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GitHub / samly97 / soil-net
This project used convolutional neural networks to predict the steady-state concentration of 3D porous media, and subsequently calculates the tortuosity. This package includes data generation, processing, training, and post-processing functions. The loss function includes a Laplacian loss, which is a physics-informed loss.
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/samly97%2Fsoil-net
Stars: 0
Forks: 0
Open Issues: 0
License: mit
Language: Python
Repo Size: 41 KB
Dependencies:
0
Created: almost 2 years ago
Updated: about 2 months ago
Last pushed: over 1 year ago
Last synced: about 2 months ago
Topics: convolutional-neural-networks, physics-informed-neural-networks, porous-media
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