A Comprehensive Evaluation of Turbulence Models for Predicting Heat Transfer in Turbulent Channel Flow across Various Prandtl Number Regimes

Fluids Pub Date : 2024-02-03 DOI:10.3390/fluids9020042
Liyuan Liu, U. Ahmed, N. Chakraborty
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Abstract

Turbulent heat transfer in channel flows is an important area of research due to its simple geometry and diverse industrial applications. Reynolds-Averaged Navier–Stokes (RANS) models are the most-affordable simulation methodology and are often the only viable choice for investigating industrial flows. However, accurate modelling of wall-bounded flows is challenging in RANS, and the assessment of the performance of RANS models for heated turbulent channel flow has not been sufficiently investigated for a wide range of Reynolds and Prandtl numbers. In this study, five RANS models are assessed for their ability to predict heat transfer in channel flows across a wide range of Reynolds and Prandtl numbers (Pr) by comparing the RANS results with respect to the corresponding Direct Numerical Simulation data. The models include three Eddy Viscosity Models (EVMs): standard k−ϵ, low Reynolds number k−ϵLS, and k−ωSST, as well as two Reynolds Stress Models (RSMs): Launder–Reece–Rodi and Speziale–Sarkar–Gatski models. The study analyses the Reynolds number effects on turbulent heat transfer in a channel flow at a Pr of 0.71 for friction Reynolds number values of 180,395,640, and 1020. The results show that all models accurately predict velocity across all Reynolds numbers, but the accuracy of mean temperature prediction drops with increasing Reynolds number for all models, except for the k−ωSST model. The study also analyses the Pr effects on turbulent heat transfer in a channel flow with Pr values between 0.025 and 10.0. An error analysis is performed on the results obtained from different turbulence models, and it is shown that the k−ωSST model has the smallest error for the predictions of the mean temperature and Nusselt number for high-Prandtl-number flows, while the low Reynolds number k−ϵLS model shows the smallest errors for low-Prandtl-number flows at different Reynolds numbers. An analytical solution is utilised to identify Pr effects on forced convection in a channel flow into three different regimes: analytical region, transitional region, and turbulent diffusion-dominated region. These regimes are helpful to discuss the validity of the models in relation to the Pr. The findings of this paper provide insights into the performance of different RANS models for heat transfer predictions in a channel flow.
全面评估用于预测不同普朗特数区间湍流通道流传热的湍流模型
通道流中的湍流传热因其简单的几何形状和多样化的工业应用而成为一个重要的研究领域。雷诺平均纳维-斯托克斯(RANS)模型是最经济实惠的模拟方法,通常也是研究工业流的唯一可行选择。然而,在 RANS 模型中,壁面约束流的精确建模具有挑战性,而且对于各种雷诺数和普朗特尔数的受热湍流通道流,RANS 模型的性能评估研究还不够充分。在本研究中,通过将 RANS 结果与相应的直接数值模拟数据进行比较,评估了五个 RANS 模型预测大范围雷诺数和普朗特数 (Pr) 下通道流传热的能力。这些模型包括三个涡粘度模型(EVM):标准 k-ϵ、低雷诺数 k-ϵLS 和 k-ωSST,以及两个雷诺应力模型(RSM):Launder-Reece-Rodi 和 Speziale-Sarkar-Gatski 模型。研究分析了在摩擦雷诺数为 180、395、640 和 1020 时,Pr 值为 0.71 的通道流中雷诺数对湍流传热的影响。结果表明,所有模型在所有雷诺数下都能准确预测速度,但除 k-ωSST 模型外,所有模型的平均温度预测精度都随着雷诺数的增加而下降。研究还分析了 Pr 值在 0.025 到 10.0 之间的通道流中 Pr 对湍流传热的影响。对不同湍流模型得出的结果进行了误差分析,结果表明,k-ωSST 模型对高珀然德数流动的平均温度和努塞尔特数的预测误差最小,而低雷诺数 k-ϵLS 模型对不同雷诺数的低珀然德数流动的预测误差最小。通过分析求解,确定了 Pr 对通道流中强制对流的影响,并将其划分为三个不同的区域:分析区域、过渡区域和湍流扩散主导区域。这些状态有助于讨论与 Pr 有关的模型的有效性。本文的研究结果有助于深入了解不同 RANS 模型在通道流传热预测中的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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