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Application of Zone Method based Physics-Informed Neural Networks in Reheating Furnaces
March 1, 2024, 5:44 a.m. | Ujjal Kr Dutta, Aldo Lipani, Chuan Wang, Yukun Hu
cs.LG updates on arXiv.org arxiv.org
Abstract: Foundation Industries (FIs) constitute glass, metals, cement, ceramics, bulk chemicals, paper, steel, etc. and provide crucial, foundational materials for a diverse set of economically relevant industries: automobiles, machinery, construction, household appliances, chemicals, etc. Reheating furnaces within the manufacturing chain of FIs are energy-intensive. Accurate and real-time prediction of underlying temperatures in reheating furnaces has the potential to reduce the overall heating time, thereby controlling the energy consumption for achieving the Net-Zero goals in FIs. In …
abstract application arxiv automobiles bulk construction cs.ai cs.lg cs.ne cs.sy diverse eess.sy energy etc foundation glass industries manufacturing materials metals networks neural networks paper physics physics-informed set type
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