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形状记忆合金超弹性本构关系的神经网络模型

A constitutive model for superelasticity of shape memory alloy based on neural network

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【作者】 崔迪李宏男宋钢兵

【Author】 CUI Di~1,LI Hong-nan~1,SONG Gang-bing~(1,2) (1.State Key Laboratory of Coastal and Offshore Engineering,Dalian University of Technology,Dalian 116024,China;2.Department of Mechanical Engineering,University of Houston,Houston,USA,77204)

【机构】 大连理工大学海岸和近海工程国家重点实验室大连理工大学海岸和近海工程国家重点实验室 辽宁大连116024辽宁大连116024美国休斯敦大学机械工程系美国休斯敦77204

【摘要】 通过试验,研究了受过循环变形、具有稳定超弹性变形性能的形状记忆合金丝在拉伸到不同应变幅值条件下卸载的超弹性变形行为。根据试验测得的结果,提出了基于神经网络的形状记忆合金超弹性本构关系模型,并把模型计算的结果和实验数据进行了比较分析,结果表明,该模型具有很高的精度。该模型避免了已有模型在参数确定上的困难,具有一定的工程应用价值,为建立形状记忆合金本构模型提供了一个新的思路。

【Abstract】 Superelasticity is one of the most important properties of shape memory alloy.In this paper,the superelastic deformation behavior of NiTi shape memory alloy subjected to cyclic loading with stable superelasticity is investigated experimentally.According to the test data,a constitutive model for the superelasticity of shape memory alloy is put forward based on artificial neural network.The numerical results agree well with experimental observations,which verifies the constitutive model has a high accuracy.With this model,the difficulties on the determination of the parameters for other models can be avoided,and which leads to a practical engineering application of this model.Thus,a new attempt is provided in the present paper for building the constitutive model of shape memory alloy.

【基金】 国家杰出青年科学基金资助(50025823);海外青年学者研究基金资助(50328807)
  • 【文献出处】 振动工程学报 ,Journal of Vibration Engineering , 编辑部邮箱 ,2006年01期
  • 【分类号】TG139.6
  • 【被引频次】5
  • 【下载频次】283
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