International Journal of Advanced Technology and Engineering Exploration ISSN (Print): 2394-5443    ISSN (Online): 2394-7454 Volume-13 Issue-139 June-2026
  1. 4774
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Material-specific melt depth prediction in conduction-limited laser melting

Osama M. Alkhawaldeh1

Department of Industrial Systems Engineering,Mutah University, Mutah,Al-Karak,Jordan1
Corresponding Author : Osama M. Alkhawaldeh

Recieved : 29-November-2025; Revised : 16-June-2026; Accepted : 18-June-2026

Abstract

Melting is a foundational mechanism in most applications of laser manufacturing processes. This paper deals with the heat conduction equation to investigate the melt depth prediction in laser melting processes. Generalized formulations used in melt depth prediction assume that the thermal conductivity in the liquid region is identical to that in the solid at room temperature, and that the ratio of energy required for melting to specific heat is the same for all materials. In this work, the proposed formulation considers the variation in these two parameters to derive a material-specific formula for melt depth prediction. The maximum melt pool depths and the irradiation times to reach the vaporization temperature at the surface of the melt pool are also calculated. Constants for aluminum, titanium, stainless steel, and superalloys are presented in the theoretical melt depth predictions. The material specific prediction model is validated for stainless steel 316L (SS316L) using a continuous wave fiber laser. The results demonstrate that the proposed formulation reduces prediction errors compared to the generalized model, though significant discrepancies remain at longer irradiation times.

Keywords

Laser melting, Melt depth prediction, Heat conduction model, Melt pool dynamics, Stainless steel 316L (SS316L), Continuous wave fiber laser.

Cite this article

Alkhawaldeh OM. Material-specific melt depth prediction in conduction-limited laser melting. International Journal of Advanced Technology and Engineering Exploration. 2026;13(139):886-897. DOI : 10.19101/IJATEE.2025.121221563

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