Benchmark Study of Melted Track Geometries in Laser Powder Bed Fusion of Inconel 625
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2021-06-01
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Gan, Zhengtao, Kevontrez K. Jones, Ye Lu, and Wing Kam Liu. “Benchmark Study of Melted Track Geometries in Laser Powder Bed Fusion of Inconel 625.” Integrating Materials and Manufacturing Innovation 10, no. 2 (June 1, 2021): 177–95. https://doi.org/10.1007/s40192-021-00209-4.
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This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s40192-021-00209-4
Abstract
In the Air Force Research Laboratory Additive Manufacturing Challenge Series, melted track geometries for a laser powder bed fusion (L-PBF) process of Inconel 625 were used to challenge and validate computational models predicting melting and solidification behavior. The impact of process parameters upon single-track single-layer, multi-track single-layer, and single-track multi-layer L-PBF processes was studied. To accomplish this, a physics-based thermal-fluid model was developed and calibrated using a proper generalized decomposition surrogate model, then compared against the experimental measurements. The thermal-fluid model was enhanced through the usage of an adaptive mesh and residual heat factor (RHF) model, based on the scanning strategy, for improved efficiency and accuracy. It is found that this calibration approach is not only robust and efficient, but it also enables the thermal-fluid model to make predictions which quantitatively agree well with the experimental measurements. The adaptive mesh provides over a 10-times speedup as compared to a uniform mesh. The RHF model improves predictive accuracy by over 60%, particularly near starting and ending points of the melted tracks, which are greatly affected by the thermal behavior of adjacent tracks. Moreover, the thermal-fluid model is shown to potentially predict lack-of-fusion defects and provide insights into the defect generation process in L-PBF.