A priori assessment of flame surface density modelling for large-eddy simulation of sound generation by turbulent premixed flames

This paper presents an a priori assessment of flame surface density modelling in the context of large-eddy simulation (LES), with a focus on flame-generated sound. A direct numerical simulation (DNS) dataset of a stoichiometric premixed, methane-air, round jet flame in the thin reaction zones (TRZ) regime is used to perform this assessment. Models for different parts of the filtered flame front displacement term (rho Sd)| backward difference c| are studied, including those for the surface averaged density weighted displacement speed (rho Sd)s and flame wrinkling factor models proposed by Charlette at al. (2002), Fureby (2005) and Muppala et al. (2005).In the first step, the wrinkling factor, the flame surface density and their conditional averages with the filtered progress variable are examined. Locally, large deviations of the modelled wrinkling factor from the DNS data are observed, especially near flame annihilation events. Nevertheless, the conditionally averaged flame surface density is predicted well by the Charlette and Fureby models.In the second step, Lighthill's acoustic analogy is used to assess the models when the time derivative of the filtered flame front displacement term is used as a source. When the wrinkling factor is calculated with the models and (rho Sd)s is obtained from the DNS, a reasonable agreement is achieved for the un- steady pressure and sound pressure level (SPL) of the generated noise. However, when the exact (rho Sd)s is replaced with simple models, a significant underprediction of SPL is observed. These results suggest that flame surface density modelling requires significant improvement, particularly for (rho Sd)s. Furthermore, special attention needs to be paid to flame annihilation events, which feature large variation of the wrinkling factor and flame displacement speed.(c) 2022 The Combustion Institute. Published by Elsevier Inc. All rights reserved.