Porosity Prediction in LPBF of AISI 316L Stainless Steel: Refined Volumetric Energy Density and FEM Simulation Approach

Abstract

Porosity in laser powder bed fusion (LPBF) additive manufacturing significantly affects the mechanical properties and performance of produced parts. Traditional volumetric energy density (VED) model has limitations in accurately predicting porosity, as it does not account for material-specific properties and thermal dynamics. This study investigates a comparative analysis of porosity formation in LPBF of AISI 316L stainless steel through experiments, finite element (FE), and analytical models. In the case of analytical model, a modified VED (MVED) relationship is proposed, incorporating material properties and thermo-physical characteristics to address the shortcomings of conventional VED approaches. LPBF experiments were conducted to print the samples by varying process parameters, and X-ray computed tomography was utilized to characterize the porosity within the fabricated samples. FEM simulations were also conducted to predict thermal distributions, melt pool dimensions and corresponding porosity. It was found that the MVED analytical model demonstrated improved empirical correlation with experimental porosity compared to the traditional VED, with an R-squared value of 0.88 versus 0.75 for the traditional model. This improvement highlights the importance of considering material-specific properties in energy density calculations. FEM results showed good agreement with experimental observations of porosity trends across different processing conditions, accurately predicting thermal distributions and melt pool dimensions. The presented approach provides insights into porosity formation mechanisms and offers potential for optimizing LPBF processing parameters to minimize defects, while addressing the limitations of traditional VED models.

Department(s)

Mechanical and Aerospace Engineering

Keywords and Phrases

Finite element modeling; Laser powder bed fusion; Melt pool dynamics; Thermal distribution; Volumetric energy density; X-ray computed tomography

International Standard Serial Number (ISSN)

0030-3992

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2025 Elsevier, All rights reserved.

Publication Date

01 Oct 2025

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