# Roles of Modeling and Artificial Intelligence in LPBF Metal Print Defect Detection: Critical Review
## 3 Advances in Numerical Modeling Techniques for LPBF Defect Detection
### Melt Pool Defect Modeling
#### 3.1.1 Thermo-Mechanical Simulations of LPBF Defects Using FEM
However, due to a ductility reduction, shortening the scan lengths caused an increase in voids and higher yield stresses. Entrapped gas pores and balling were observed during the simulations. A similar study numerically investigated the temperature and stress fields of a novel dual-laser partition scanning strategy under different auxiliary beam powers using ANSYS [43]. The results showed that the residual stress levels increase and decrease with increasing auxiliary beam power. A study predicted the 2D temperature profile and melt pool geometry for LPBF-printed Inconel 625 powder using an in-house FEM code in MATLAB [44]. The results showed the strong impact of porosity on the final melt pool temperature field. Increasing the porosity generates a higher local temperature profile through decreased effective thermal conductivity. Additionally, the change in powder reflectivity produces the most considerable variation in the melt pool geometry. A study developed an in-house non-linear 3D FEM in MATLAB to simulate the LPBF process of Inconel 625 with various process parameters [45]. Most heat diffusion at medium levels of energy density aligns with the build direction. As the scanning velocity decreases, heat diffusion was proposed to affect the growth direction of columnar grains. In an investigation, authors created a distortion model of the LPBF process for Inconel 625 and 718 using Netfabb [46]. The residual stresses produced by the melt pool solidification are analyzed. A parametric study was conducted on the LPBF process of Inconel 718 using ABAQUS to calibrate the laser penetration depth and absorptivity of the heat source model as a function of the laser power and scan speed [47]. The steep keyhole walls generated through the vaporization and convection environments increase laser reflectivity, which can further deepen the keyholes. A new efficient and part-level FE simulation scheme using Deal-II software was conducted to refine and coarsen the mesh adaptively [48]. The melt pool was shown to have an influence on neighboring scanning tracks and beneath layers. A continuous-mesoscale level set model of the LPBF process was developed to evaluate the Inconel 718 melt pool and track development during the build using an in-house FEM code [35]. LOF defects between the first and second tracks were observed. Capillary digging was also observed for Inconel 718, but it was not as prevalent as for Ti6 Al4V. A research effort presented an FEM approach utilizing ANSYS software to determine the layers' dwell time effect on the deformation of the component during the LPBF of Inconel 718 [49]. Short dwell times increased the thermal distortion of the part and the residual stresses. Another study simulated the LBM of Inconel 738 using a continuous-mesoscale FEM process in JMatPro software. The denudation and keyhole behaviors leading to pore defects were analyzed using an in-house level set model [50]. A distortion model of AlSi10 Mg printing using Netfabb was created [46]. The residual stresses produced by melt pool solidification were analyzed. COMSOL Multiphysics was used to simulate and calculate the melt pool dimensions, heat transfer rate, and temporal variation in the temperature changing rate during the LPBF of Hastelloy X [51]. As the energy density increases, the melt pool depth becomes more significant due to higher levels of heat penetration into the powder bed. Increasing the laser beam velocity will decrease the laser beam supplied power, diminishing the melting pool's temperature gradient. It was also concluded that the cooling capacity increases with the increasing beam power due to having a liquid thermal transport capacity that is higher than the solidified part. The effects of the melt pool hydrodynamics and material evaporation were investigated for the AlSi10 Mg melt pool using COMSOL [52]. The high magnitude of rapid heating/cooling rates indicates the formation of a metastable microstructure with little or no time for the constituents to segregate or precipitate.