## 1 Introduction
Afterward, anisotropic thermal conductivity and absorptivity were calibrated by trial and error to increase the accuracy of the simulation. [PERSON] et al. [4] performed heat transfer analysis by applying a heat source model considering optical penetration depth (OPD) to a finite element model composed of only powder, and the OPD was calibrated and verified by comparing with the experimental value. [PERSON] et al. [5] analyzed the temperature profile and melt pool size of the powder bed for the SLM process by finite element analysis and compared them with experimental results. [PERSON] et al. [6] evaluated the parameter with the greatest influence on temperature and stress by sensitivity analysis to the physical characteristics of the material (conductivity, specific heat capacity, Young's modulus). The effects of process parameters (laser power, scan speed, overlap between adjacent paths) on the heat distribution and residual stress of components were evaluated. [PERSON] et al. [7] analyzed the effect of hatching spacing on temperature field, microstructure and melt pool size, overlap rate, surface quality, and relative density by experiments and simulations, and they determined the optimal hatch spacing. In these studies related to AM process simulations using FEM, several assumptions were made to determine the analysis parameters and conditions. Although the laser heat source penetrates through the powder bed due to the pores between the powder particles, and the penetration depth is determined according to the material and powder characteristics, the penetration depth was simply set to the powder layer [3; 6; 8; 9], or it was assumed that the heat source model did not penetrate through the powder bed and the heat source was applied only to the powder bed surface [2; 7; 10; 11]. In some cases, in order to determine the thermal properties of the powder, porosity was considered [3; 4; 6; 7; 8; 9; 10] or the Marangoni effect causing surface tension in the melting pool was applied [5; 8; 12]. In some studies [4; 10; 12], radiation was ignored because it was evaluated to have little effect as a boundary condition. These assumptions reduce the complexity of the finite element model and increase the convergence of the analysis, but the accuracy of thermal analysis with analysis parameter values based on these assumptions cannot be assured for all analysis cases. In addition to methods using FEM, many studies also have been conducted using CFD and analytical models to propose accurate thermal analysis models for LPBF process simulation and prediction of the melt pool size. [PERSON] et al. (2013) described a multiscale modeling strategy, including a powder scale model that simulated single track/single multi-layer builds and provided powder bed and melt pool thermal data, and the modeling was tied to experiments through data mining. [PERSON] et al. (2014) applied a CFD model to investigate the fluid dynamics in melt pools and resultant pore defects. To accurately capture the melting and solidification process, major process physics, such as the surface tension, evaporation, as well as laser multi-reflection, have been considered in the model. The predicted melt pool dimensions were validated with experimental measurements. [PERSON] et al. (2015) introduced five different heat source models (steady-state moving point heat source, transient moving point heat source, semi-elliptical moving heat source, double elliptical moving heat source, and uniform moving heat source) to predict the three-dimensional temperature field analytically. The proposed temperature field models were validated using experimental measurement of melt pool geometry. [PERSON] et al. (2016) determined that the temperature distribution in the simple thermal model of SLM was characterized by two dimensionless parameters (normalized enthalpy and the ratio of dwell time to the diffusion time).