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  Predictions of Flow and Heat Transfer in Low Emission Combustors
 
 
Titel: Predictions of Flow and Heat Transfer in Low Emission Combustors
Auteur: Lu, Yiping
Esposito, Eric
Ekkad, Srinath V.
Verschenen in: Heat transfer engineering
Paginering: Jaargang 29 (2008) nr. 4 pagina's 375-384
Jaar: 2008-04
Inhoud: Flow and heat transfer predictions in modern low emission combustors are critical to maintaining the liner wall at reasonable temperatures. This study is the first to focus on a critical issue for combustor design. The objective of this paper is to understand the effect of different swirl angle for a dry low emission (DLE) combustor on flow and heat transfer distributions. This paper provides the effect of fuel nozzle swirl angle on velocity distributions, temperature, and surface heat transfer coefficients. A simple test model is investigated with flow through fuel nozzles without reactive flow. The fuel nozzle angle is varied to obtain different swirl conditions inside the combustor. The effect of flow Reynolds number and swirl number are investigated using FLUENT. Different RANS-based turbulence models are tested to determine the ability of these models to predict the swirling flow. For comparison, different turbulence models such as standard k - ε, realizable k - ε, and shear stress transport (SST) k-ω turbulence model were studied for non-reactive flow conditions. The results show that, for a high degree swirl flow, the SST k-ω model can provide more reasonable predictions for recirculation and high velocity gradients. With increasing swirl angle, the average surface heat transfer coefficient increases while the average static temperature will decrease. Preliminary analysis shows that the k-ω model is the best model for predicting swirling flows. Also critical is the effect of the swirling flows on the liner wall heat transfer. The strength and magnitude of the swirl determines the local heat transfer maxima location. This location needs to be cooled more effectively by various cooling schemes.
Uitgever: Taylor & Francis
Bronbestand: Elektronische Wetenschappelijke Tijdschriften
 
 

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