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A novel energy density model based on empirically-derived laser and powder parameters for directed energy deposition of stainless steel 316 L

  • Sungkyunkwan University

Research output: Contribution to journalArticlepeer-review

Abstract

In this study, a modified specific energy density (MSED) is proposed to address the limitations of the nominal energy–density model, which fails to reflect actual laser thermal interactions or effective powder behavior in directed energy deposition (DED). The actual heat-affected diameter and powder distribution were parameterized through empirical laser marking experiments and vision-based image analysis of powder flow. The effective energy delivered per unit mass was calculated by integrating the spatial overlap between laser energy and powder concentration. Geometric growth, including width and height, increased with MSED but began to decrease above 150 (kJ/g) s, at which point the dilution rate approached the physical limit of approximately 70 %. Microstructural trends were also qualitatively identified, with fine dendritic structures appearing at low MSED and gradual dendritic coarsening at high MSED. Furthermore, a regression model was developed using laser power, scan speed, and MSED and validated through four-fold cross-validation. This model demonstrated strong generalization, with an average predictive performance R2 = 0.956, and the dilution-specific model achieved an R2 = 0.912 for the single MSED relationship. These results demonstrate that MSED serves as a physically based indicator representing various qualities and can be used as an optimization indicator in DED manufacturing.

Original languageEnglish
Article number115433
JournalMaterials and Design
Volume262
DOIs
StatePublished - Feb 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • Correlation analysis
  • Cross-sectional quality characteristics
  • Directed energy deposition
  • Modified specific energy density
  • Parameter quantification
  • Quality prediction regression model

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