Numerical modeling of flow processes over gravelly surfaces using structured grids and a numerical porosity treatment
Numerical modeling of flow processes over gravelly surfaces using structured grids and a numerical porosity treatment
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使用结构化网格和数值孔隙率处理对砾石表面的流动过程进行数值模拟
DOI：
10.1029/2002wr001934
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发表时间：
2004
影响因子：
5.4
通讯作者：
D. Ingham
中科院分区：
文献类型：
--
作者：
S. N. Lane;R. Hardy;L. Elliott;D. Ingham
本文介绍了一种在高分辨率三维计算流体动力学模型中表示砾石床河复杂表面地形的方法的开发和验证。这是基于规则的结构化网格以及对质量守恒方程的孔隙率修改的应用，其中根据被阻塞的细胞体积的百分比，完全阻塞的细胞被分配为零的孔隙率，完全未阻塞的细胞被分配为1的孔隙率，部分阻塞的细胞被分配0到1之间的孔隙率。该模型保留了平衡壁函数和RNG型双方程湍流模型。该模型与基于水槽的水加工砾石床表面的 0.002 m 分辨率数字高程模型相结合，该模型使用双媒体数字摄影测量获得，表面高程精确至 ±0.001 m。通过与使用三分量声学多普勒测速仪 (ADV) 测量的速度数据进行比较来验证该模型。模型验证表明，与之前的研究相比，一致性水平显着提高，尤其是与床层剪切相关的一致性，尽管模型预测的分辨率明显高于 ADV 测量结果，使得在存在强剪切的情况下进行模型评估尤其困难。进行了一系列模拟来评估模型对河床地形和粗糙度表示的敏感性。这些证明了在没有高分辨率地形表示的情况下预测砾石床河中 3D 流场的固有局限性。他们还表明，下游通量的模型预测对地形平滑比对粗糙度参数化的变化更敏感，反映了颗粒和床形态尺度上质量守恒（即堵塞）和动量守恒效应的重要性。模型预测允许以高分辨率可视化表单流交互的结构。特别是，最突出的床颗粒对湍流动能最大值施加了关键的控制，该最大值通常在床上方流动深度的约 20% 处观察到。
This article describes the development and validation of a method for representing the complex surface topography of gravel bed rivers in high‐resolution three‐dimensional computational fluid dynamic models. This is based on a regular structured grid and the application of a porosity modification to the mass conservation equation in which fully blocked cells are assigned a porosity of zero, fully unblocked cells are assigned a porosity of one, and partly blocked cells are assigned a porosity of between 0 and 1, according to the percentage of the cell volume that is blocked. The model retains an equilibrium wall function and an RNG‐type two‐equation turbulence model. The model is combined with a 0.002 m resolution digital elevation model of a flume‐based, water‐worked, gravel bed surface, acquired using two‐media digital photogrammetry and with surface elevations that are precise to ±0.001 m. The model is validated by comparison with velocity data measured using a three‐component acoustic Doppler velocimeter (ADV). Model validation demonstrates a significantly improved level of agreement than in previous studies, notably in relation to shear at the bed, although the resolution of model predictions was significantly higher than the ADV measurements, making model assessment in the presence of strong shear especially difficult. A series of simulations to assess model sensitivity to bed topographic and roughness representation were undertaken. These demonstrated inherent limitations in the prediction of 3‐D flow fields in gravel bed rivers without high‐resolution topographic representation. They also showed that model predictions of downstream flux were more sensitive to topographic smoothing that to changes in the roughness parameterization, reflecting the importance of both mass conservation (i.e., blockage) and momentum conservation effects at the grain and bed form scale. Model predictions allowed visualization of the structure of form‐flow interactions at high resolution. In particular, the most protruding bed particles exerted a critical control on the turbulent kinetic energy maxima typically observed at about 20% of the flow depth above the bed.