Large eddy simulation of multi-regime burner: a reaction mechanism sensitivity analysis
Ciottoli, Pietro Paolo
Hernandez Perez, Francisco
Im, Hong G.
Malpica Galassi, Riccardo
KAUST DepartmentMechanical Engineering
Physical Science and Engineering (PSE) Division
Clean Combustion Research Center
Mechanical Engineering Program
Permanent link to this recordhttp://hdl.handle.net/10754/674898
MetadataShow full item record
AbstractHigh Reynolds number jets and mixture inhomogeneities enhance the presence of local reaction zones at different combustion regimes. From a modeling perspective, the multi-regime process requires ad-hoc models to be accurately described. In this work, highly resolved large eddy simulations of the Darmstadt multi-regime burner, which spans regimes from a fully non-premixed flame in the core jet region to an outer premixed flame as well as local extinction and re-ignition, are conducted using the eddy dissipation concept. Three different reaction mechanisms for methane are considered to study the effects of the kinetics model on the solution, including the detailed GRI Mech 3.0 and two reduced ones. The averages and fluctuations of the main scalars are compared against experimental data, and the mixing lines and conditional averages in the mixture fraction-progress variable space are also contrasted. The results highlight that a detailed description of chemical kinetics leads to a shrinkage of the predicted non-premixed flame and improves the prediction of the carbon monoxide mass fraction, when compared to the predictions obtained with the reduced chemistry models.
CitationAngelilli, L., Ciottoli, P. P., Hernandez Perez, F. E., Valorani, M., Im, H. G., & Malpica Galassi, R. (2022). Large eddy simulation of multi-regime burner: a reaction mechanism sensitivity analysis. AIAA SCITECH 2022 Forum. doi:10.2514/6.2022-0639
SponsorsThe authors acknowledge the support of the Italian Ministry of University and Research (MIUR) and King Abdullah University of Science and Technology (KAUST). Computational resources were provided by the KAUST Supercomputing Laboratory (KSL).
Conference/Event nameAIAA SCITECH 2022 Forum