Genetic algorithm-based numerical optimization of powder compaction process with temperature-dependent cap plasticity model

In this paper, a shape optimization technique is presented for the cold and hot isostatic pressing of metal powders based on the genetic algorithm (GA) approach. The GA technique is used to obtain the desired optimal compacted component by changing the boundaries of component and verifying the prescribed constraints. The coupled thermomechanical analysis of hot isostatic pressing is employed for metal powders during densification process. The numerical modeling of hot powder compaction simulation is performed based on the large deformation formulation, temperature-dependent cap plasticity model, and frictional contact algorithm. The modified cap plasticity takes the temperature effects into the numerical simulation of highly nonlinear behavior of metal powder. Finally, numerical examples are analyzed to demonstrate the feasibility of proposed optimization algorithm for designing powder components in the cold- and hot-forming processes of powder compaction.