Journal of Shanghai Jiaotong University ›› 2017, Vol. 51 ›› Issue (11): 1340-1347.doi: 10.16183/j.cnki.jsjtu.2017.11.009

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The Loading Path Optimization for T-Shape Tube Hydroforming Using Adaptive Radial Basis Function

SONG Xuewei,MA Lingling,HUANG Tianlun,LIU Min   

  1. College of Automotive Engineering, Jilin University, Changchun 130022, China
  • Online:2017-11-30 Published:2017-11-30

Abstract: The study of surrogate model optimization of the loading path of a T-shape tube hydroforming is carried out in this paper. The adaptive optimization algorithm is introduced to radial basis function(RBF). In order to improve approximate accuracy in the concerned local regions, the paper proposes to add sample points gradually into the sample database, and to obtain the globally optimal efficiency and accuracy. The effectiveness of the method in global optimization is demonstrated by a numerical example firstly, then, adaptive radial basis function model for the T-shape tube hydroforming loading path optimization is constructed,and optimization design is carried out. The contact areas of the tube and the counter punch are selected to be the optimization target, the constraints are that the maximum thinning ratio is less than the experimental value, and the protrusion height is higher than the experimental value. The Latin hypercube design is used to obtain sample points, and the actual values of finite element analysis model of T-shape hydroforming are calculated. The loading path optimization design results are compared with the experimental values, and the result shows that the contact areas of T-shape tube and counter punch have improved by 71.912% under the condition that the minimum thickness and the protrusion height are maintained.

Key words: vehicle engineering, T-shape tube hydroforming, surrogate model, loading path optimization, adaptive radial basis function (RBF)

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