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Design Optimization for Cold Forging by an integrated Methodology of CAD/FEM/ANN

机译:CAD / FEM / ANN综合方法的冷锻设计优化

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In this paper, an integrated methodology of geometric modeling, finite element method (FEM) and artificial neural network (ANN) is proposed for design optimization of cold forging process. Forging processes with some key design variables are firstly simulated using rigid-plastic FEM so as to create training data for the ANN model. Then neural network model is used to predict for unseen data after being properly trained. Finally, some forging experiments are carried out to confirm the ANN prediction results, a good agreement is found between the predicted data and the measured results.
机译:本文提出了一种综合的几何建模,有限元法(FEM)和人工神经网络(ANN)的设计优化。使用刚性塑料FEM首先模拟具有一些关键设计变量的锻造过程,以便为ANN模型创建培训数据。然后,神经网络模型用于在经过适当培训后预测未经看不见的数据。最后,进行了一些锻造实验以确认ANN预测结果,在预测数据和测量结果之间发现了良好的一致性。

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