Improved inherent strain extraction algorithm based analytical surface modeling for Ti-6Al-4V and SS316L selective laser melting part

Abstract

Selective laser melting (SLM) is one of the most popular metal additive manufacturing (AM) techniques relied on powder bed and has been widely used in numerous fields. Printing surface modeling is a critical step for product development and quality control of SLM parts as the surface profile has a great impact on the structure and functional performance of printed parts. However, it is still a challenge to predict the printing surface geometry of the SLM part accurately and quickly due to the complex physical processes and thermomechanical behaviors in SLM. To address this barrier, a comprehensive bottom-up modeling approach based on an improved inherent strain method (ISM) is proposed to estimate the surface fluctuation between designed and printed parts and further predict the printing surfaces of SLM parts. The improved inherent strain is extracted from multi-physics analytical calculation considering the thermal influences of in-plane scanning tracks, interlayer re-melting and interlayer strain accumulation. Specifically, temperature filed is obtained from the quasi-static heat analytical model integrating residual temperature involving the heat contribution of in-plane scanning tracks via virtual heat source technique. The interlayer strain accumulation and interlayer re-melting effects are embedded into the inherent strain terms through the layer-lever fluctuation superposition and re-melted depth parameter respectively. Strain compositions are solved through thermo-elastic Green function models and modified elastic-plastic McDowell analytical models, where temperature-dependent material properties are employed. The proposed method has been validated by experimental observations from the literature via two SLM parts using two distinct materials (Ti-6Al-4 V and SS316L).