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 66 articles )

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  1. Li, Wenyu; Hegde, Arun; Oreluk, James; Packard, Andrew; Frenklach, Michael: Representing model discrepancy in bound-to-bound data collaboration (2021)
  2. 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)
  3. Belov, A. A.; Kalitkin, N. N.: Method for experimental data processing concerning chemical reaction rates in low-atomic gases (2020)
  4. Both, A.; Lehmkuhl, O.; Mira, D.; Ortega, M.: Low-dissipation finite element strategy for low Mach number reacting flows (2020)
  5. Kulkarni, Tejas; Buttay, Romain; Kasbaoui, M. Houssem; Attili, Antonio; Bisetti, Fabrizio: Reynolds number scaling of burning rates in spherical turbulent premixed flames (2020)
  6. Sawant, N.; Dorschner, B.; Karlin, I. V.: Consistent lattice Boltzmann model for multicomponent mixtures (2020)
  7. Muela, J.; Borrell, R.; Ventosa-Molina, J.; Jofre, L.; Lehmkuhl, O.; Pérez-Segarra, C. D.: A dynamic load balancing method for the evaluation of chemical reaction rates in parallel combustion simulations (2019)
  8. Müller, Juliane; Day, Marcus: Surrogate optimization of computationally expensive black-box problems with hidden constraints (2019)
  9. Pant, Tejas; Han, Chao; Wang, Haifeng: Examination of errors of table integration in flamelet/progress variable modeling of a turbulent non-premixed jet flame (2019)
  10. Bykov, V.; Gubernov, V. V.; Maas, U.: Mechanisms performance and pressure dependence of hydrogen/air burner-stabilized flames (2018)
  11. Hegde, Arun; Li, Wenyu; Oreluk, James; Packard, Andrew; Frenklach, Michael: Consistency analysis for massively inconsistent datasets in bound-to-bound data collaboration (2018)
  12. Jeon, Min-Kyu; Kim, Nam Il: Fuel pyrolysis and its effects on soot formation in non-premixed laminar jet flames of methane, propane, and DME (2018)
  13. Kim, Hun Young; Lee, Jiseop; Kim, Nam Il: Effects of N(_2)/CO(_2) dilution on flame propagation velocities and quenching distances of oxy-methane premixed mixtures using an annular-stepwise-diverging-tube (ASDT) (2018)
  14. Morrison, Rebecca E.; Oliver, Todd A.; Moser, Robert D.: Representing model inadequacy: a stochastic operator approach (2018)
  15. Tang, Kunkun; Massa, Luca; Wang, Jonathan; Freund, Jonathan B.: An adaptive least-squares global sensitivity method and application to a plasma-coupled combustion prediction with parametric correlation (2018)
  16. Xie, Qing; Xiao, Zhixiang; Ren, Zhuyin: A spectral radius scaling semi-implicit iterative time stepping method for reactive flow simulations with detailed chemistry (2018)
  17. Zhang, Hongda; Yu, Zhou; Ye, Taohong; Cheng, Ming; Zhao, Majie: Large eddy simulation of turbulent stratified combustion using dynamic thickened flame coupled with tabulated detailed chemistry (2018)
  18. Fooladgar, Ehsan; Chan, C. K.; Nogenmyr, Karl-Johan: An accelerated computation of combustion with finite-rate chemistry using LES and an open source library for in-situ-adaptive tabulation (2017)
  19. Kang, Xin; Gollan, Rowan J.; Jacobs, Peter A.; Veeraragavan, Ananthanarayanan: On the influence of modelling choices on combustion in narrow channels (2017)
  20. Maxwell, Brian McN.; Bhattacharjee, R. R.; Lau-Chapdelaine, S. S. M.; Falle, S. A. E. G.; Sharpe, G. J.; Radulescu, M. I.: Influence of turbulent fluctuations on detonation propagation (2017)

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