Permeability Prediction of Nanoscale Porous Materials Using Discrete Cosine Transform-Based Artificial Neural Networks

Permeability Prediction of Nanoscale Porous Materials Using Discrete Cosine Transform-Based Artificial Neural Networks

The permeability of porous materials determines the fluid flow rate and aids in the prediction of their mechanical properties. This study developed a novel approach that combines the discrete cosine transform (DCT) and artificial neural networks (ANN) for permeability analysis and prediction in digi...

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Bibliographic Details
Main Authors: Dongshuang Li, Shaohua You, Qinzhuo Liao, Gang Lei, Xu Liu, Weiqing Chen, Huijian Li, Bo Liu, Xiaoxi Guo
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Materials
Subjects:
permeability
nanoscale
porous material
discrete cosine transform
artificial neural network
Online Access:https://www.mdpi.com/1996-1944/16/13/4668

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https://www.mdpi.com/1996-1944/16/13/4668

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