Neural Network Prediction of Nonlinear Elastic Unloading for High Strength Steel
نویسندگان
چکیده
In achieving accurate results, current nonlinear elastic recovery applications of finite element (FE) analysis have become more complicated for sheet metal springback prediction. In this paper, an artificial neural network (ANN) was used to mimic the nonlinear elastic recovery and provides a generalized solution in the FE analysis. The nonlinear elastic recovery was processed through back-propagation networks. This approach is able to perform pattern recognition and create direct mapping of the elastically-driven change after plastic deformation. The FE program for nonlinear elastic recovery experiment was carried out with the integration of ANN. The results obtained at the end of the FE analyses were closed to the measured data.
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