The reliable prediction of the turbulent combustion process in lean flames is of paramount importance in the design of gas turbine combustors. The present work presents an assessment of the capabilities of Flamelet Generated Manifold (FGM) in the framework of Reynolds-Averaged Navier-Stokes (RANS) and Large-Eddy Simulation (LES) At this purpose the TECFLAM swirl burner consisting of a strongly swirling, unconfined natural gas flame was chosen. Results highlight that RANS-FGM succeeds in predicting the main characteristics of the reacting flow field and species concentrations. However, only LES is capable of reproducing the actual turbulent mixing between swirling flow and co-flow, thus leading to appreciable enhancements with respect to RANS results
Methane swirl-stabilized lean burn flames: Assessment of scale-resolving simulations / Pampaloni, Daniele*; Bertini, Davide; Puggelli, Stefano; Mazzei, Lorenzo; Andreini, Antonio. - In: ENERGY PROCEDIA. - ISSN 1876-6102. - ELETTRONICO. - 126:(2017), pp. 834-841. (Intervento presentato al convegno 72nd Conference of the Italian Thermal Machines Engineering Association, ATI 2017 tenutosi a ita nel 2017) [10.1016/j.egypro.2017.08.274].
Methane swirl-stabilized lean burn flames: Assessment of scale-resolving simulations
PAMPALONI, DANIELE;Bertini, Davide;Puggelli, Stefano;Mazzei, Lorenzo;Andreini, Antonio
2017
Abstract
The reliable prediction of the turbulent combustion process in lean flames is of paramount importance in the design of gas turbine combustors. The present work presents an assessment of the capabilities of Flamelet Generated Manifold (FGM) in the framework of Reynolds-Averaged Navier-Stokes (RANS) and Large-Eddy Simulation (LES) At this purpose the TECFLAM swirl burner consisting of a strongly swirling, unconfined natural gas flame was chosen. Results highlight that RANS-FGM succeeds in predicting the main characteristics of the reacting flow field and species concentrations. However, only LES is capable of reproducing the actual turbulent mixing between swirling flow and co-flow, thus leading to appreciable enhancements with respect to RANS results
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