Numerical Simulations of Heat Loss Effect on Premixed Jet Flame Using Flamelet Generated Manifold Combustion Model

Jesse W. Hofsteenge, Alireza Ghasemi Khourinia and Jim B. W. Kok
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Jesse W. Hofsteenge: Department of Thermal Engineering, Mechanical Engineering, Universitity of Twente, De Horst 2, 7522 NB Enschede, The Netherlands
Alireza Ghasemi Khourinia: Department of Thermal Engineering, Mechanical Engineering, Universitity of Twente, De Horst 2, 7522 NB Enschede, The Netherlands
Jim B. W. Kok: Department of Thermal Engineering, Mechanical Engineering, Universitity of Twente, De Horst 2, 7522 NB Enschede, The Netherlands

Energies, 2022, vol. 15, issue 3, 1-17

Abstract: Numerical simulations are performed on a combustor setup which represents the recirculating behaviour of a combustor in the flameless combustion regime. Previous experimental and numerical studies showed that heat loss is prominent for this setup. Here, the amount of heat loss through the combustor walls is quantified and its effect analysed. For this a non-adiabatic Flamelet Generated Manifold (FGM) model is employed. This model uses tabulated chemistry in combination with governing equations for a small set of control variables to accurately describe a turbulent flame. In the current implementation, equations for enthalpy and the mean and variance of the reaction progress variable are solved. Turbulence-chemistry interactions are incorporated through a presumed-PDF approach. In contrast to earlier work, the model is applied in the commercial solver Ansys CFX, coupled to a low-mach, compressible, steady-state Reynolds-Averaged Navier-Stokes (RANS) turbulence model. Results from the simulations show that heat loss consumes over 30% of the combustor’s thermal power. Despite this large heat loss, its effect on the combustion chemistry is small. The inclusion of heat loss in the chemistry tabulation does improve the prediction of the velocity and temperature field in the primary reaction zone. However, the effect of including heat loss is limited in the prediction of species concentrations.

Keywords: turbulent combustion; tabulated chemistry; modelling; numerical simulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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