[HTML][HTML] Physics-informed online learning for temperature prediction in metal AM

P Sajadi, M Rahmani Dehaghani, Y Tang, GG Wang - Materials, 2024 - mdpi.com
In metal additive manufacturing (AM), precise temperature field prediction is crucial for
process monitoring, automation, control, and optimization. Traditional methods, primarily …

A novel deep learning model for the real-time prediction of emissivity and thermal history in metal additive manufacturing processes

C Liu, T Yuan, H Shan, Y Wang, H Lai… - Journal of Manufacturing …, 2025 - Elsevier
Thermal history during the additive manufacturing (AM) process significantly influences the
performance of the produced structures. In numerous studies, researchers have focused on …

Real-Time 2D Temperature Field Prediction in Metal Additive Manufacturing Using Physics-Informed Neural Networks

P Sajadi, MR Dehaghani, Y Tang, GG Wang - arxiv preprint arxiv …, 2024 - arxiv.org
Accurately predicting the temperature field in metal additive manufacturing (AM) processes
is critical to preventing overheating, adjusting process parameters, and ensuring process …