Numerical modeling of flow in continuous bends from Daliushu to Shapotou in Yellow River
Numerical modeling of flow in continuous bends from Daliushu to Shapotou in Yellow River
复制标题
黄河大柳树至沙坡头连续弯道流量数值模拟
DOI：
10.3882/j.issn.1674-2370.2014.02.007
复制
发表时间：
2014-04
影响因子：
4
通讯作者：
李义天
中科院分区：
文献类型：
--
作者：
景何仿;李春光;郭亚昆;朱立军;李义天
黄河上游大柳树至沙坡头段由五个弯道组成，地形复杂。建立了二维RNG k-e模型对河段水流进行数值模拟。为了考虑弯道内的环流，对动量方程进行了改进，增加了源项。数值模拟结果与现场实测值的对比表明，改进的二维深度平均RNGk-e模型可以提高数值模拟的精度。建立了一种快速自适应算法，可以自动调整研究河段不同河段的曼宁糙率系数。这样不仅可以大大缩短试算时间，而且可以大大提高数值模拟的精度。4个典型算例的模拟水面坡度与实测水面坡度的对比表明，随着上游平均流速的增大，水面纵坡和横向坡度增大。此外，还比较了横流和主流线的位置，它们在所研究的大部分河段都是重合的。但在两弯交界处，在河宽突然减小或增大的位置，横流与主流线的位置出现偏差。
Abstract The upper reach of the Yellow River from Daliushu to Shapotou consists of five bends and has complex topography. A two-dimensional Re -Normalisation Group (RNG) k -e model was developed to simulate the flow in the reach. In order to take the circulation currents in the bends into account, the momentum equations were improved by adding an additional source term. Comparison of the numerical simulation with field measurements indicates that the improved two-dimensional depth-averaged RNG k -e model can improve the accuracy of the numerical simulation. A rapid adaptive algorithm was constructed, which can automatically adjust Manning's roughness coefficient in different parts of the study river reach. As a result, not only can the trial computation time be significantly shortened, but the accuracy of the numerical simulation can also be greatly improved. Comparison of the simulated and measured water surface slopes for four typical cases shows that the longitudinal and transverse slopes of the water surface increase with the average velocity upstream. In addition, comparison was made between the positions of the talweg and the main streamline, which coincide for most of the study river reach. However, deviations between the positions of the talweg and the main streamline were found at the junction of two bends, at the position where the river width suddenly decreases or increases.
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影响因子：
2.4
作者：
H. Lien;T. Hsieh;Jinn‐Chuang Yang;K. Yeh
通讯作者：
H. Lien;T. Hsieh;Jinn‐Chuang Yang;K. Yeh
影响因子：
2.4
作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
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影响因子：
1
作者：
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通讯作者：
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影响因子：
8.6
作者：
YAKHOT, V;ORSZAG, SA
通讯作者：
ORSZAG, SA