使用一维湍流（ODT）对湍流同心环形管道流动的数值模拟：第2部分：传热
Numerical Simulation of Turbulent Concentric Annular Pipe Flow using One-Dimensional Turbulence (ODT): Part 2: Heat Transfer
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中文总结 AI 辅助
研究湍流同心环形管道流动传热问题，用随机一维湍流（ODT）模型，在扩展参数范围模拟分析，校准模型研究半径比等因素影响，得到内壁边界层解析表达式，发现半径比对热统计量有显著影响，给出传热标度关联式。
中文摘要 AI 辅助
本文使用随机一维湍流（ODT）模型，在扩展参数范围内对具有被动传热的湍流同心环形管道流动进行了理论分析和数值模拟。ODT通过在降维和随机模型公式中沿代表性径向坐标完全解析粘性、传导和湍流平流传输过程来提供预测能力。使用固定模型校准，研究了半径比等因素对传热的影响，得到了内壁边界层的解析表达式等结果。结果表明传统线性表达式不足以表示径向间隙中的近壁低阶统计量，特别是在内圆柱壁处。此外，若不考虑曲率和有限雷诺数效应，对数定律区域也不适用。传热标度通过努塞尔特关联式进行参数化，并考虑了半径比效应。研究发现半径比对两个弯曲壁上的热统计量有显著影响，即使在高雷诺数和低普朗特数下也应予以考虑。
英文摘要
Turbulent concentric coaxial (annular) pipe flow with passive heat transfer is theoretically analyzed and numerically modeled in an extended parametric range using the stochastic one-dimensional turbulence (ODT) model. ODT provides predictive capabilities by fully resolving viscous, conductive, and turbulent advective transport processes along a representative radial coordinate within a dimensionally reduced and stochastic model formulation. Using a fixed model calibration for moderate and low Prandtl numbers, $Pr=0.71$ and $0.025$, effects of radius ratio, $η=R_{\rm i}/R_{\rm o}$ are investigated up to a highly turbulent flow regime. The analytical expression of the inner wall boundary layer yields a logarithmic law of the wall for the passive temperature. These results suggest that a conventional linear expression is inadequate for representing near-wall low-order statistics in the radial gap, in particular at the cylindrical inner wall. Additionally, the log-law region falls short if curvature and finite Reynolds number effects are not considered. Analytical boundary layer profiles fitting numerical predictions form the basis for heat transfer scaling relations. Heat transfer scalings are parameterized by a Nusselt correlation, which is extended to account for radius ratio effects. The findings demonstrate that the radius ratio has a significant impact on the thermal statistics over the two curved walls and should be considered even at high Reynolds numbers and low Prandtl numbers.
