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DC Field | Value | Language |
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dc.contributor.author | Devi, K | - |
dc.contributor.author | Khatua, K K | - |
dc.contributor.author | Khutia, J R | - |
dc.date.accessioned | 2016-08-05T12:05:30Z | - |
dc.date.available | 2016-08-05T12:05:30Z | - |
dc.date.issued | 2016-07 | - |
dc.identifier.citation | River Flow 2016 Eighth International Conference on Fluvial Hydraulic, St. Louis, USA , 10–14 July 2016 | en_US |
dc.identifier.uri | http://hdl.handle.net/2080/2526 | - |
dc.description | Copyright belongs to the Proceeding of Publisher | en_US |
dc.description.abstract | It is technically exigent task to solve depth integrated Navier Stokes equation for finding out the depth averaged velocity and boundary shear distribution in a compound channel with symmetric and asymmetric flood plains.Due to complexity of the flow structure at junction of main channel and flood plain, there is a certain level of uncertainty to predict the accurate depth averaged velocity and boundary shear distribution exceptionally at the shear layer region, appearing near the junctions due to enormous turbulence. Experiments have been conducted to study the dependence of shear layer width with independent geometric and hydraulic parameters. As the shear layer width is directly depend upon the mean velocity ratios of the sub sections therefore an effort has been made to develop reliable expressions to predict the mean velocity ratios for both symmetric and asymmetric compound channels. Through multi linear regression analysis, generalised expressions for enumerating the quantification of shear layer width of compound channels of homogenous roughness are presented. The depth integrated Navier Stokes equation can be refined for predicting the variables in the shear layer region. | en_US |
dc.subject | Compound channel | en_US |
dc.subject | Symmetric | en_US |
dc.subject | Asymmetric | en_US |
dc.title | Prediction of Mixing Layer in Symmetric and Asymmetric Compound Channels | en_US |
dc.type | Article | en_US |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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2016_ICSH_RiverFlow_KDevi_Prediction.pdf | 777.26 kB | Adobe PDF | View/Open |
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