Machine learning informed visco-plastic model for the cyclic relaxation of 316H stainless steel at 550 °C
文献类型:期刊论文
作者 | Du R(杜柔); Song HX(宋恒旭); Gao, Fuhai; Mo, Yafei; Yan, Ziming; Zhuang, Zhuo; Liu XM(刘小明); Wei, Yueguang |
刊名 | INTERNATIONAL JOURNAL OF PLASTICITY |
出版日期 | 2023-11-01 |
卷号 | 170页码:23 |
ISSN号 | 0749-6419 |
关键词 | Cyclic relaxation High -temperature plasticity Visco-plastic constitutive model Bayesian method Fatigue and creep |
DOI | 10.1016/j.ijplas.2023.103743 |
英文摘要 | Among the structural alloys for this fast reactor, 316H stainless steel has emerged as a promising candidate. Because the operating temperature of Sodium-cooled reactor is specifically designed to be 550 degrees C, this operating temperature triggers material inelastic behavior depends more on the coupling of fatigue and creep, which complicates the constitutive model. By introducing static recovery terms, previous studies could capture some experimental features, but failed to describe the interaction by fatigue and creep. In this work, in order to describe the fatigue and creep during cyclic relaxation of 316H stainless steel at 550 degrees C, we propose a modified visco-plastic constitutive model within the framework of unified Chaboche model. In the proposed model, the parameters related to the static recovery items are coupled, and thus cannot be identified from experiments using the traditional trial and error. To address this issue, we employed the Bayesian approach to identify these parameters. The parameter identification involves two steps: (i) con-structing a Gaussian Process surrogate model using data generated from the finite element method, and (ii) obtaining the value of parameters through Markov Chain Monte Carlo sampling under the Bayesian framework. The proposed procedure, is demonstrated by the using experi-mental results of 316H stainless steel at 550 degrees C. Under the coupling of fatigue-creep, the material exhibits a cyclic-dependent accelerated stress relaxation before reaching the saturated stage and a steady state of relaxed stress after a long holding time. These mechanical responses are well predicted by the proposed model. Further, we conducted two kinds of multi-axial cyclic test, tensile test of notched bar and coupled tensile-torsion test, to validate the proposed constitutive model for the cyclic behavior under the multi-axial stress state. |
分类号 | 一类 |
WOS关键词 | CREEP-FATIGUE INTERACTION ; KINEMATIC HARDENING RULE ; NICKEL-BASE SUPERALLOY ; CONSTITUTIVE-EQUATIONS ; RATCHETING BEHAVIOR ; PLASTICITY ; DEFORMATION ; TEMPERATURE ; SIMULATION ; RESPONSES |
资助项目 | National Natural Science Foundation of China[12022210] ; National Natural Science Foundation of China[12032001] ; National Natural Science Foundation of China, Basic Science Center Program for Multiscale Problems in Nonlinear Mechanics[11988102] ; Youth Innovation Promotion Association CAS[2018022] |
WOS研究方向 | Engineering ; Materials Science ; Mechanics |
语种 | 英语 |
WOS记录号 | WOS:001145805100001 |
资助机构 | National Natural Science Foundation of China ; National Natural Science Foundation of China, Basic Science Center Program for Multiscale Problems in Nonlinear Mechanics ; Youth Innovation Promotion Association CAS |
其他责任者 | Liu, Xiaoming |
源URL | [http://dspace.imech.ac.cn/handle/311007/94151] |
专题 | 力学研究所_非线性力学国家重点实验室 |
推荐引用方式 GB/T 7714 | Du R,Song HX,Gao, Fuhai,et al. Machine learning informed visco-plastic model for the cyclic relaxation of 316H stainless steel at 550 °C[J]. INTERNATIONAL JOURNAL OF PLASTICITY,2023,170:23. |
APA | Du R.,Song HX.,Gao, Fuhai.,Mo, Yafei.,Yan, Ziming.,...&Wei, Yueguang.(2023).Machine learning informed visco-plastic model for the cyclic relaxation of 316H stainless steel at 550 °C.INTERNATIONAL JOURNAL OF PLASTICITY,170,23. |
MLA | Du R,et al."Machine learning informed visco-plastic model for the cyclic relaxation of 316H stainless steel at 550 °C".INTERNATIONAL JOURNAL OF PLASTICITY 170(2023):23. |
入库方式: OAI收割
来源:力学研究所
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