Simulation Of Forming Process And Development Of Process Emulation Module For Small Bending Beam Of Railway Vehicles

With the rapid development of the rail transit,people put forward new requirements for the manufacturing quality.As a numerical simulation method,the finite element method was widely used in the rail transit industry due to its powerful ability to solve the problems with nonlinear and complex boundary conditions.The time and production cost could be greatly reduced by using the finite element method to simulate the forming process and optimize process parameters of the small bending beam.The forming properties of the materials used for small bending beam are studied.The basic mechanical properties parameters of the materials used for small bending beam are determined by undirectional tensile test.The parameters of plastic criterion and fracture criterion for the material parameters are deduced.The forming process of the small bending beam is further analyzed.The simulation of the part is carried out by using Abaqus software.The forming performance is analyzed.By the process of finite element analysis of the small bending beam,the Python language is used for the secondary development of the Abaqus software.The forming simulation module suitable for the finite element analysis of small bending beam is designed to quickly establish the finite element model of small bending beam,fastly output thinning ratio cloud map and section parameters.Through the analysis of the forming process of small bending beam,the optimization process for the pressing parts is designed,and the simulation module is developed to improve the simulation efficiency.Taking the small bending beam as an example,the influence of different technological parameters on the forming results of the small bending beam is analyzed,and the optimum technological parameters and their adjusting range are determined.Considering the coupling effect among various factors,the orthogonal test method is used to determine the proportion of each factor's influence on the optimization target.The data of orthogonal experiment is used as the sample data of neural network training.The mapping relationship between process parameters and forming results is obtained by using neural network algorithm.The combination of process parameters is further optimized by combining genetic algorithm.Optimized process parameters is applied to simulate.The simulation results are compared with the experimental results,and the reliability of the numerical simulation and the optimization method is verified,which can provide some guidance for the actual production.