Upscaling and Automation: Pushing the Boundaries of Multiscale Modeling through Symbolic Computing

ORAL

Abstract

Macroscopic differential equations that accurately account for microscopic phenomena can be systematically generated using rigorous upscaling methods. However, such methods are time-consuming, prone to error, and become quickly intractable for complex systems with tens or hundreds of equations. To ease these complications, we propose a method of automatic upscaling through symbolic computation. By streamlining the upscaling procedure and derivation of applicability conditions to just a few minutes, the potential for democratization and broad utilization of upscaling methods in real-world applications emerges. We demonstrate the ability of our software prototype, Symbolica, by reproducing homogenized advective-diffusive-reactive (ADR) systems from earlier studies and homogenizing a large ADR system deemed impractical for manual homogenization. Novel upscaling scenarios previously restricted by unnecessarily conservative assumptions are discovered and numerical validation of the models derived by Symbolica is provided.

*This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Agreement No. HR00112090061. The views, opinions and/or findings expressed are those of the authors and should not be interpreted as representing the official views or policies of the Department of Defense or U.S. Government. KP was also supported by the Stanford Graduate Fellowship in Science and Engineering.

Publication: K. Pietrzyk, S. Korneev, M. Behandish, and I. Battiato: Upscaling and Automation: Pushing the Boundaries of Multiscale Modeling through Symbolic Computing. Transport Porous Med. (Accepted)

Presenters

  • Kyle Pietrzyk

    • Stanford University

Authors

  • Kyle Pietrzyk

    • Stanford University
  • Svyatoslav Korneev

    • Palo Alto Research Center
  • Morad Behandish

    • Palo Alto Research Center
  • Ilenia Battiato

    • Stanford Univ