A Calibrated Model with a Novel Heat Source for Accelerated Simulation of Laser-Based Powder Bed Fusion of Metals

Date of Award

5-9-2026

Degree Name

M.S. in Mechanical Engineering

Department

Department of Mechanical and Aerospace Engineering

Advisor/Chair

Abdullah Amin

Abstract

Accurate prediction of melt pool geometry and cooling rates at part scale remains a significant challenge in Laser-Based Metal Powder Bed Fusion (PBF-LB/M) Additive Manufacturing. In this research, the commercial CFD solver Ansys Fluent is used to develop a calibrated model for accelerated prediction of melt-pool metrics and cooling rates. The model is developed by calibrating laser processing parameters against experimental benchmarks from the NIST 2022 AM-Bench study for Inconel 718 material. Single-track simulations are conducted to evaluate melt pool depth, width, solid cooling rate, liquid cooling rate, transition cooling rate, and time above melting. Eight different types of heat sources (single conical, double conical, cylindrical with decays, ellipsoidal etc.) are validated and compared. Double conical heat source is then tested for single track cases different volumetric energy density to find the models reliability. The calibrated model of single conical and double conical heat sources is applied to multi-track simulations to predict melt pool morphology and cooling rates. 10 tracks are simulated and rest of 37 tracks were predicted with fit curves. Results are compared with same experiment. Effect of laser incidence angle was studied. To find effect of laser turnaround time on melt pool dimensions and cooling rates, two cases are applied. These results are then compared with NIST AM-Bench 2025 experiment. Multiple laser simulations were done to find the difference between using one laser and two lasers. Finally, three different beam shapes (Flat top, Donut and Bessel) are considered to find its effects and compare with gaussian beam. Therefore, a calibrated modeling framework is demonstrated to enable rapid calibration and accurate prediction, providing a computationally efficient alternative to purely physics-driven, expensive, and complicated thermal-CFD models. The results demonstrate that multi-track melt-pool dimensions and cooling rates can be predicted from single-track calibrated data very quickly with high accuracy, thereby facilitating efficient process optimization in laser-based powder bed fusion of metals.

Keywords

Mechanical Engineering

Comments

OCLC No. 1591830030

Rights Statement

Copyright 2026, author.

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