Process Optimization And Springback Control For Thermoforming Of 7055 Aluminum Alloy

On the premise of meeting the reliability requirements,in order to achieve the lightweight design requirements of the transportation industry for energy saving and emission reduction,it’s an effective measure that using high-strength,low-density and resource-rich aluminum alloy to replace traditional steel.This paper is aimed at the problem of poor plastic deformation ability during cold forming and large springback after forming of high-strength aluminum alloy.Taking 7055 aluminum alloy as the research object,the mechanical behavior of the material under hot deformation and the thermoforming processing of a double-C part are investigated.The main content is as follows:Tensile tests were performed on 7055 aluminum alloy at different temperatures and strain rates,and the influence of temperature and strain rate on flow stress and elongation of the material was analyzed.The Arrhenius and modified Johnson-Cook constitutive models were established to characterize the thermal deformation mechanical properties of the material in the range of 300-400℃.The results showed that the modified Johnson-Cook constitutive model has a higher accuracy and can describe the mechanical behavior of the material under hot deformation more accurately.The user material subroutine VUMAT of a more accurate constitutive model was developed with FORTRAN language.The subroutine was embedded into finite element software of ABAQUS to provide material basis for numerical simulation,and the correctness of the subroutine was verified through hot stretch simulation.The finite element model of thermoforming and springback process was established in ABAQUS,and the springback principle and evaluation method were investigated.The process analysis of the double-C part for 7055 aluminum alloy under thermoforming was carried out by orthogonal test method.The influence of each process parameter on the maximum thinning rate and springback value was studied,and the key process parameters affecting forming and springback were determined.An improved Kriging surrogate model with adaptive dynamic updating was proposed and applied to the optimization of the thermoforming processing for the double-C part.Firstly,the parameter of stochastic process part in the original Kriging model was optimized.Secondly,the particle swarm algorithm was used to solve MSP and EI sampling criterion to realize the dynamic updating of sample points.The high-efficiency characteristics of the hybrid sampling criterion were verified with three classical nonlinear function.Finally,based on the improved Kriging model with dynamic updating,the thermoforming process of the double-C part was optimized.Taking forming process parameters as design variables,thinning rate and springback as optimization targets,a Kriging model between process parameters and forming quality was established,and the multi-objective genetic algorithm was used to optimize the optimal process parameters.The optimal process parameters obtained by simulation was verified through the thermoforming experiment of the double-C part,and the results showed that the optimization method effectively reduced the maximum thinning rate and springback value,thereby improving the forming quality of the formed parts.