利用粒子图像测速,本征正交分解和速度相关表征高粗糙度表面流动结构

2019/07/19   下载量: 0

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应用领域 能源/新能源
检测样本 其他
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采用LaVision公司由DaVis软件平台和ImagerPro型相机构成的粒子成像测速系统,对于水洞中的含有粗糙表面的流体的流场进行了测量并利用本征正交分解等数学工聚,对流动结构和水洞壁面表面粗糙度的相关性进行了实验研究。

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      High Reynolds number flow inside a channel of rectangular cross section is examined using Particle Image Velocimetry. One wall of the channel has been replaced with a surface of a roughness representative to that of real hydropower tunnels, i.e. a random terrain with roughness dimensions typically in the range of ≈10% - 20% of the channels hydraulic radius. The rest of the channel walls can be considered smooth. The rough surface was captured
from an existing blasted rock tunnel using high resolution laser scanning and scaled to 1:10. For quantification of the size of the largest flow structures, integral length scales are derived from the auto-correlation functions of the temporally averaged velocity. Additionally, Proper Orthogonal Decomposition (POD) and higher-order statistics are applied to the instantaneous snapshots of the velocity fluctuations. The results show a high spatial heterogeneity of the velocity and other flow characteristics in vicinity of the rough surface, putting outer similarity treatment into jeopardy. Roughness effects are not confined to the vicinity of the rough surface but can be seen in the outer flow throughout the channel, indicating a different behavior than postulated by Townsend’s similarity hypothesis. The effects on the flow structures vary depending on the shape and size of the roughness elements leading to a high
spatial dependence of the flow above the rough surface. Hence, any spatial averaging,
e.g. assuming a characteristic sand grain roughness factor, for determining local flow parameters becomes less applicable in this case.

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