TY  - EJOU
AU  - Zhu, Changsheng 
AU  - Miao, Jintao 
AU  - Gao, Zihao 
AU  - Liu, Shuo 
AU  - Li, Jingjie 

TI  - Efficient Prediction of Quasi-Phase Equilibrium in KKS Phase Field Model via Grey Wolf-Optimized Neural Network
T2  - Computers, Materials \& Continua

PY  - 2025
VL  - 84
IS  - 3
SN  - 1546-2226

AB  - As the demand for advanced material design and performance prediction continues to grow, traditional phase-field models are increasingly challenged by limitations in computational efficiency and predictive accuracy, particularly when addressing high-dimensional and complex data in multicomponent systems. To overcome these challenges, this study proposes an innovative model, LSGWO-BP, which integrates an improved Grey Wolf Optimizer (GWO) with a backpropagation neural network (BP) to enhance the accuracy and efficiency of quasi-phase equilibrium predictions within the KKS phase-field framework. Three mapping enhancement strategies were investigated–Circle-Root, Tent-Cosine, and Logistic-Sine mappings–with the Logistic mapping further improved via Sine perturbation to boost global search capability and convergence speed in large-scale, complex data scenarios. Evaluation results demonstrate that the LSGWO-BP model significantly outperforms conventional machine learning approaches in predicting quasi-phase equilibrium, achieving a 14–28 reduction in mean absolute error (MAE). Substantial improvements were also observed in mean squared error, root mean squared error, and mean absolute percentage error, alongside a 7–33 increase in the coefficient of determination (). Furthermore, the model exhibits strong potential for microstructural simulation applications. Overall, the study confirms the effectiveness of the LSGWO-BP model in materials science, especially in enhancing phase-field modeling efficiency and enabling accurate, intelligent prediction for multicomponent alloy systems, thereby offering robust support for microstructure prediction and control.
KW  - Logistic-sine mapping; LSGWO-BP model; microstructure; quasi-phase equilibrium; phase field model

DO  - 10.32604/cmc.2025.067157