Arfaie, A., Burns, A.D., Dorrell, R.M. et al. (3 more authors) (2018) Optimisation of flow resistance and turbulent mixing over bed forms. Environmental Modelling & Software, 107. pp. 141-147. ISSN 1364-8152
Abstract
Previous work on the interplay between turbulent mixing and flow resistance for flows over periodic rib roughness elements is extended to consider the flow over idealized shapes representative of naturally occurring sedimentary bed forms. The primary motivation is to understand how bed form roughness affects the carrying capacity of sediment-bearing flows in environmental fluid dynamics applications, and in engineering applications involving the transport of particulate matter in pipelines. For all bed form shapes considered, it is found that flow resistance and turbulent mixing are strongly correlated, with maximum resistance coinciding with maximum mixing, as was previously found for the special case of rectangular roughness elements. Furthermore, it is found that the relation between flow resistance to eddy viscosity collapses to a single monotonically increasing linear function for all bed form shapes considered, indicating that the mixing characteristics of the flows are independent of the detailed morphology of individual roughness elements.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 Elsevier. This is an author produced version of a paper subsequently published in Environmental Modelling and Software. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Turbulent flow; Roughness; CFD; Bed forms |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 18 Oct 2019 08:56 |
Last Modified: | 18 Oct 2019 08:56 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.envsoft.2018.06.002 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:152306 |