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- W2389980815 abstract "The test makes the high strength steel automotive longeron as reasearch object,takes the blank holder pressure,frictional coefficient and die fillet as test factors and gets the springback value along Y-axis as evaluation objectives.Uniform design experiment of FE simulation model is set up basing on what we've selected.Then a network prediction model of high strength steel automotive rail' s springback is created,being based on the analysis results.At last,better combination of parameters is found by using the network in the vicinity of the optimal combination of uniform design experiment.The results have been proved to be correct by using FEM simulation.The result shows that the neural network,numerical simulation and uniform pilot program can be combined to optimize the stamping process parameters.The time of parameters'optimization will be reduced obviously.At the same time the design-efficiency could be greatly increased." @default.
- W2389980815 created "2016-06-24" @default.
- W2389980815 creator A5049020202 @default.
- W2389980815 date "2010-01-01" @default.
- W2389980815 modified "2023-09-28" @default.
- W2389980815 title "Construction of a BP Neural Network Prediction Model of High Strength Steel Automotive Longeron's Springback" @default.
- W2389980815 hasPublicationYear "2010" @default.
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