Machine learning informed visco-plastic model for the cyclic relaxation of 316H stainless steel at 550 °C
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
2023-11-01
卷号170页码:23
关键词Cyclic relaxation High -temperature plasticity Visco-plastic constitutive model Bayesian method Fatigue and creep
ISSN号0749-6419
DOI10.1016/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
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关键词CREEP-FATIGUE INTERACTION ; KINEMATIC HARDENING RULE ; NICKEL-BASE SUPERALLOY ; CONSTITUTIVE-EQUATIONS ; RATCHETING BEHAVIOR ; PLASTICITY ; DEFORMATION ; TEMPERATURE ; SIMULATION ; RESPONSES
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
内容类型期刊论文
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.
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