Analyzing the efficiency and robustness of deep convolutional neural networks for modeling natural convection in heterogeneous porous media-Reference-Cited by-同舟云学术

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Analyzing the efficiency and robustness of deep convolutional neural networks for modeling natural convection in heterogeneous porous media

Published:2022-02 Issue: Volume:183 Page:122131
ISSN:0017-9310
Container-title:International Journal of Heat and Mass Transfer
language:en
Short-container-title:International Journal of Heat and Mass Transfer

Author:

Rajabi Mohammad Mahdi,Hajizadeh Javaran Mohammad Reza,Bah Amadou-oury,Frey Gabriel,Le Ber Florence,Lehmann François,Fahs Marwan

Publisher

Elsevier BV

Subject

Fluid Flow and Transfer Processes,Mechanical Engineering,Condensed Matter Physics

Reference45 articles.

1. Convection in Porous Media;Nield,2017

2. Modeling Approaches to Natural Convection in Porous Media;Su,2015

3. Polynomial chaos expansions for uncertainty propagation and moment independent sensitivity analysis of seawater intrusion simulations;Rajabi;J. Hydrol. (Amst),2015

4. Analyzing natural convection in porous enclosure with polynomial chaos expansions: effect of thermal dispersion, anisotropic permeability and heterogeneity;Fajraoui;Int. J. Heat Mass Transf.,2017

5. Uncertainty quantification and global sensitivity analysis of double-diffusive natural convection in a porous enclosure;Rajabi;Int. J. Heat Mass Transf.,2020

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