/OstRipening

Primary LanguagePython

OstwaldRipening - pore network for ostwald ripening simulation

This repository hosts the classical network flow code for the simulation of ostwald ripening, written in python. This code extends the capabilities of pnflowPy.

Getting Started

  • Install your favorite Python distribution if you don't already have one (we used Anaconda). You may want to choose a distribution that has the standard packages pre-installed
  • Install required libraries (check the Dependencies below)
  • Download the code
  • Run the examples.

Dependencies

There are a few extra libraries to install:

  • pandas
  • scipy
  • sortedcontainers
  • numpy_indexed
  • petsc4py

Installation

Quick installation can be achieved by replicating the environment in Anaconda:

  1. Clone the repo 
    git clone https://github.com/ImperialCollegeLondon/pnflowPy.git
  2. Configure conda 
    conda update conda
conda config --set ssl_verify false
  3. Replicate the environment: 
    conda env create -f environment.yml
  4. Activate the environment: 
    conda activate flowmodel
  • If numba was not installed, try: 
    conda install -c numba numba
  • If numpy-indexed was not installed, try: 
    pip install numpy-indexed

Running pnflowPy

To run the OstRipening code, you should first generate the networks from the images using the pnextract or poreXtractor module, see the documentation of pnextract executable. Then you should copy the generated networks into the data folder and edit the input_pnflow.dat by setting the NETWORK keyword and other keywords. Full descriptions of the keywords in the input_pnflow.dat can be found in doc/pnflow_guide.pdf inside the pnflow module. However, only the keywords inside the input_pnflow.dat have been implemented, others might be added later for more robustness.

You can then run the pnflowPy by doing the following:

  1. Change directory into the OstRipening folder.
  2. Running the following command in terminal or in Windows command-prompt (cmd): 
    python main.py data/input_pnflow.dat

The generated network files of a 1000 cube water-wet Bentheimer sandstone have been provided in the data folder (image can be found in https://www.imperial.ac.uk/earth-science/research/research-groups/pore-scale-modelling/micro-ct-images-and-networks/) and this could be used for an example.

Contributions

It would be very great to make any contributions to this project to make it better. If you would like to contribute, please fork the repo and create a pull request or simply open an issue with the tag "contribution". Please give this project a star. Thank you!

License

Distributed under the MIT License.

Contact and References

For contacts and references please see: https://www.imperial.ac.uk/earth-science/research/research-groups/pore-scale-modelling

Alternatively, contact Ademola Adebimpe: