Surface correlations of hydrodynamic drag for transitionally rough engineering surfaces
Surface correlations of hydrodynamic drag for transitionally rough engineering surfaces
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DOI：
10.1080/14685248.2016.1258119
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发表时间：
2017-01-01
影响因子：
1.9
通讯作者：
Sandham, Neil
中科院分区：
文献类型：
--
作者：
Thakkar, Manan;Busse, Angela;Sandham, Neil
粗糙表面通常由单个等效沙粒粗糙度高度尺度来表征，该高度尺度通常需要通过实验室实验来确定。最近，这种方法得到了直接数值模拟方法的补充，可以扫描代表性表面并在雷诺数范围内计算粗糙度效应。这一发展提出了未来几年的前景，即为不同类型的粗糙表面提供足够的数据，以便能够将表面特征与粗糙度效应联系起来，例如量化壁对数定律向下位移的粗糙度函数。在本贡献中，我们使用 17 个不规则表面在相同摩擦雷诺数下的模拟数据，这些表面处于过渡粗糙状态。所有表面都缩放至相同的物理粗糙度高度。平均流向速度剖面显示出广泛的粗糙度函数值，而速度缺陷剖面则显示出良好的塌陷。湍流动能的轮廓峰值也根据表面而变化。然后，我们考虑哪些表面特性很重要，以及如何将新特性纳入经验模型中，然后测试其准确性。针对粗糙度函数和轮廓峰值湍流动能，系统地开发了具有多个粗糙度参数的优化模型。在确定粗糙度函数时，除了已知的实度（或锋面积比）和偏斜度参数外，流向相关长度和均方根粗糙度高度也很重要。峰值湍流动能由偏度和均方根粗糙度高度以及平均前向表面角和展向有效斜率决定。结果表明，将粗糙壁流动特性（从流体动力学光滑到完全粗糙的整个范围）与表面参数相关联是可行的。
Rough surfaces are usually characterised by a single equivalent sand-grain roughness height scale that typically needs to be determined from laboratory experiments. Recently, this method has been complemented by a direct numerical simulation approach, whereby representative surfaces can be scanned and the roughness effects computed over a range of Reynolds number. This development raises the prospect over the coming years of having enough data for different types of rough surfaces to be able to relate surface characteristics to roughness effects, such as the roughness function that quantifies the downward displacement of the logarithmic law of the wall. In the present contribution, we use simulation data for 17 irregular surfaces at the same friction Reynolds number, for which they are in the transitionally rough regime. All surfaces are scaled to the same physical roughness height. Mean streamwise velocity profiles show a wide range of roughness function values, while the velocity defect profiles show a good collapse. Profile peaks of the turbulent kinetic energy also vary depending on the surface. We then consider which surface properties are important and how new properties can be incorporated into an empirical model, the accuracy of which can then be tested. Optimised models with several roughness parameters are systematically developed for the roughness function and profile peak turbulent kinetic energy. In determining the roughness function, besides the known parameters of solidity (or frontal area ratio) and skewness, it is shown that the streamwise correlation length and the root-mean-square roughness height are also significant. The peak turbulent kinetic energy is determined by the skewness and root-mean-square roughness height, along with the mean forward-facing surface angle and spanwise effective slope. The results suggest feasibility of relating rough-wall flow properties (throughout the range from hydrodynamically smooth to fully rough) to surface parameters.