A self-supervised physics-informed neural network is claimed to estimate liquid sodium Nusselt numbers in miniature heat sinks to about 8% error, but the evidence for an advantage over plain neural networks is weak and the network's loss function is ambiguously defined.
Prediction of thermal conductivity of ethylene glycol –water solutions by using artificial neural networks,
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SPINN: An Optimal Self-Supervised Physics-Informed Neural Network Framework
A self-supervised physics-informed neural network is claimed to estimate liquid sodium Nusselt numbers in miniature heat sinks to about 8% error, but the evidence for an advantage over plain neural networks is weak and the network's loss function is ambiguously defined.