Characterization of Double-Averaged Velocity Profile in an Open-Channel With Intermediate Relative Roughness

Document Type : Research Article

Authors

1 BSc student, Dept. of Civil and Environmental Engineering, Amirkabir University of Technology

2 Department of Civil engineering, Faculty of Engineering, Kharazmi university

3 Professor, Dept. of Civil and Environmental Engineering, Amirkabir University of Technology

4 PhD student, Dept. of Civil and Environmental Engineering, Amirkabir University of Technology

Abstract

Flow with intermediate relative roughness (the ratio of roughness height to water depth higher than 1/80 and lower than 1/40) is common in most of the mountainous streams. Despite this fact and numerous studies on flow with intermediate relative roughness, it is still unclear how the profile of the streamwise velocity varies along with water depth. In this study, the instantaneous velocity of flow in an open-channel with the rough bed has been measured using Particle Image Velocimetry (PIV). In order to analyze the profile of streamwise velocity, double averaging method (spatial averaging of time-averaged values in a thin slab parallel to the channel bed) was used. It was observed that near the rough bed, vectors of instantaneous velocity showed strong spatial variations that make extraction of unique behavior for velocity profile impossible without double averaging. Results also showed that values of double averaged velocity were not sensitive to priority in averaging (i.e. time and then spatial averaging or spatial and then time averaging); thus double averaging regardless of priority can be used. To investigate double averaged velocity profile, three approaches including a logarithmic profile with a variable parameter, linear profile and mixing layer profile were employed. Results showed that all three profiles could be fitted properly to our experimental data. However, logarithmic profile with variable Von-Karman constant and integration constant that was supported by strong scientific background was the most suitable profile and therefore can be recommended.

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Main Subjects


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