• CN:11-2187/TH
  • ISSN:0577-6686

›› 2003, Vol. 39 ›› Issue (3): 110-112.

• 论文 • 上一篇    下一篇

Hill非二次屈服准则次数m值识别及应变控制研究

吴建军;李祥   

  1. 西北工业大学飞行器制造工程系
  • 发布日期:2003-03-15

STUDY ON THE IDENTIFICATION OF THE m VALUE OF HILL’S NEW YIELD CRITERION AND THE CONTROL OF DEFORMATION PATH

Wu Jianjun;Li Xiang   

  1. Northwestern Polytechnical University
  • Published:2003-03-15

摘要: 正确确定本构模型中的物性参数是金属成形过程准确分析和模拟的基础。以Hill非二次屈服准则为基础,应用人工神经网络(ANN)技术建立了材料在变形过程中不同应力状态下物性参数m值的识别方法,并在MTS试验机上进行了薄壁管拉扭试验,通过试验中各阶段的实际应变增量值与m值识别前后计算所得理论应变增量值的比较,验证了识别所得m值以及根据识别所得m值进行应变控制的正确性。

关键词: 物性参数 人工神经网络 识别 应变控制

Abstract: It’s very essential to correctly determine the material parameter in constitutive model for appropriately analyzing and simulating the process of metal forming. Based on Hill’s new yield criterion, the approach of artificial neural networks is used to identify the material parameter m in variant stress states during the process of material deformation. By the experiment of tension and torsion test of thin walled tube on MTS , the experimental strain increment is obtained and compared with theoretical strain increment which obtained by simulation with m value 2 and the identified m value. The results of comparison validate the correctness of identified m and deformation control method using the identified m.

Key words: Artificial neural networks, Deformation control, Identification, Material parameter

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