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ogs5py: A Python-API for the OpenGeoSys 5 Scientific Modeling Package.

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This study introduces ogs5py, a Python API for OpenGeoSys 5, enhancing subsurface flow modeling. It bridges complex hydrogeology simulations with Python's flexibility for wider scientific adoption.

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Area of Science:

  • Hydrogeology and Computational Science
  • Environmental Engineering
  • Geosciences

Background:

  • High-performance numerical codes are crucial for subsurface flow and transport modeling in hydrogeology.
  • Existing compiled-language software (C/C++, Fortran) often lacks user-friendliness, hindering wider adoption.
  • OpenGeoSys (OGS) is a powerful open-source solver for complex hydrogeological processes but shares usability challenges.

Purpose of the Study:

  • To introduce ogs5py, a Python API designed to improve the usability and integration of the OpenGeoSys 5 (OGS) scientific modeling package.
  • To provide a flexible and user-friendly Python-based interface for OGS, facilitating wider adoption and application in hydrogeology.
  • To connect OGS simulations with Python's extensive scientific and computational ecosystem.

Main Methods:

  • Development of ogs5py as a Python API for OpenGeoSys 5.
  • Implementation of a fully Python-based project representation for OGS.
  • Inclusion of convenience functions for user interaction with OGS.
  • Integration of OGS with the Python scientific computing environment.

Main Results:

  • A novel Python API (ogs5py) for the OpenGeoSys 5 modeling package.
  • Enhanced user interaction and project management for OGS simulations within Python.
  • Seamless integration of OGS with Python's powerful libraries for data analysis and visualization.
  • Improved accessibility and flexibility for hydrogeological modeling workflows.

Conclusions:

  • ogs5py significantly enhances the usability and accessibility of OpenGeoSys 5 for hydrogeological modeling.
  • The Python API facilitates integration into broader scientific workflows, promoting wider adoption of advanced simulation tools.
  • This development bridges the gap between high-performance scientific codes and the user-friendly Python environment.