Diksha Mahadule

Physics-Informed Residual Deep Learning for Constitutive Modeling of Hot Deformation and Dynamic Recrystallization in a Mo-Rich $\alpha+\beta$ Titanium Alloy

This model accurately reproduced temperature-dependent flow curves, DRX kinetics, and Zener-Hollomon relationships, while maintaining physically consistent constitutive behavior, demonstrating that physics-informed deep learning provides a robust and interpretable framework for constitutive modeling.