Melt pool dynamics are highly complex and are the origins of many defects (e.g., pores and cracks) as well as the microstructure and properties in additive manufacturing. There have been many models to simulate the melt pool, from low-fidelity thermal conduction models to the high-fidelity thermal-fluid flow models. In this presentation, we will introduce our efforts and findings in developing a high-fidelity/accuracy model of melt pool dynamics. We have conducted uncertain quantification to screen the important factors in the model, which reveals the significance ranking of laser energy absorptivity, laser diameter, thermal conductivity, viscosity and others [1]. To ensure the accuracy of laser energy absorptivity, it is critical to incorporate the ray-tracing heat source model, where the energy absorptivity is calculated according to the Fresnel equations accounting material composition and local incidence angle. Accurately measured laser diameter is a significant factor in the model. Many thermo-physical parameters of the materials are temperature dependent and difficult to measure experimentally, but their uncertainties do not significantly propagate to the model uncertainty of the melt pool dynamics. Another key factor is the evaporation, inducing the heat and mass losses and more importantly recoil pressure, which is dependent on the local chemical compositions and temperature as well as ambient pressure. After realizing the oversimplifications of the commonly used evaporation model, we derived a new evaporation model incorporating the different evaporation rates of different chemical elements [2]. Our melt pool model has been validated against various experiments, including in-situ X-ray imaging results. REFERENCES [1] Amanda Giam, Fan Chen, Jiaxiang Cai, and Wentao Yan. "Factorial design analytics on effects of material parameter uncertainties in multiphysics modeling of additive manufacturing." npj Computational Materials 9, no. 1 (2023): 51. [2] Lu Wang, Yanming Zhang, and Wentao Yan. "Evaporation model for keyhole dynamics during additive manufacturing of metal." Physical Review Applied 14, no. 6 (2020): 064039.