Analytical modeling of yield strength-grain size-processing parameters relationship

The main focus of this research is to investigate how microstructural changes impact material properties of yield strength, which involves studying the material’s microstructure—grain size—in the emerging additive manufacturing (AM) technology. Compared to the expensive cost of traditional test-and-trial or finite element methods (FEM), physics-based analytical simulation with closed-form solution is playing an increasing important role in prediction and process optimization of microstructure evolution and materials properties in metal AM industries. In this work, various models have been developed to predict manufacturing processes using physics-based frameworks, and experimental results have been used to validate these models. It has been observed that the periodic settings of laser power and scanning speed lead to similar trends of grain size and yield strengths, which shows the existence of the relevant quantitative relationship, and these findings pave the road for the future of inverse search for optimized processing parameters.