most citedHybrid thermal modeling of additive manufacturing processes using physics-informed neural networks for temperature prediction and parameter identification

150 citations · 150 across the 1 of their papers we have counts for

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1 paper

cs.LG2022★ 150 cited

Hybrid thermal modeling of additive manufacturing processes using physics-informed neural networks for temperature prediction and parameter identification

Shuheng Liao, Tianju Xue, Jihoon Jeong +3

Understanding the thermal behavior of additive manufacturing (AM) processes is crucial for enhancing the quality control and enabling customized process design. Most purely physics…