中国机械工程 ›› 2022, Vol. 33 ›› Issue (07): 864-871.DOI: 10.3969/j.issn.1004-132X.2022.07.014

• 先进材料加工工程 • 上一篇    下一篇

考虑热塑性变形的316H不锈钢Johnson-Cook本构参数逆向识别

李秀儒1;魏兆成1;郭明龙1;王敏杰1;郭江1;高伟2;孙昉2   

  1. 1.大连理工大学精密与特种加工教育部重点实验室,大连,116024
    2.陆军装备部大连军代室,大连,116010
  • 出版日期:2022-04-10 发布日期:2022-05-04
  • 通讯作者: 魏兆成(通信作者),男,1981年生,副教授。研究方向为切削理论与技术、先进加工工艺与刀具。发表论文46篇。E-mail:wei_zhaocheng@dlut.edu.cn。
  • 作者简介:李秀儒,男,1995年生,博士研究生。研究方向为切削加工机理、表面质量。发表论文2篇。E-mail:lixiuru@mail.dlut.edu.cn。
  • 基金资助:
    国家重点研发计划(2018YFA0702900);
    国家自然科学基金(U1908231)

Reverse Identification of Johnson-Cook Constitutive Parameters of 316H Stainless Steels Considering Thermoplastic Deformations

LI Xiuru1;WEI Zhaocheng1;GUO Minglong1;WANG Minjie1;GUO Jiang1;GAO Wei2;SUN Fang2   

  1. 1.Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education,Dalian University of Technology,Dalian,Liaoning,116024
    2.Dalian Military Representative Office of the Army Equipment Department,Dalian,Liaoning,116010
  • Online:2022-04-10 Published:2022-05-04

摘要: 本构模型能表征材料变形过程中的动态响应,其精度对机械加工中切削力、切削温度的解析预测具有决定性作用。针对316H不锈钢本构模型缺失问题,提出一种基于切削理论的Johnson-Cook本构参数逆向识别方法。通过建立的不等分主剪切区的应力、应变、应变率及温度分布的数学模型,以及准静态压缩试验和正交切削试验的数据,采用粒子群算法逆向识别出316H不锈钢的本构参数。切削力预测模型验证了该逆向识别方法的可行性和本构模型的可靠性。

关键词: 316H不锈钢, 本构模型, 逆向识别, 不等分剪切区, 摩擦因数

Abstract: The constitutive model might characterize the dynamic response of materials in the deformation processes, and the accuracy of constitutive model played a determinant role in analytical prediction of cutting forces, cutting temperature in machining. Aiming at the problems of lack for constitutive model of 316H stainless steels, a Johnson-Cook(J-C) constitutive parameter reverse identification method was proposed based on metal cutting theory. By establishing mathematics models of stress, strain, strain rate, and temperature distribution in unequal principal shear zones, and combining with the data of quasi-static compression tests and orthogonal cutting tests, the constitutive parameters of 316H stainless steel were reversely identified by particle swarm optimization algorithm. The cutting force prediction model was used to verify the feasibility of the reverse identification method and the reliability of the constitutive model.

Key words: 316H stainless steel, constitutive model, reverse identification, unequal division shear zone model, coefficient of friction

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