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Data · dataset · 2022

A dataset for conduction heat transfer and deep learning

Listed in Teesside University Research Data Repository

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Big data images for conduction heat transfer The related paper has been published here: Edalatifar, Mohammad, Mohammad Bagher Tavakoli, Mohammad Ghalambaz, and Farbod Setoudeh. "Using deep learning to learn physics of conduction heat transfer." Journal of Thermal Analysis and Calorimetry 146, no. 3 (2021): 1435-1452. Links: doi.org/10.1007/s10973-020-09875-6 link.springer.com/article/10.1007/s10973-020-09875-6 Mohammad Edalatifar, Mohammad Ghalambaz, Mohammad Bagher Tavakoli, Farbod Setoudeh, New loss functions to improve deep learning estimation of heat transfer, Neural Computing and Applications Link: doi.org/10.1007/s00521-022-07233-1 Keywords: Deep convolutional neural networks - Loss function - Heat transfer images - Physical images - Artificial intelligence - CFD - Computational fluids dynamics - Finite volume method - Laplace equation - Dirichlet boundary condition

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Provenance · 1 source records, 9 field assertions
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Teesside University Research Data Repositoryoai:data.mendeley.com/rw9yk3c559.220 h agoJSON v1
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