Heat Source Model Development for Thermal Analysis of Laser Powder Bed Fusion Using Bayesian Optimization and Machine Learning

Abstract

To understand the correlation between process, structures, and properties in laser powder bed fusion (L-PBF), it is essential to use numerical analysis as well as experimental approaches. A finite element thermal analysis uses a moving heat source model represented as a volumetric heat flux to simulate heat input by laser. Because of its computational efficiency, finite element thermal analysis is suitable for iterative procedures such as parametric study and process optimization. However, to obtain valid simulated results, the heat source model must be calibrated by comparison with experimental results for each laser scanning condition. The need for re-calibration limits the applicable window of laser scanning conditions in the thermal analysis. Thus, the current study developed a novel heat source model that is valid and precise under any laser scanning condition within a wide process window. As a secondary objective in the development, we quantitatively evaluated and compared the four heat source models proposed to date. It was found that the most suitable heat source model for the L-PBF is conical one among them. Then, a multiple linear regression analysis was performed to represent the heat source model as a function of laser power and scanning velocity. Consequently, the thermal analysis with the novel model is valid and precise within the wide process window of L-PBF.

Particle Size Effect on Powder Packing Properties and Molten Pool Dimensions in Laser Powder Bed Fusion Simulation

“…In view of the situation described above, simulation studies of L-PBF have increased in the last decade. For example, heat transfer analysis, which considers changes in physical properties associated with the phase change between solid and liquid metals [6,9,21]; elastoplastic simulation for evaluating residual stresses [9,22,23]; and multiphysics analysis which involves fluid dynamics, heat transfer considering solid-liquid-gas phase change, and laser ray tracing using multiphysics computational fluid dynamics (CFD) simulation [24][25][26][27][28][29][30][31][32][33]. The use of multiphysics CFD simulation has shown promise in predicting defect formation.…”