Prediction of mixed grains during hot deformation of 12%Cr heat-resistant steel by coupling method of DRX-CA and FE simulation

In this paper, a novel method was presented for forecasting mixed grains within large-scale forgings of 12%Cr heat-resistant steel during the single-pass hot deformation process. The proposed approach integrates a dynamic recrystallization cellular automaton (DRX-CA) model with finite element (FE) simulations and is complemented by evaluation criteria for mixed grains microstructure. Firstly, through the single-pass hot compression experiment, the necessary data for constructing the DRX-CA model were obtained, leading to its establishment. Based on the DRX-CA model, the stress–strain curves, grain microstructure, and DRX percentage observed in the experiment were simulated and reproduced, which verified the model’s effectiveness in describing 12%Cr heat-resistant steel’s DRX behavior; Secondly, grain microstructure evolution in different deformation zones during 12%Cr heat-resistant steel’s single-pass hot deformation (upsetting process) was studied through the integration of DRX-CA model with FE simulation. The mixed grains degree of the resulting microstructure was assessed based on evaluation criteria for mixed grains microstructure; Finally, the grain structure obtained by the above method was validated through upsetting experiments. The results revealed that the average grain size and mixed grain degree obtained from both the experiments and simulations were not significantly different, indicating that the combination of the DRX-CA model and FE simulation can effectively predict the mixed grains during the upsetting process. This novel method for predicting mixed grains shifts the evaluation point of mixed grains forward, integrating the characteristics of defect prediction and process optimization, and provides a reference for controlling mixed grains during the hot forging process of large forgings.