論文ID: 25-00065
Critical resolved shear stress (CRSS) is one of the most important parameters in the field of plasticity in metals, and the CRSS ratios between slip systems govern the plastic anisotropy, workability, and so on. Therefore, it is highly valuable to develop a system that can predict CRSS ratios with high accuracy in a short period of time. With the above background, Sato et al. (Transactions of JSME (in Japanese), (2023)) developed a system to predict CRSS ratios using distributions of strain and crystal orientation. However, the system requires much time to predict CRSS ratios. In this study, a new CRSS ratio prediction system with low computational cost has developed by devising a calculation method and introducing the covariance matrix adaptation evolution strategy (CMA-ES), a method of meta-heuristics. The validation of system was conducted by prediction of CRSS ratios in virtual hexagonal close-packed (HCP) materials from the strain distributions obtained by a crystal plasticity finite element method (CPFEM) and crystal orientation distributions. The validation results showed that the prediction of CRSS ratios for <a> slip systems was success and the accuracy was similar when information from all measurement points and when representative values for individual grains were used. The prediction accuracy was also the same level when the method introducing CMA-ES was employed. These results indicate that the developed system can predict CRSS ratios for <a> slip systems in HCP metals within seconds.