Modeling the powder compaction process by an integrated simulation and inverse optimization method

Abstract

A method of integrated modeling using the inverse optimization was proposed to simulate the compaction process of metal powders in this work. By using the present work, one can alleviate the time consuming and expensive experiment, and the material parameters can be determined more accurately. The constitutive parameters of the modified Drucker-Prager Cap model were identified using finite element simulations in ABAQUS- iSIGHT integrated environment. The downhill simplex optimization method has been used to predict the material parameters in a way to minimize the differences between experimental and simulation result of uniaxial powder compaction. The accuracy of inverse parameters has been validated as the powder Distaloy AE, while the sensitivity of the plasticity parameters of the DPC model has been discussed. The results show that the ejection process cannot be fully simulated when the plastic parameters are assumed to be constants, while for the case that adopting plastic parameters changed with relative density can show a good agreement with the experimental data. Finally, the parametric module of Python was applied to simulate the compaction of industrial part. The integrated modeling using inverse optimization method was verified again in compaction of a typical multi-level gear component. And the numerical results show that the errors of the maximum and the minimum relative density are about 5% and 4% respectively.