Performance Evaluation of RANS-Based Turbulence Models in Predicting Turbulent Non-Premixed Swirling Combustion within a Realistic Can Combustor
Aishvarya Kumar, Ram Prakash Bharti

TL;DR
This paper evaluates various RANS turbulence models in CFD simulations of a realistic can combustor, focusing on their accuracy in predicting flow, temperature, and species concentrations in non-premixed swirling combustion.
Contribution
It provides a detailed comparison of turbulence models, highlighting the superior performance of the SST k-omega model in predicting key flow features and combustion characteristics.
Findings
SST k-omega model predicts flow features more accurately.
The model indicates most combustion occurs in the primary zone.
Higher temperature and TKE predictions support strong mixing.
Abstract
This study has presented a comprehensive computational fluid dynamics (CFD) analysis of combustion flow in a realistic can combustor, evaluating the influence of various turbulence models on flow, thermal, and species fields. The non-premixed combustion modeling is performed using a presumed (beta) PDF approach in conjunction with a steady laminar flamelet model employing the San Diego reaction mechanism, and the turbulence is modeled using the RANS approach. The influence of turbulence models (standard , realizable , SST , LPS-RSM) on the velocity field, such as the mean axial velocity, mean transverse velocity, turbulent kinetic energy (TKE) and shear stress, is analyzed, besides their influence on temperature and species (\ce{C3H8}, \ce{CO2}, and \ce{CO}) concentration. Analysis showed that despite the shortcomings of the isotropic turbulent…
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