Multiscale FE modeling of SLMed ASS316 L reinforced with nanoparticles during FSP: exploring the impact of particle volume fraction, shape, and type on mechanical strength

Abstract

This study investigates the effect of nanoparticle volume fraction, shape, and type on the strength of nanocomposites made of selective laser melted (SLM) austenitic stainless steel (AISI 316L) reinforced with nanoparticles during friction stir processing (FSP). Using the mean field homogenization (MFH) method with the Mori–Tanaka model, multiscale finite element simulations were conducted to predict the mechanical behavior of the composites. These simulations were validated through experimental tests, yielding consistent results, with tensile strength reaching 740 MPa for reinforced sample, compared to 670 MPa for unreinforced FSP-treated material. A systematic design of experiments (DOE) was implemented using response surface methodology (RSM), generating 15 sample configurations. The strength of these configurations was calculated via finite element modeling. Analysis of variance (ANOVA) was then performed to evaluate the direct and interaction effects of the parameters, identifying the volume fraction as the most critical factor, with significant contributions from particle shape and type. A mathematical model derived from the ANOVA results demonstrated strong predictive accuracy (R² = 98.33%) and was validated against simulation data. This integrated framework underscores the potential of combining experimental and computational techniques for optimizing metal matrix nanocomposites in advanced engineering applications.