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Numerical simulation of soot formation in a gas turbine model combustor
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About the Numerical Simulation of Soot Formation in a Gas turbine model combustor Project
Soot, an undesirable particulate pollutant resulting from incomplete hydrocarbon combustion, poses significant risks to human health and contributes to climate change. Stringent soot emission regulations for combustion devices necessitate accurate prediction of soot behavior in Computational Fluid Dynamics (CFD) simulations. However, modeling soot presents challenges due to the complex interactions between turbulence, chemical reactions, and particulate evolution across various time scales. The population balance equation (PBE) is commonly employed to study soot by tracking the evolution of particle number density function (NDF). While directly solving the PBE is computationally expensive, the method of moments (MOM) offers a computationally efficient alternative by tracking a few lower-order moments of the distribution. The recently proposed Extended Quadrature Method of Moment (EQMOM) enables the reconstruction of the complete NDF from the transported moments. A robust cell-centered finite-volume (FV) framework has been developed in the open-source tool OpenFOAM for turbulent reacting flows. It incorporates a detailed and accurate C++ library for evaluating soot formation using the quadrature-based method of moments approach. The coupled numerical framework offers flexibility in runtime selection, allowing for various turbulence models, combustion models, and moment closure strategies to account for the size distribution of soot particles. The gas turbine model combustor contains significant flow field characteristics. Within the combustor, a variety of intricate physical phenomena occur, interacting with one another and influencing both combustor performance and emissions. Combustor geometry from Geigle K.P. et al. (2015), Proc. Combust. Inst., 35, pp. 3373–3380. The images and data used here are adapted from the work of: Tim Jeremy Patrick Karpowski, Federica Ferraro, Christian Hasse. The source of which can be found at [Link to the Source: https://doi.org/10.6084/m9.figshare.12451934.v2] . The images and data licensed under CC BY 4.0 [License Link: https://creativecommons.org/licenses/by/4.0/]."
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June 27th, 2023 Uploaded
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