Journal of Materials Research and Technology (Nov 2023)
Simulation of solidification microstructure evolution of 316L stainless steel fabricated by selective laser melting using a coupled model of smooth particle hydrodynamics and cellular automata
Abstract
Selective Laser Melting (SLM) is an efficient and advanced manufacturing technology that utilizes lasers to melt and solidify metal or alloy powders, layer by layer, to form the desired object shape. This study aims to investigate the evolution behavior of the solidification microstructure during the SLM process and presents a novel numerical simulation method based on the Smoothed Particle Hydrodynamics-Cellular Automaton (SPH-CA) coupling model. The SPH-CA coupling model combines the particle information, such as position and temperature, from Smoothed Particle Hydrodynamics (SPH) with the Cellular Automaton (CA) method in a one-way coupling manner, enabling simultaneous computation of multiple physical fields, including heat transfer, melting, solidification, and morphology. This model addresses challenges that are difficult to handle in grid-based computations, such as free surface variations, boundary deformations, interfacial motion, and large deformations. Additionally, it effectively simulates the morphology of the solidification microstructure. Furthermore, the coupling process performs kernel function weighted calculations at the same scale, which results in higher accuracy compared to the grid-based multiscale mapping. The simulation results demonstrate that different processing parameters influence the morphology of the molten pool and the thermal undercooling, thereby affecting the growth characteristics of the grains. A higher laser scanning speed leads to smaller molten pool size, finer grain sizes in the solidification microstructure, larger laser grain angles, and a higher content of columnar grains. These findings are consistent with experimental observations and existing conclusions, providing evidence for the feasibility and effectiveness of the proposed model in the context of SLM.
