Adaptive hyper reduction for additive manufacturing thermal fluid analysis
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2020-08-18
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Lu, Ye, Kevontrez Kyvon Jones, Zhengtao Gan, and Wing Kam Liu. “Adaptive Hyper Reduction for Additive Manufacturing Thermal Fluid Analysis.” Computer Methods in Applied Mechanics and Engineering 372 (December 1, 2020): 113312. https://doi.org/10.1016/j.cma.2020.113312.
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Abstract
Thermal fluid coupled analysis is essential to enable an accurate temperature prediction in additive manufacturing. However, numerical simulations of this type are time-consuming, due to the high non-linearity, the underlying large mesh size and the small time step constraints. This paper presents a novel adaptive hyper reduction method for speeding up these simulations. The difficulties associated with non-linear terms for model reduction are tackled by designing an adaptive reduced integration domain. The proposed online basis adaptation strategy is based on a combination of a basis mapping, enrichment by local residuals and a gappy basis reconstruction technique. The efficiency of the proposed method will be demonstrated by representative 3D examples of additive manufacturing models, including single-track and multi-track cases.