Computationally Efficient Multiscale Neural Networks Applied to Fluid Flow in Complex 3D Porous Media
Wen Pan
Transport in Porous Media, 2021
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ML-LBM: Machine Learning Aided Flow Simulation in Porous Media
Traiwit Chung
ArXiv, 2020
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Prediction of Porous Media Fluid Flow with Spatial Heterogeneity Using Criss-Cross Physics-Informed Convolutional Neural Networks
Mpoki Sam Mwasamwasa
Cmes-computer Modeling in Engineering & Sciences, 2023
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Neural solution of elliptic partial differential equation problem for single phase flow in porous media
Vytautas Kraujalis
Mathematical Models in Engineering
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Predicting porosity, permeability, and tortuosity of porous media from images by deep learning
Maciej Matyka
Scientific Reports, 2020
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A gradient-based deep neural network model for simulating multiphase flow in porous media
Hussein Hoteit
Journal of Computational Physics
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Physics Informed Neural Network in Turbulent Porous Flow: Pore-scale Flow Reconstruction
mohammad jadidi
Proceedings of the World Congress on Momentum, Heat and Mass Transfer, 2024
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Deep learning for diffusion in porous media
Dawid Strzelczyk
arXiv (Cornell University), 2023
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Encoder–Decoder Convolutional Neural Networks for Flow Modeling in Unsaturated Porous Media: Forward and Inverse Approaches
Nima Kamali
Water
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Leveraging machine learning in porous media
Hossein Mashhadimoslem
Journal of Materials Chemistry A, 2024
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Predicting Effective Diffusivity of Porous Media from Images by Deep Learning
Rui Qiao
Scientific Reports
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Influence of the parameters of the convolutional neural network model in predicting the effective compressive modulus of porous structure
Sergei Bosiakov
Frontiers in Bioengineering and Biotechnology, 2022
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Learning Generic Solutions for Multiphase Transport in Porous Media via the Flux Functions Operator
Shayma Alkobaisi
arXiv (Cornell University), 2023
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Effect of Antecedent Conditions on Prediction of Pore-Water Pressure using Artificial Neural Networks
Muhammad Tayyab Mustafa
Modern Applied Science, 2012
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Artificial Neural Network to Determine Dynamic Effect in Capillary Pressure Relationship for Two-Phase Flow in Porous Media with Micro-Heterogeneities
Navraj Hanspal
Environmental Processes, 2014
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Towards an hybrid computational strategy based on Deep Learning for incompressible flows
Antonio Alguacil
AIAA AVIATION 2020 FORUM, 2020
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Physics-informed Neural Networks with Periodic Activation Functions for Solute Transport in Heterogeneous Porous Media
Pingki Datta
Cornell University - arXiv, 2022
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AI Fluid Flow AIFF for Understanding Porous Media Behavior from Micro to Reservoir Scale Aided by Machine Learning
Omar Al-Farisi
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Pore Pressure Prediction from Seismic Data using Neural Network
Dip Kumar Singha
SPG, India
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Predicting high-fidelity multiphysics data from low-fidelity fluid flow and transport solvers using physics-informed neural networks
Maryam Aliakbari
International Journal of Heat and Fluid Flow, 2022
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Poroelastic model parameter identification using artificial neural networks: on the effects of heterogeneous porosity and solid matrix Poisson ratio
hamidreza dehghani
Computational Mechanics
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Residual-based adaptivity for two-phase flow simulation in porous media using Physics-informed Neural Networks
John Hanna
Computer Methods in Applied Mechanics and Engineering
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Real-time relative permeability prediction using deep learning
Ovoke Arigbe
Journal of Petroleum Exploration and Production Technology, 2018
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NEURAL NETWORKS FOR AIR PERMEABILITY PREDICTION
Michal Vik, Martina Viková
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Application of feedforward neural network in the study of dissociated gas flow along the porous wall
Slobodan Savic
Expert Systems With Applications, 2011
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An improved technique in porosity prediction: a neural network approach
Ian Taggart
IEEE Transactions on Geoscience and Remote Sensing, 1995
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Application of Machine Learning and Artificial Intelligence in Proxy Modeling for Fluid Flow in Porous Media
Shahab Mohaghegh
Fluids, 2019
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Model-parallel Fourier neural operators as learned surrogates for large-scale parametric PDEs
Felix Herrmann
Computers & Geosciences, 2023
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A data-driven proxy to Stoke's flow in porous media
Nasser Nasrabadi
arXiv (Cornell University), 2019
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