Local estimation of the mixing model constant for transported PDF combustion models

This work presents a novel method for the local estimation of the mixing constant in transported, joint-composition, probability density function (TPDF) combustion models. In the literature, the micro-mixing model’s constant, denoted as Cϕ which represents the ratio between the integral and the mixi...

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Veröffentlicht in:Fuel (Guildford) 2024-02, Vol.357, p.130022, Article 130022
Hauptverfasser: Giuntini, Lorenzo, Savarese, Matteo, Galletti, Chiara, Parente, Alessandro
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Sprache:eng
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Zusammenfassung:This work presents a novel method for the local estimation of the mixing constant in transported, joint-composition, probability density function (TPDF) combustion models. In the literature, the micro-mixing model’s constant, denoted as Cϕ which represents the ratio between the integral and the mixing time-scale, is usually set to a fixed and uniform value. The selection of the appropriate value of the aforementioned constant is mostly done by trial-and-error procedures, which entails a considerable computational cost considering the complexity of TPDF models. In addition, the assumption of a uniform value for this constant may affect the performance of such models, as local effects are neglected. For these reasons, an approach for the local estimation of the mixing constant based on the transport of a passive scalar is developed in this work. The approach is tested by performing Reynolds-Averaged Navier–Stokes simulations on the Adelaide Jet-In-Hot-Coflow (AJHC) flames at different Reynolds numbers (i.e., 5,000 and 10,000) and oxygen concentrations in the coflow (i.e., 3 and 9% in mass basis). The model is validated against experimental data of temperature and species. The local approach can help to overcome the issues related to the tuning of Cϕ, which in many cases may result in time-consuming trial-and-error procedures. •An approach for the local estimation of the mixing constant, Cϕ, is proposed.•The approach is tested against detailed experimental data.•Optimal parameters for model’s calibration are determined.•Cϕ shows a non-uniform spatial distribution.•The need for a trial-and-error tuning of Cϕ is eliminated.•This approach allows generalizing the applicability of TPDF models.
ISSN:0016-2361
1873-7153
DOI:10.1016/j.fuel.2023.130022