Project: Physics-Based Data-Driven Additive Manufacturing Process Design
The objective of this research is to develop multiscale multiphysics simulation models to understand the complex phenomena in additive manufacturing processes and establish the process-structure-property relationships with new physics-informed machine learning methods for process design.
Multiphysics Simulation of Rapid Solidification
Powder bed fusion and direct energy deposition processes are widely used in metal based AM. Yet, the major technical barriers for their industry-scale applications are the high process variability and poor product quality. The lack of fundamental understanding of rapid solidification of materials causes uncertainty in the process. In this work, a novel multiphysics simulation mechanism of phase field with thermal lattice Boltzman methods (PF-TLBM) is developed to simulate solidification process with the simultaneous considerations of fluid flow, thermal distribution, and grain formation.
Atomistic Simulation of Laser Sintering
In this work, atomistic scale molecular dynamics simulation models are developed to analyze the effects of particle distributions and materials on the thermal and mechanical properties of sintered components.