GRI-Mech 3.0

GRI-Mech 3.0 is an optimized mechanism designed to model natural gas combustion, including NO formation and reburn chemistry. It is the successor to version 2.11, and another step in the continuing updating evolution of the mechanism. The optimization process is designed to provide sound basic kinetics which also furnish the best combined modeling predictability of basic combustion properties. Improvements were made in the categories of updating the kinetics with recent literature results, including some new and improved target experiments to the optimization, expanding the mechanism and target selection, and examining the sensitivity to the thermodynamics.


References in zbMATH (referenced in 88 articles )

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  1. Romero-Anton, N.; Martin-Escudero, K.; Ren, Mengmeng; Azkorra-Larrinaga, Z.: Consideration of the interactions between the reaction zones in the new extended eddy dissipation concept model (2022)
  2. Gupta, Harshit; Teerling, Omkejan J.; van Oijen, Jeroen A.: Effect of progress variable definition on the mass burning rate of premixed laminar flames predicted by the flamelet generated manifold method (2021)
  3. Inanc, Eray; Kempf, Andreas M.; Chakraborty, Nilanjan: Effect of sub-grid wrinkling factor modelling on the large eddy simulation of turbulent stratified combustion (2021)
  4. Li, Wenyu; Hegde, Arun; Oreluk, James; Packard, Andrew; Frenklach, Michael: Representing model discrepancy in bound-to-bound data collaboration (2021)
  5. Orlac’h, Jean-Maxime; Darabiha, Nasser; Giovangigli, Vincent; Franzelli, Benedetta: Importance of mass and enthalpy conservation in the modelling of titania nanoparticles flame synthesis (2021)
  6. Papapostolou, Vassilios Stergios; Turquand d’Auzay, Charles; Chakraborty, Nilanjan: Effects of the spatial distribution of (\mathrmCO_2) dilution on localised forced ignition of stoichiometric (\mathrmCH_4)-(\mathrmCO_2)-air mixtures (2021)
  7. Plotnikov, M. Yu.; Shkarupa, E. V.: Two approaches to calculating composition of rarefied gas mixture exposed to chemical reactions at flow through cylindrical channel (2021)
  8. Sarkar, Sourav; Mukhopadhyay, Achintya; Sen, Swarnendu: The effects of steam and water spray on NO formation in a methane-air counterflow diffusion flame (2021)
  9. Xu, Rui; Le, Van Minh; Marchand, Alexis; Rogaume, Thomas; Richard, Franck; Luche, Jocelyn; Trouvé, Arnaud: The unsteady response of radiating laminar diffusion flames exposed to decreasing mixing rate conditions representative of fires (2021)
  10. Belov, A. A.; Kalitkin, N. N.: Method for experimental data processing concerning chemical reaction rates in low-atomic gases (2020)
  11. Both, A.; Lehmkuhl, O.; Mira, D.; Ortega, M.: Low-dissipation finite element strategy for low Mach number reacting flows (2020)
  12. Kulkarni, Tejas; Buttay, Romain; Kasbaoui, M. Houssem; Attili, Antonio; Bisetti, Fabrizio: Reynolds number scaling of burning rates in spherical turbulent premixed flames (2020)
  13. Miranda, F. C.; Coelho, P. J.; Ströhle, J.; Janicka, J.: Large-eddy simulation of a bluff-body stabilised nonpremixed flame with radiation heat transfer (2020)
  14. Sawant, N.; Dorschner, B.; Karlin, I. V.: Consistent lattice Boltzmann model for multicomponent mixtures (2020)
  15. Wang, Yiqing; Jayachandran, Jagannath; Chen, Zheng: Effects of pressure rise rate on laminar flame speed under normal and engine-relevant conditions (2020)
  16. Bode, Mathis; Collier, Nathan; Bisetti, Fabrizio; Pitsch, Heinz: Adaptive chemistry lookup tables for combustion simulations using optimal B-spline interpolants (2019)
  17. Emmett, Matthew; Motheau, Emmanuel; Zhang, Weiqun; Minion, Michael; Bell, John B.: A fourth-order adaptive mesh refinement algorithm for the multicomponent, reacting compressible Navier-Stokes equations (2019)
  18. Farokhi, Mohammadreza; Birouk, Madjid: A hybrid EDC/flamelet approach for modelling biomass combustion of grate-firing furnace (2019)
  19. Jesch, David; Bevrnja, Alija; di Mare, Francesca; Janicka, Johannes; Sadiki, Amsini: Large eddy simulation of a turbulent flame using tabulated chemistry with a novel multivariate PDF (2019)
  20. Kaplan, Carolyn R.; Özgen, Alp; Oran, Elaine S.: Chemical-diffusive models for flame acceleration and transition-to-detonation: genetic algorithm and optimisation procedure (2019)

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