A Python package for performing pore network modeling of porous media

A set of tools for characterizing and analyzing 3D images of porous materials

Python Simulation Tool for Fractured and Deformable Porous Media

Library for performing multiphase simulations (based on the Shan-Chen model) in complicated geometries (i.e. porous media 3D images)

Open source digital rocks software platform for micro-CT, CT, thin sections and borehole image analysis. Includes tools for: annotation, AI, HPC, porous media flow simulation, porosity analysis, permeability analysis and much more.

Random walk to calculate the tortuosity tensor of images

A simple finite difference scheme for the Rayleigh-Bernard equations (buoyancy driven convection).

Open-source preprocessing tool that can create, at the required level of accuracy, a fully conformal uniformly distributed grid for a given realistic fracture network. This leads to a robust way of constructing a hierarchy of Discrete-Fracture-Models for uncertainty quantification of energy production from reservoirs with natural fracture networ…

Acoustic design exploration and material property identification for porous structures

A python package that takes XCT images of porous materials and generates representative digital twin micromodels

Modeling multiphase flow in fractured porous media using DARTS: a simple DFM example. See https://darts.citg.tudelft.nl/ for more information

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.

Code corresponding to paper "Robust time-discretisation and linearisation schemes for singular and degenerate evolution systems modelling biofilm growth" implemented in python using FEniCSx. It covers the biofilm model and the porous medium equation.

Bacterial motility patterns adapt smoothly in response to spatial confinement and disorder [Zhang H., Wetherington M.T., Ko H., FitzGerald C.E., Munro. E.M., Nirody J.A]