多孔晶格上湍流强制对流的摩擦与传热建模
Modelling friction and heat transfer in turbulent forced convection over porous lattices
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中文总结 AI 辅助
本研究通过直接数值模拟，提出用Forchheimer系数替代粗糙度高度，将粗糙壁理论扩展至多孔表面，推导出摩擦系数与斯坦顿数公式，验证多孔基底可有效增强湍流传热。
中文摘要 AI 辅助
我们进行了直接数值模拟（DNS），以研究立方晶格多孔基底如何影响湍流通道流动中的动量与热量传递。模拟覆盖了从260到1500的摩擦雷诺数、0.5、1和2的普朗特数，以及50%、71%和87%的基底孔隙率。我们表明，针对粗糙壁湍流发展的理论可以扩展到多孔表面，只需将粗糙度高度替换为流向Forchheimer系数的倒数。平均速度和温度剖面的偏移遵循现有的完全粗糙动量与热理论，从而能够使用粗糙壁模型进行预测。将这些模型与合成的温度和速度剖面相结合，我们推导出摩擦系数和斯坦顿数的解析公式，这些公式与我们的DNS数据吻合度在5%以内。性能增强因子（衡量在恒定泵功率下相对于压降代价的传热增强）与粗糙表面所获得的相当。这表明多孔基底为增强湍流流动中的传热提供了一种替代方法。
英文摘要
We perform direct numerical simulations (DNS) to investigate how cubic-lattice porous substrates influence momentum and heat transfer in turbulent channel flows. The simulations span friction Reynolds numbers from 260 to 1500, Prandtl numbers of 0.5, 1, and 2, and substrate porosities of 50%, 71%, and 87%. We show that theories developed for rough- wall turbulence can be extended to porous surfaces by replacing the roughness height with the inverse of the streamwise Forchheimer coefficient. The shifts in the mean velocity and temperature profiles follow existing fully rough momentum and thermal theories, enabling their prediction with rough-wall models. Combining these models with synthetic temperature and velocity profiles, we derive analytical formulas for the friction coefficient and Stanton number that agree with our DNS data to within 5%. The performance enhancement factor, which measures heat-transfer augmentation relative to the pressure-drop penalty at constant pumping power, is comparable to that obtained for rough surfaces. This suggests that porous substrates provide an alternative method for enhancing heat transfer in turbulent flows.
