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Numerical treatment for Darcy–Forchheimer flow of propylene glycol with carbon nanotubes under the impacts of MHD and activation energy

Abstract This study is the application of a recurrent neural networks with Bayesian regularization optimizer (RNNs-BRO) to analyze the effect of various physical parameters on fluid velocity, temperature, and mass concentration profiles in the Darcy–Forchheimer flow of propylene glycol mixed with ca...

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Principais autores: Hafiz Muhammad Shahbaz, Iftikhar Ahmad
Formato: Artigo
Idioma:Inglês
Publicado em: Nature Portfolio 2024-12-01
coleção:Scientific Reports
Assuntos:
Activation energy
Propylene glycol
Carbon nanotubes
Recurrent neural networks
Bayesian regularization
Acesso em linha:https://doi.org/10.1038/s41598-024-82569-3
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