A Robust Reacting Flow Solver with Computational Diagnostics Based on OpenFOAM and Cantera

Dezhi Zhou, Hongyuan Zhang, Suo Yang

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


In this study, we developed a new reacting flow solver based on OpenFOAM (OF) and Can-tera, with the capabilities of (i) dealing with detailed species transport and chemistry, (ii) integration using a well-balanced splitting scheme, and (iii) two advanced computational diagnostic methods. First of all, a flaw of the original OF chemistry model to deal with pressure-dependent reactions is fixed. This solver then couples Cantera with OF so that the robust chemistry reader, chemical reaction rate calculations, ordinary differential equations (ODEs) solver, and species transport properties handled by Cantera can be accessed by OF. In this way, two transport models (mixture-averaged and constant Lewis number models) are implemented in the coupled solver. Finally, both the Strang splitting scheme and a well-balanced splitting scheme are implemented in this solver. The newly added features are then assessed and validated via a series of auto-ignition tests, a perfectly stirred reactor, a 1D unstretched laminar premixed flame, a 2D counter-flow laminar diffusion flame, and a 3D turbulent partially premixed flame (Sandia Flame D). It is shown that the well-balanced property is crucial for splitting schemes to accurately capture the ignition and extinction events. To facilitate the understanding on combustion modes and complex chemistry in large scale simulations, two computational diagnostic methods (conservative chemical explosive mode analysis, CCEMA, and global pathway analysis, GPA) are subsequently implemented in the current framework and used to study Sandia Flame D for the first time. It is shown that these two diagnostic methods can extract the flame structure, combustion modes, and controlling global reaction pathways from the simulation data.

Original languageEnglish (US)
Article number102
Issue number2
StatePublished - Feb 2022

Bibliographical note

Funding Information:
Funding: S. Yang gratefully acknowledges the faculty start-up funding from the University of Minnesota—Twin Cities. H. Zhang gratefully acknowledges the support from the 3M Science and Technology Doctoral Fellowship, UMII MnDRIVE Graduate Assistantship Award, and Frontera Computational Science Fellowship.

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.


  • Chemical explosive mode analysis (CEMA)
  • Global pathway analysis (GPA)
  • Reacting flow solver
  • Well-balanced splitting scheme


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