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The effect of absorption ratio on meltpool features in laser-based powder bed fusion of IN718

journal contribution
posted on 2024-11-02, 20:40 authored by Amirmahyar KhorasaniAmirmahyar Khorasani, AmirHossein Ghasemi, Martin LearyMartin Leary, Elmira Gharehzadeh SharabianElmira Gharehzadeh Sharabian, Laura Cordova, Ian Gibson, David DowningDavid Downing, Stuart BatemanStuart Bateman, Milan BrandtMilan Brandt, Bernard Rolfe
The purpose of this research is to develop a hybrid experimental and computational model to estimate the absorption of the laser for Laser-Based Powder Bed Fusion (LB-PBF) of IN718. The research also aims to find an underlying knowledge on the effect of absorption ratio on meltpool morphology. This model helps to improve the accuracy of the prediction of the meltpool morphology and the rheology of the melt tracks as well as the temperature-related phenomena in the process. In this paper, two test sets for the initial test with constant and dynamic/(process parameters dependent) absorption ratios were simulated. Melt tracks with different process parameters are printed and simulated from low to high energy density. Then, the Absorption Ratio (AR) is changed for each simulation until the same meltpool depth as the experimental results is obtained. In the next step, the temperature of the meltpool in the interaction area of the laser and material is measured from the performed simulations. Based on the obtained temperature and process parameters, a mathematical model is developed to estimate the absorption ratio in different conditions. The model is validated in hybrid computational and experimental conditions. The investigation provides the first model to calculate the absorption ratio in LB-PBF based on the temperature of the meltpool and process parameters. Results show that the developed model significantly enhances the accuracy of estimating meltpool features such as temperature, rheological and thermophysical properties of the material in the melting state.

History

Journal

Optics and Laser Technology

Volume

153

Number

108263

Start page

1

End page

14

Total pages

14

Publisher

Elsevier

Place published

United Kingdom

Language

English

Copyright

© 2022 Published by Elsevier Ltd.

Former Identifier

2006117056

Esploro creation date

2022-09-14

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