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摘要：
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将有限元模拟技术和神经网络理论相结合,建立了钛合金等温锻造工艺设计的优化系统,实现了CAD-CAE-优化-CAD的循环,在循环过程中,CAE对CAD产生了数据反馈。将FEM模拟结果作为初始数据导入优化系统,作为ANN的训练参数,利用训练好的神经网络对设计做出预测,循环系统不断运行直至得到良好的结果。利用该优化系统能获得像顶级专家主持一样的优良效果,使得设计过程在时间和效果上都得到提高。
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This research was aimed to develop an integrated methodology based on FEM simulation and artificial neural network (ANN) for optimization of isothermal forging process of Ti alloys. The cycle of CAD-CAE-OPTIMIZATION-CAD was realized. The results of CAE were introduced into a CAD environment during the cycle. The FEM simulation was first used to create training cases for the ANN, and the well-trained ANN was used to predict the performance of the design. The cycling work was done automatically until the results were acceptable, and the final design scheme would approach the optimal one with the experience and knowledge of top experts. The integrated approach is effective and time saving.
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基金项目：
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成都市科技攻关计划项目(07GGYB966GX-026)
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作者简介：
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参考文献：
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