A review on the simulation of selective laser melting AlSi10Mg

Selective laser melting (SLM) has found extensive applications in the realm of metal printing as an additive manufacturing technique. The performance of metals fundamentally dictates their industrial utility. Aluminum alloys, the second most utilized alloy following steels, have extensive applications in aerospace, automotive components, biomedicine, etc. Among these alloys, AlSi10Mg stands out as one of the most extensively researched aluminum alloys in SLM. Nevertheless, conducting experimental trials with varying materials and process parameters proves not only to be expensive but also time-consuming. Numerical simulations have emerged as viable solutions to address this challenge. Consequently, in order to more successfully conquer this challenge, based on the solidification theory, this paper provides an exposition on the formation process of SLM and metallurgical defects. It comprehensively reviews the current state of numerical simulations for SLM formed AlSi10Mg, addressing three crucial aspects: heat and mass transfer processes, microstructure evolution, and mechanical properties. These discussions are structured around different problem scales and physical phenomena, encompassing thermodynamic process numerical simulations (based on high-fidelity heat analysis models at the powder scale and heat conduction models relying on the continuum assumption), microstructure evolution prediction simulations (utilizing phase field methods and cellular automaton approaches), and mechanical performance analysis simulations (encompassing models that do not consider any defects, those that consider defects, and those that factor in underlying grain structures). The applicability and distinct characteristics of each model are analyzed, followed by an exploration of the process-structure-performance relationship modeling. On this basis, the challenges and trends facing numerical simulation of SLM formed AlSi10Mg are summarized, especially the application of data-driven in numerical simulation