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A new method was worked out to improve the precision of springback prediction in sheet metal forming by combining the finite element method (FEM) with the data mining (DM) technique. First the genetic algorithm (GA) was adopted for recognizing the material parameters. Then according to the even design idea, the suitable calculation scheme was confirmed, and FEM was used for calculating the springback. The computation results were compared with experiment data, the difference between them was taken as source data, and a new pattern recognition method of DM called hierarchical optimal map recognition method (HOMR) is applied for summarizing the calculation regulation in FEM. At the end, the mathematics model of the springback simulation was established.Based on the model, the calculation errors of springback can be controlled within 10 % compared with the experimental results. 相似文献
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Influences of Randomly Distributed Wall THickness of Beverage Can on Its Strength and Stiffness 总被引：1，自引：0，他引：1
This paper describes the research undertaken on the strength and stiffness of fluctuation on the wall thickness of steel beverage cans using the Monte-Carlo stochastic finite element method.Sample distributions were firestly assumed and then proven using the data observations of the wall thickness.the APDL language was then applied,and the stresses and displacements of the can were calculated by using the ANSYS software.It is concluded that the structureal reliability of a steel-making beverage can be estimated accurately. 相似文献
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1 Ｉｎｔｒｏｄｕｃｔｉｏｎ Ｔｈｅｓｔｒｅｓｓｉｎｔｅｎｓｉｔｙｆａｃｔｏｒ(ＳＩＦ)ｏｆｔｈｅｓｅｍｉｅｌｌｉｐｔｉｃａｌｓｕｒｆａｃｅｃｒａｃｋｎｅｅｄｓｔｏｂｅｃａｌｃｕｌａｔｅｄｆｏｒｅｖａｌｕａｔｉｎｇｔｈｅｓｔｒｅｎｇｔｈｏｆｍｅｔａｌｃｏｍｐｏｎｅｎｔｓｂｅｃａｕｓｅｍａｎｙｆｌａｗｓｏｃｃｕｒｏｎｔｈｅｃｏｍｐｏｎｅｎｔｓｕｒｆａｃｅｄｕｅｔｏｔｈｅｎａｎｕｆａｃｔｕｒｅａｎｄｔｒａｎｓｐｏｒｔｐｒｏｃｅｄｕｒｅ.Ｕｐｔｏｎｏｗ,ｓｏｌｖｉｎｇｔｈｒｅｅｄｉｍｅｎｓｉｏｎａｌｃｒａ… 相似文献
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