Ying-Jie Zhao

A mechanism-data fusion framework for process-microstructure prediction and optimization in laser directed energy deposition of Ti-6Al-4V using dual-level surrogate modeling

A physics-informed mechanism-data fusion framework that couples macroscopic finite element method (FEM) and microscopic phase-field method (PFM) with a dual-level long short-term memory (LSTM) neural network with a dual-level data-driven surrogate model is developed.