基于混合硬化模型的Ti-6Al-4V低周疲劳损伤分析

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英文篇名：Analysis on low cycle fatigue damage of Ti-6Al-4V based on combined hardening model 作者：宋松 ; 韩永典 ; 徐连勇 ; 荆洪阳 ; 赵雷 英文作者：SONG Song;HAN Yongdian;XU Lianyong;JING Hongyang;ZHAO Lei;School of Materials Science and Engineering,Tianjin University;Tianjin Key Laboratory of Advanced Joining Technology;State Key Laboratory of Engine Combustion; 关键词：连续损伤力学 ; 损伤本构模型 ; 混合硬化模型 ; 有限元模拟 ; 疲劳寿命预测 英文关键词：continuum damage mechanics;;damage constitutive model;;combined hardening model;;finite element simulation;;fatigue life prediction 中文刊名：HJXB 英文刊名：Transactions of the China Welding Institution 机构：天津大学材料科学与工程学院;天津市现代连接技术重点实验室;天津大学内燃机燃烧学国家重点实验室; 出版日期：2019-01-25 出版单位：焊接学报 年：2019 期：v.40 基金：国家自然科学基金资助项目(51475326) 语种：中文; 页：HJXB201901009 页数：7 CN：01 ISSN：23-1178/TG 分类号：49-54+169

摘要

以连续损伤力学(CDM)为基础,根据Ti-6Al-4V钛合金应变疲劳试验结果,改进了Krajcinovic和Lemaitre提出的损伤本构模型,并拟合确定了损伤模型参数;将该损伤本构模型编写为USDFLD子程序并耦合到ABAQUS有限元软件中.使用Chaboche非线性随动强化和非线性各向同性硬化的混合硬化模型来描述Ti-6Al-4V钛合金的弹塑性行为,并拟合确定了混合硬化模型参数.模拟了材料在不同应变幅下的低周疲劳损伤演化.结果表明,损伤模型预测寿命和试验寿命吻合较好,对比试验和模拟结果可以发现,损伤模型预测寿命的平均误差为3.878%.
        The damage constitutive model proposed by Krajcinovic and Lemaitre was improved according to the result of the strain fatigue tests of Ti-6Al-4V titanium alloy based on the continuum damage mechanics(CMD),then parameters of the damage model were determined through fitting the strain fatigue data.The damage model was compiled into USDFLD subroutine,then this USDFLD subroutine was coupled into ABAQUS software.The combined hardening model mixed with Chaboche nonlinear kinematic hardening and nonlinear isotropic hardening was used to describe the elastic and plastic behavior,the parameters of the combined hardening model were determined through fitting the strain fatigue data.The fatigue damage evolutions of the material under different strain amplitude were simulated.The experiment results showed that the prediction life based on the damage model was in good agreement with the experimental life.Comparing the results of experiments and simulations,the average error was 3.878%.

引文

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