Numerical modeling of thermal anisotropy on a selective laser melting process Academic Article in Scopus uri icon

abstract

  • © 2020, Emerald Publishing Limited.Purpose: An experimental and numerical study of thermal profiles of 316 L stainless steel during selective laser melting (SLM) was developed. This study aims to present a novel approach to determine the significance and contribution of thermal numerical modeling enhancement factors of SLM. Design/methodology/approach: Surface and volumetric heat models were proposed to compare the laser interaction with the powder bed and substrate, considering the powder size, absorptance and propagation of the laser energy through the effective depth of the metal layer. The approach consists in evaluating the contribution of the thermal conductivity anisotropic enhancement factors to establish the factors that minimized the error of the predicted results vs the experimental data. Findings: The level of confidence of the carried-out analysis is of 97.8% for the width of the melt pool and of 99.8% for the depth of the melt pool. The enhancement factors of the y and z spatial coordinates influence the most in the predicted melt pool geometry. Research limitations/implications: Nevertheless, the methodology presented in this study is not limited to 316 L stainless steel and can be applied to any metallic material used for SLM processes. Practical implications: This study is focused on 316 L stainless steel, which is commonly used in SLM and is considered a durable material for high-temperature, high-corrosion and high-stress situations. Social implications: The additive manufacturing (AM) technology is a relatively new technology becoming global. The AM technology may have health benefits when compared to the conventional industrial processes, as the workers avoid extended periods of exposure present in conventional manufacturing. Originality/value: This study presents a novel approach to determine the significance and contribution of thermal numerical modeling enhancement factors of SLM. It was found that the volumetric heat model and anisotropic enhancement thermal approaches used in the present research, had a good agreement with experimental results.

publication date

  • September 29, 2020