A method based on dynamic RBF surrogate model and particle swarm optimization algorithm was proposed. Material constitutive parameters of sheet metal stamping springback included the elastic modulus, strength coefficient, hardening exponent and anisotropy coefficient, etc. The springback simulation accuracy was improved by reversing the correct material parameters.Taking numisheet 96 S-rail for an example, the main material parameters regarded as reverse variables were screened through the orthogonal experiment design and grey relation analysis. Based on the target of difference between experiment and simulation values of Z coordinate springback of one section, the reverse result of material constitutive parameters was obversed through optimization. The results show that by using the reversed material parameters for S-rail springback simulation, the simulation accuracy is obviously improved,and also the inverse efficiency can be guaranteed. Compared the test results of two cross sections with simulation results, it shows that the result is effective, and also this method is of feasibility.
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