Inverse Optimization Of Constitutive Parameter And Parameterized Simulation Of Compacting Forming Of Powder Metallury Parts

In order to shorten the design period,reduce the cost of product and improve the quality of powder metallurgy products,it is an inevitable trend to introduce the numerical simulation technology into the process design and predict the defects in the process of powder forming.The accurate constitutive model is needed for the numerical simulation of powder compaction.At present,the constitutive model based on generalized plastic mechanics has better accuracy in numerical simulation of powder forming.However,due to the complexity of the model and more parameters,it is generally necessary to determine the parameters in the constitutive model by a variety of billet strength experiments,molding experiments and three axis experiments.In this paper,an inverse optimization method for parameters of generalized plastic mechanics model is proposed to achieve fast acquisition of constitutive model parameters.In order to improve the modeling efficiency,the model is parameterized based on the two development of ABAQUS in Python language.The main contents and results of this paper are as follows:1.A density dependent generalized plastic yielding model suitable for the forming of metal materials used in this paper is established,namely the modified Drucker-Prager Cap yield model.Using the ASC100.29 metal powder as the experimental material,the material parameters are calibrated by molding test,Brazil disc experiment and uniaxial compression test.The curves of the Brazil disk experiment and the uniaxial compression test are analyzed.2.Based on the ABAQUS-MATLAB joint simulation platform,using the composite optimization algorithm,the objective function is formed by the difference between numerical simulation and experimental oppression data,and it is minimized and the parameters of the constitutive model are obtained.Taking ASC100.29 metal powder as an example,the material parameters are retrieved and optimized.The results show that the optimized material parameters are basically consistent with the parameters obtained from the experiment.The optimized forming pressing force is basically consistent with the experimental curve,and the accuracy of the optimization method is verified.The material parameters of Ag57.6-Cu22.4-Sn10-In10 mixed metal powder are optimized.The simulation results of compacting force and relative density of powder forming are compared with the experimental results,and the feasibility of the combined inversion optimization method is further verified.3.Based on the two development of ABAQUS in Python language,the model is parameterized,and the research variables can be changed by changing the key parameters,so that a lot of repetitive modeling work can be avoided and the model of different sizes can be set up quickly.