Data Driven Modelling Special Interest Group

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Scope

For us, data-driven modeling comprises a variety of different topics, some of which are listed below:

  • machine learning (ML): combining CFD and ML, e.g., using ML models in CFD or deriving ML models from CFD data
  • data science: analyzing CFD data to guide modeling and decision making
  • data engineering: aggregating, storing, and processing CFD data

The following list briefly summarizes our current objectives:

  • short term objectives
    • reduce the technical barrier to get started with data-driven modeling in OpenFOAM to enable more people to include data-driven workflows in their applications or research
    • promote data-driven techniques that are already available in OpenFOAM, e.g., dynamic mode decomposition (DMD)
    • promote third-party libraries for data-driven modeling that are based on or built for OpenFOAM
  • long term objectives
    • aid the understanding of when and how to use data-driven modeling in the CFD workflow
    • accelerate developments and applications of data-driven approaches around OpenFOAM
    • establish tested data-driven techniques as a natural element of CFD simulations to improve accuracy and/or speed

Work process

A detailed roadmap, as well as a collection of resources, are available on Github. The Github repository is also a great means to get in touch (e.g., via Github issues). Besides the repository, feel free to contact the SIG's chairs, Andre Weiner and Tomislav Marić, or any other member of the SIG.

Meetings

We aim to have short virtual meetings (max. 1h) every two months and meet in person, if possible, at the OpenFOAM conference and workshop. The bi-monthly meetings serve to update all members about the recent progress and to coordinate upcoming efforts. Everybody is welcome to join our meetings. Past and upcoming meetings are listed below:

  • next virtual meeting: September 2022, online
  • July 21 2022, OpenFOAM-v2206 release webinar, slides
  • July 11 2022, in person, 17th OpenFOAM Workshop, Cambridge
  • Jun 9 2022, online, slides
  • Apr 5 2022, online, slides
  • Feb 8 2022, online, slides

Members

  • Andre Weiner, Technical University of Braunschweig, chair
  • Tomislav Marić, Technical University of Darmstadt, co-chair
  • Abhijeet Vishwasrao, Ecole Polytechnique Paris
  • Alex Skillen, The University of Manchester
  • Chiara Pesci, ESI
  • Dirk Gründing, private contributer
  • François Mazen, Kitware
  • Holger Marschall, Technical University of Darmstadt
  • Karthik Kashinath, Nvidia
  • Kutalmis Bercin, ESI-OpenCFD
  • Nausheen Basha, Imperial College London
  • Neil Ashton, Amazon Web Services
  • Rahul Sundar, Indian Insitute of Technology, Madras
  • Reza Lotfi Navaei, Tarbiat Modares University, Tehran
  • Saeed Salehi, Chalmers University of Technology

If you would like to participate actively in this SIG, please get in touch.