Turbulent Rectangular Compound Open Channel Flow Study Using Multi-Zonal Approach
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Publication date
2019-06Author
Pu, Jaan H.Keyword
Shiono-Knight methodSecondary flow
Turbulence
Natural flow
Lateral velocity distribution
Depth-averaged model
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© The Author(s) 2018 OpenAccess This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Peer-Reviewed
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Show full item recordAbstract
In this paper, an improved Shiono-Knight model (SKM) has been proposed to calculate the rectangular compound open channel flows by considering a Multi-Zonal (MZ) approach in modelling turbulence and secondary flows across lateral flow direction. This is an effort to represent natural flows with compound shape more closely. The proposed model improves the estimation of secondary flow by original SKM model to increase the accuracy of depthaveraged velocity profile solution formed within the transitional region between different sections (i.e. between main-channel and floodplain) of compound channel. This proposed MZ model works by sectioning intermediate zones between floodplain and main-channel for running computation in order to improve the modelling accuracy. The modelling results have been validated using the experimental data by national UK Flood Channel Facility (FCF). It has been proven to work reasonably well to model secondary flows within the investigated compound channel flow cases and hence produce better representation to their flow lateral velocity profile.Version
Published versionCitation
Pu JH (2019) Turbulent rectangular compound open channel flow study using multi-zonal approach. Environmental Fluid Mechanics. 19(3): 785-800.Link to Version of Record
https://doi.org/10.1007/s10652-018-09655-9Type
Articleae974a485f413a2113503eed53cd6c53
https://doi.org/10.1007/s10652-018-09655-9