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Optimisation of flow resistance and turbulent mixing over bed forms

Arfaie, A.; Burns, A.D.; Dorrell, R.M.; Ingham, D.B.; Eggenhuisen, J.T.; McCaffrey, W.D.

Authors

A. Arfaie

A.D. Burns

D.B. Ingham

J.T. Eggenhuisen

W.D. McCaffrey



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.

Citation

Arfaie, A., Burns, A., Dorrell, R., Ingham, D., Eggenhuisen, J., & McCaffrey, W. (2018). Optimisation of flow resistance and turbulent mixing over bed forms. Environmental modelling & software : with environment data news, 107, 141-147. https://doi.org/10.1016/j.envsoft.2018.06.002

Journal Article Type Article
Acceptance Date Jun 1, 2018
Online Publication Date Jun 15, 2018
Publication Date Sep 1, 2018
Deposit Date Jul 17, 2018
Publicly Available Date Jun 16, 2019
Journal Environmental Modelling and Software
Print ISSN 1364-8152
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 107
Pages 141-147
DOI https://doi.org/10.1016/j.envsoft.2018.06.002
Keywords Turbulent flow; Roughness; CFD; Bed forms
Public URL https://hull-repository.worktribe.com/output/888651
Publisher URL https://www.sciencedirect.com/science/article/pii/S1364815217312689?via%3Dihub
Copyright Statement ©2018, Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Additional Information This is the accepted manuscript of an article published in Environmental modelling & software, 2018. The version of record is available at the DOI link in this record.

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