Yang Xianglong, Yang Lei
College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China.
Key Laboratory for Resilient Infrastructures of Coastal Cities (MOE), Shenzhen University, Shenzhen 518060, China.
Entropy (Basel). 2022 Feb 19;24(2):295. doi: 10.3390/e24020295.
As computational fluid dynamics (CFD) advances, entropy generation minimization based on CFD becomes attractive for optimizing complex heat-transfer systems. This optimization depends on the accuracy of CFD results, such that accurate turbulence models, such as elliptic relaxation or elliptic blending turbulence models, become important. The performance of a previously developed elliptic blending turbulence model (the SST k-ω-φ-α model) to predict the rate of entropy generation in the fully developed turbulent circular tube flow with constant heat flux was studied to provide some guidelines for using this class of turbulence model to calculate entropy generation in complex systems. The flow and temperature fields were simulated by using a CFD package, and then the rate of entropy generation was calculated in post-processing. The analytical correlations and results of two popular turbulence models (the realizable - and the shear stress transport (SST) - models) were used as references to demonstrate the accuracy of the SST k-ω-φ-α model. The findings indicate that the turbulent Prandtl number (Pr) influences the entropy generation rate due to heat-transfer irreversibility. Pr = 0.85 produces the best results for the SST k-ω-φ-α model. For the realizable - and SST - models, Pr = 0.85 and Pr = 0.92 produce the best results, respectively. For the realizable - and the SST - models, the two methods used to predict the rate of entropy generation due to friction irreversibility produce the same results. However, for the SST k-ω-φ-α model, the rates of entropy generation due to friction irreversibility predicted by the two methods are different. The difference at a Reynolds number of 100,000 is about 14%. The method that incorporates the effective turbulent viscosity should be used to predict the rate of entropy generation due to friction irreversibility for the SST k-ω-φ-α model. Furthermore, when the temperature in the flow field changes dramatically, the temperature-dependent fluid properties must be considered.
随着计算流体动力学（CFD）的发展，基于CFD的熵产生最小化对于优化复杂的传热系统变得具有吸引力。这种优化取决于CFD结果的准确性，因此精确的湍流模型，如椭圆松弛或椭圆混合湍流模型，变得至关重要。研究了先前开发的椭圆混合湍流模型（SST k-ω-φ-α模型）在预测具有恒定热通量的充分发展湍流圆管流中熵产生率方面的性能，以便为使用这类湍流模型计算复杂系统中的熵产生提供一些指导。使用CFD软件包模拟了流动和温度场，然后在后期处理中计算了熵产生率。使用两种流行湍流模型（可实现模型和剪切应力传输（SST）模型）的解析关联式和结果作为参考，以证明SST k-ω-φ-α模型的准确性。研究结果表明，湍流普朗特数（Pr）由于传热不可逆性而影响熵产生率。对于SST k-ω-φ-α模型，Pr = 0.85时产生最佳结果。对于可实现模型和SST模型，Pr = 0.85和Pr = 0.92时分别产生最佳结果。对于可实现模型和SST模型，用于预测由于摩擦不可逆性导致的熵产生率的两种方法产生相同的结果。然而，对于SST k-ω-φ-α模型，两种方法预测的由于摩擦不可逆性导致的熵产生率不同。在雷诺数为100,000时，差异约为14%。对于SST k-ω-φ-α模型，应使用包含有效湍流粘度的方法来预测由于摩擦不可逆性导致的熵产生率。此外，当流场中的温度变化很大时，必须考虑与温度相关的流体属性。
