The parameter sets used during the selective laser melting (SLM) process directly affect the final product through the resulting melt-pool temperature. Achieving the optimum set of parameters is usually done experimentally, which is a costly and time-consuming process. Additionally, controlling the deviation of the melt-pool temperature from the specified value during the process ensures that the final product has a homogeneous microstructure. This study proposes a multiphysics numerical model that explores the factors affecting the production of parts in the SLM process and the mathematical relationships between them, using stainless steel 316L powder. The effect of laser power and laser spot diameter on the temperature of the melt-pool at different scanning velocities were studied. Thus, mathematical expressions were obtained to relate process parameters to melt-pool temperature. The resulting mathematical relationships are the basic elements to design a controller to instantly control the melt-pool temperature during the process. In the study, test samples were produced using simulated parameters to validate the simulation approach. Samples produced using simulated parameter sets resulting in temperatures of $2000\left(\mathrm{K}\right)$ and above had acceptable microstructures. Evaporation defects caused by extreme temperatures, unmelted powder defects due to insufficient temperature, and homogenous microstructures for suitable parameter sets predicted by the simulations were obtained in the experimental results, and the model was validated.

Powder spattering and splashing in the melt pool are common phenomena during Laser-based Powder Bed Fusion (LPBF) of metallic materials having high fluidity. For this purpose, analytical and computational fluid dynamics (CFD) models have been deduced for the LPBF of AlSi10Mg alloy. The single printed layer’s dimensions were estimated using primary operating conditions for the analytical model. In CFD modelling, the volume of fluid and discrete element modelling techniques were applied to illustrate the splashing and spatter phenomena, providing a novel hydrodynamics CFD model for LPBF of AlSi10Mg alloy. The computational results were compared with the experimental analyses. A trial-and-error method was used to propose an optimized set of parameters for the LPBF of AlSi10Mg alloy. Laser scanning speed, laser spot diameter and laser power were changed. On the other hand, the powder layer thickness and hatch distance were kept constant. Following on, 20 samples were fabricated using the LPBF process. The printed samples’ microstructures were used to select optimized parameters for achieving defect-free parts. It was found that the recoil pressure, vaporization, high-speed vapor cloud, Marangoni flow, hydraulic pressure and buoyancy are all controlled by the laser-material interaction time. As the laser-AlSi10Mg material interaction period progresses, the forces presented above become dominant. Splashing occurs due to a combination of increased recoil pressure, laser-material interaction time, higher material’s fluidity, vaporization, dominancy of Marangoni flow, high-speed vapor cloud, hydraulic pressure, buoyancy, and transformation of keyhole from J-shape to reverse triangle-shape that is a tongue-like protrusion in the keyhole. In the LPBF of AlSi10Mg alloy, only the conduction mode melt flow has been determined. For multi-layers printing of AlSi10Mg alloy, the optimum operating conditions are laser power = 140 W, laser spot diameter = 180 µm, laser scanning speed = 0.6 m/s, powder layer thickness = 50 µm and hatch distance = 112 µm. These conditions have been identified using sample microstructures.

This study quantifies the microstructure-controlled tensile anisotropy of near fully dense laser powder bed fusion (LPBF) AlSi10Mg. Tensile specimens built at 0o, 45o, and 90o relative to the build direction were selected, enabling a focus on orientation-dependent grain morphology and crystallographic alignment. EBSD analysis revealed pronounced differences in grain shape and alignment across orientations, which were transferred into a statistically representative 3D polycrystal RVE (100×50×100 µm3, ~590 grains) generated using DREAM.3D. Crystal plasticity simulations were performed using DAMASK under periodic boundary conditions using two constitutive frameworks: (i) a phenomenological slip-based model and (ii) a dislocation-density-based physics model. Both model fitting parameters were calibrated to match experimental tensile data via Bayesian (Gaussian-process) optimization with an objective function combining stress-strain and hardening-rate errors. To capture build-orientation effects with minimal parameter freedom, only one strength-related parameter was varied, while all other rate and hardening parameters were held constant across orientations. The strength related parameter in both models is rooted in SEM-based quantification of an orientation-dependent Si-network length scale instead of being treated as an empirical entity. Both formulations produced consistent microstructure-resolved trends showing higher stress accumulation in the 0o case and more uniform strain accommodation in the 90o case at the same macroscopic strain. The work demonstrates that the LPBF induced tensile anisotropy can be captured accurately in meso-scale simulations using large, grain-resolved RVEs, while representing sub-grain Si-network effects implicitly through effective strength calibration grounded by measured Si-network geometry. The higher flow stress in the 0o condition is linked to the smaller effective Si-network spacing along the loading direction, which increases dislocation-barrier interactions, whereas the larger spacing in the 90o condition promotes easier plastic flow. Comparison of phenomenological and physics-based models in CP formulations for the deformation modeling of LBPF AlSi10Mg helps researchers choose a better model for their use cases with appropriate parameters based on the load frame relative to the build orientation.

Directed Energy Deposition (DED) is a metal additive manufacturing process widely used for near-net-shape fabrication, repair of high-value components, and production of large-scale metallic structures. The quality of DED-built parts strongly depends on the thermal history, melt pool geometry, and layer-by-layer heat accumulation during deposition. Therefore, numerical simulation is an effective tool for understanding the process physics and supporting parameter selection before experimental manufacturing. In this study, a three-dimensional multiphysics model was developed to simulate the DED process using COMSOL Multiphysics. The model couples heat transfer, laminar fluid flow, and solid mechanics to evaluate the thermal and physical behavior of deposited metallic layers. A moving Gaussian laser heat source was implemented to represent laser-material interaction, while the governing equations of energy, momentum, and mass conservation were solved to predict temperature distribution and melt pool formation. A symmetric computational domain consisting of a base plate and three deposited powder layers was designed. Steel AISI 4340 was selected as the model material, and its thermophysical properties were incorporated into the simulation. The results show that the proposed model can capture the transient temperature distribution and melt pool evolution during successive layer deposition. The findings indicate that heat accumulation from previously deposited layers significantly affects the thermal field and melt pool characteristics in subsequent layers. The simulation also demonstrates that a coupled multiphysics approach provides deeper insight into the interaction between laser heating, melt pool development, and thermal deformation. The developed model can be used as a practical framework for understanding DED process behavior and supporting future process parameter optimization studies.