BİR SİLİNDİRDEN ZORLANMIŞ TÜRBÜLANSLI TAŞINIM ISI GEÇİŞİNDE RANS VE LES MODELLERİNİN KIYASLAMALI BİR DEĞERLENDİRMESİ

Abstract

Geçici rejimde çapraz hava (Pr=0.7) akışına maruz izotermal yatay bir silindirin 2B ve 3B türbülanslı akış ve ısı geçiş karakteristikleri halihazırda yaygın olarak kullanılan türbülans modellerinin sayısal performansı bağlamında araştırılmıştır. 2B simülasyonlar için Standard k− (SKE), Re-Normalizasyon Grup k− (RNG), Realizable k− (RKE), Standard k- (SKW), Shear Stress Transport (SST) k- and Reynolds Stress Modeli (RSM) türbülans modelleri iki-tabaka duvar (veya Gelişmiş Duvar Uygulaması) modeli ile birlikte kullanılmıştır. 3B simülasyonlar için, RNG, SKW, SST, RSM ve dinamik gerilme modeli içeren ve içermeyen Smagorinsky-Lilly algoritması kullanan LES modeli kullanılmıştır. Bu çalışmada, türbülans modeleri için performans kriteri 2B ve 3B akış ile ısı geçişi sayısal tahminlerin doğruluğuna (CD, CL, CL,rms, St ve Nu sayıları) dayanmaktadır. FLUENT 6.3.26® CFD yazılımının kullanıldığı sayısal simülasyonlar, Reynolds sayılarının 1000, 3900 ve 10000 değerleri için gerçekleştirilmiştir. Kaldırma/sürünme katsayıları ve Strouhal sayıları gibi akış karakteristikleri hesaplanarak mevcut deneysel ve sayısal verilerle karşılaştırmalı olarak kıyaslanmıştır. 2B RANS modelleri, akışın doğası gereği üç boyutlu olması nedeniyle akış karakteristiklerinin tahmininde tutarlı değildir, ancak RANS modellerine nazaran RSM biraz daha iyi bir performans göstermiştir. 2B RANS modellerinde Re=1000 ve 3900 için ortalama Nusselt sayısı makul bir doğrulukla tahmin edilmiştir. RNG modeli tutarlı bir şekilde ortalama Nusselt sayısını yüksek tahmin etmekte iken, diğer 3B-RANS modelleri mevcut Nusselt korrelasyonlarının tahmin aralığında sayısal sonuçlar vermiştir. LES modelinin, bu çalışmada göz önüne alınan akış koşullarında, makul akış ve ısı geçişi karakteristikleri ile sonuçlanmasına rağmen LES'in performansı giriş koşullarına da bağlı olduğu gösterilmiştir.

Keywords

• LES simulasyonu
• türbülans modelleri
• iki-boyutlu
• üç-boyutlu
• RANS model

A COMPARATIVE ASSESSMENT OF TURBULENT FORCED CONVECTION HEAT TRANSFER FROM A SINGLE CYLINDER USING RANS AND LES MODELS

Abstract

Unsteady 2D and 3D turbulent flow and heat transfer characteristics of a single isothermal horizontal cylinder in crossflow of air (Pr=0.7) is investigated to assess the numerical performance of the common turbulence models currently in use. For 2D simulations, Standard k− (SKE), Re-Normalization Group k− (RNG), Realizable k− (RKE), Standard k- (SKW), Shear Stress Transport (SST) k- and Reynolds Stress Model (RSM) turbulence models are used in conjunction with the two-layer wall (or Enhanced Wall Treatment, EWT) model. For 3D simulations, RNG, SKW, SST, RSM and Large Eddy Simulation (LES) using Smagorinsky-Lilly with and without dynamic stress models are used. In this study, the performance criterion of the turbulence models is based on the accuracy of the computational predictions of 2D and 3D flow as well as heat transfer (CD, CL, CL,rms, St and Nu numbers) characteristics. Numerical simulations are carried out for Reynolds numbers of 1000, 3900 and 10000 using FLUENT 6.3.26® CFD software. The flow characteristics, such as the lift/drag coefficients and Strouhal numbers, are computed and tabulated comparatively with available experimental and numerical data. The 2D RANS models are not consistent in predicting the flow characteristics due to three-dimensionality nature of the fluid flow, but RSM performs slightly better than RANS models. The mean Nusselt number for Re=1000 and 3900 is predicted with reasonable accuracy with 2D-RANS models. While the RNG model consistently over estimates the mean Nusselt number, other 3D-RANS models yield values within the ranges predicted by the Nusselt number correlations. It is shown that although LES models yields reasonable flow and heat transfer characteristics for flow conditions considered here, the performance of LES is also dependent on the inlet condition.

Keywords

• Large eddy simulation
• turbulence models
• two-dimensional
• three-dimensional
• RANS models

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