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Article

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

Department of Mechanical Engineering, University of Minnesota–Twin Cities, Minneapolis, MN 55455, USA
*
Author to whom correspondence should be addressed.
Current address: UM-SJTU Joint Institute, Shanghai Jiao Tong University, Shanghai 200240, China.
Aerospace 2022, 9(2), 102; https://doi.org/10.3390/aerospace9020102
Submission received: 4 January 2022 / Revised: 2 February 2022 / Accepted: 8 February 2022 / Published: 14 February 2022
(This article belongs to the Section Aeronautics)

Abstract

In this study, we developed a new reacting flow solver based on OpenFOAM (OF) and Cantera, 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.
Keywords: reacting flow solver; well-balanced splitting scheme; chemical explosive mode analysis (CEMA); global pathway analysis (GPA) reacting flow solver; well-balanced splitting scheme; chemical explosive mode analysis (CEMA); global pathway analysis (GPA)

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MDPI and ACS Style

Zhou, D.; Zhang, H.; Yang, S. A Robust Reacting Flow Solver with Computational Diagnostics Based on OpenFOAM and Cantera. Aerospace 2022, 9, 102. https://doi.org/10.3390/aerospace9020102

AMA Style

Zhou D, Zhang H, Yang S. A Robust Reacting Flow Solver with Computational Diagnostics Based on OpenFOAM and Cantera. Aerospace. 2022; 9(2):102. https://doi.org/10.3390/aerospace9020102

Chicago/Turabian Style

Zhou, Dezhi, Hongyuan Zhang, and Suo Yang. 2022. "A Robust Reacting Flow Solver with Computational Diagnostics Based on OpenFOAM and Cantera" Aerospace 9, no. 2: 102. https://doi.org/10.3390/aerospace9020102

APA Style

Zhou, D., Zhang, H., & Yang, S. (2022). A Robust Reacting Flow Solver with Computational Diagnostics Based on OpenFOAM and Cantera. Aerospace, 9(2), 102. https://doi.org/10.3390/aerospace9020102

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