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20102023
most citedSciANN: A Keras/Tensorflow wrapper for scientific computations and physics-informed deep learning using artificial neural networks

428 citations · 1.5k across the 19 of their papers we have counts for

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physics.flu-dyn2023★ 2 cited

A Darcy-Cahn-Hilliard model of multiphase fluid-driven fracture

Alexandre Guével, Yue Meng, Christian Peco +2

A Darcy-Cahn-Hilliard model coupled with damage is developed to describe multiphase-flow and fluid-driven fracturing in porous media. The model is motivated by recent experimental…

physics.flu-dyn2023★ 2 cited

Direct comparison of numerical simulations and experiments of CO injection and migration in geologic media: Value of local data and predictability

Lluís Saló-Salgado, Malin Haugen, Kristoffer Eikehaug +3

The accuracy and robustness of numerical models of geologic CO sequestration are almost never quantified with respect to direct observations that provide a ground truth. Here,…

physics.flu-dyn2019★ 114 cited

Signatures of fluid-fluid displacement in porous media: wettability, patterns, and pressures

Bauyrzhan K. Primkulov, Amir A. Pahlavan, Xiaojing Fu +3

We develop a novel `moving capacitor' dynamic network model to simulate immiscible fluid-fluid displacement in porous media. Traditional network models approximate the pore geometr…

physics.flu-dyn2017★ 80 cited

Anomalous transport in disordered fracture networks: spatial Markov model for dispersion with variable injection modes

Peter Kang, Marco Dentz, Tanguy Le Borgne +2

We investigate tracer transport on random discrete fracture networks that are characterized by the statistics of the fracture geometry and hydraulic conductivity. While it is well…

physics.flu-dyn2010★ 245 cited

Fluid Mixing from Viscous Fingering

Birendra Jha, Luis Cueto-Felgueroso, Ruben Juanes

Viscous fingering is a well-known hydrodynamic instability that sets in when a less viscous fluid displaces a more viscous fluid. When the two fluids are miscible, viscous fingerin…