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Developing an approximation of a natural, rough gravel riverbed both physically and numerically

Stubbs, Alex, Stoesser, Thorsten and Bockelmann-Evans, Bettina 2018. Developing an approximation of a natural, rough gravel riverbed both physically and numerically. Geosciences 8 (12) , p. 449. 10.3390/geosciences8120449

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Abstract

Near-bed and pore space turbulent flows are beginning to be understood using new technologies and advances in direct numerical simulation (DNS) and large-eddy simulation (LES) techniques. However, the riverbed geometry that is used in many computational studies remains overly simplistic. Thus, this study presents the development of an artificial representation of a gravel riverbed matrix, and the assessment of how well it approximates a natural riverbed. A physical model of a gravel riverbed matrix that was 120 mm deep, 300 mm wide, and 2.048 m long was manufactured from cast acrylic. Additionally, a numerical approximation of the physical model was created and used for analysis. The pore matrix of the artificial riverbed was found to be comparable to that of a natural gravel riverbed in terms of its porosity and void ratio. The diameters of the artificial riverbed’s surface particles were found to vary less, with fewer irregularities, than those found for natural gravel riverbeds; yet, they were normally distributed similarly to natural riverbeds. A power spectral density function showed that the artificial riverbed exhibited a degree of roughness that was much lower than that found in nature. Thus, the hydraulic resistance and friction factor will both be lower than desired. These findings suggest that the novel methods that have been developed in this study can offer both the physical and numerical approximation of a gravel bed surface that is comparable to a natural gravel riverbed with low surface roughness, reduced particle size variance, and typical particle distribution and porosity

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: MDPI
ISSN: 2076-3263
Date of First Compliant Deposit: 29 November 2018
Date of Acceptance: 28 November 2018
Last Modified: 30 May 2019 22:05
URI: http://orca.cf.ac.uk/id/eprint/117194

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