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Bammann-Chiesa-Johnson粘塑性本构模型的参数识别方法与验证 被引量:4
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作者 周婷婷 王罡 +2 位作者 杨洋 李遥 帅茂兵 《材料导报》 EI CAS CSCD 北大核心 2017年第3期75-79,111,共6页
Bammann-Chiesa-Johnson(BCJ)粘塑性本构模型对材料力学响应的再现和预测能力强烈依赖于其模型参数的确定,而模型参数的确定往往是通过反分析方法来进行。由于BCJ粘塑性模型包含了应变、应变率和温度耦合效应以及加载路径和温度历史,其... Bammann-Chiesa-Johnson(BCJ)粘塑性本构模型对材料力学响应的再现和预测能力强烈依赖于其模型参数的确定,而模型参数的确定往往是通过反分析方法来进行。由于BCJ粘塑性模型包含了应变、应变率和温度耦合效应以及加载路径和温度历史,其常数多达18个,所以寻找最佳的模型参数识别值十分繁琐。针对BCJ本构模型参数复杂、识别困难的问题,本文基于参数的物理意义,在准静态、蠕变及动态加载试验基础上,通过模型参数解耦分离、粒子群智能优化的方法分6步对18个材料常数进行识别,并用识别结果对1060纯铝动态加载试验力学响应进行模拟,模拟结果与试验结果符合良好。通过定量化误差分析,证明了BCJ粘塑性模型对实验数据的预测具有较高精度,该模型参数识别方法科学可行。 展开更多
关键词 BCJ粘塑性模型 参数识别 参数解耦 粒子群智能优化算法 1060纯铝
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Damage smoothing effects in a delocalized rate sensitivity model for metals
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作者 K.Enakoutsa K.N.Solanki +2 位作者 F.R.Ahad Y.Tjiptowidjojo D.J.Bammann 《Theoretical & Applied Mechanics Letters》 CAS 2012年第5期18-22,共5页
It has been long time established that application of damage delocalization method to softening constitutive models yields numerical results that are independent of the size of the finite element. However, the predict... It has been long time established that application of damage delocalization method to softening constitutive models yields numerical results that are independent of the size of the finite element. However, the prediction of real-world large and small scale problems using the delocalization method remains in its infancy. One of the drawbacks encountered is that the predicted load versus displacement curve suddenly drops, as a result of excessive smoothing of the damage. The present paper studies this unwanted effect for a delocalized plasticity/damage model for metallic materials. We use some theoretical arguments to explain the failure of the delocalized model considered, following which a simple remedy is proposed to deal with it. Future works involve the numerical implementation of the new version reproduce real-world problems. 展开更多
关键词 bammann-chiesa-johnson model damage smoothing Fourier transform SOFTENING
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