Dynamic adaptive chemistry with mechanisms tabulation and in situ adaptive tabulation (ISAT)for computationally efficient modeling of turbulent combustion

To deal with the major challenges of combustion simulation with detailed chemical kinetics, a new dynamic adaptive chemistry method with mechanisms tabulation (DAC-ST: DAC with single tabulation)and a method in which DAC-ST is combined with the ISAT (In Situ Adaptive Tabulation)approach (DAC-DT: DAC with double tabulation)to accelerate numerical calculation of large chemical mechanisms in turbulent combustion flows are proposed. Compared to the conventional DAC, DAC-ST expedites calculations by tabulating and reusing the reduced mechanisms, and DAC-DT further expedites the calculations by reducing the number of direct ordinary differential equations (ODEs)integrations and tabulating and retrieving the solutions. The correlation of the two mechanisms is evaluated by a pre-specified criterion comprising temperature, pressure, fuel, oxygen, OH, CH₂O, and HO₂, and can be updated by a user-specified threshold value. The proposed methods were validated in a piloted partially premixed methane/air diffusion flame (Sandia Flame D)with the 53-species GRI-Mech 3.0 and a hydrogen fueled model scramjet combustor (DLR)with 9 species and 27 reactions. The results indicate that the two proposed methods can accurately capture the flame structure and that the relative percentage errors of temperature and species concentration are well-controlled and proportional to the threshold values. Further, compared to the conventional DAC, detailed diagnostics show that DAC-ST and DAC-DT reduce the computational overhead of mechanism reduction by factors of 41 and 96 for Flame D and 165 and 365 for DLR, respectively. They also speed up ODE integration by factors of 3.9 and 7.8 for Flame D and 1.6 and 4.0 for DLR, respectively. The successful validation demonstrates that the two proposed methods can be efficiently used in the simulation of reactive flow for detailed kinetic mechanisms, especially for the case with a large number of cells, e.g., DNS.