKY2020607B003) CRRC (No.202CDA001) 

主　　题：fatigue intelligent manufacturing integrated computational materials engineering(ICME) digital twin machine learning 

摘      要：Artificial intelligent aided design and manufacturing have been recognized as one kind of robust data-driven and data-intensive technologies in the integrated computational material engi-neering(ICME)*** by the dramatical developments of the services of China Railway High-speed series for more than a decade,it is essential to reveal the foundations of lifecycle man-agement of those trains under environmental ***,the smart design and manufacturing of welded Q350 steel frames of CR200J series are introduced,presenting the capability and opportu-nity of ICME in weight reduction and lifecycle management at a cost-effective *** order to address the required fatigue life time enduring more than 9×10^(6)km,the response of optimized frames to the static and the dynamic loads are comprehensively *** is highlighted that the maximum residual stress of the optimized welded frame is reduced to 69 MPa from 477 MPa of previous existing *** on the measured stress and acceleration from the railways,the fatigue life of modified frame under various loading modes could fulfil the requirements of the lifecycle ***,our recent developed intelligent quality control strategy of welding process mediated by machine learning is also introduced,envisioning its application in the intelligent weld-ing.