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Research Article
Fan Yang
Wuhan University School of Water Resources and Hydropower Engineering
Corresponding Author
ORCiD: https://orcid.org/0000-0003-4306-4402
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This work is licensed under a CC BY 4.0 License. Read Full License
The settlement of non-spherical particles, such as propagules of plants and natural sediments, are commonly observed in riverine ecosystems. The settling process is influenced by both particle properties (size, density and shape) and fluid properties (density and viscosity). Therefore, the drag law of non-spherical particles is a function of both particle Reynolds number and particle shape. Herein, a total of 828 settling data are collected from the literatures, which cover a wide range of particle Reynolds number (0.008–10000). To characterize the influence of particle shapes, sphericity is adopted as the general shape factor, which varies from 0.421 to 1.0. By comparing the measured drag with the standard drag curve of spheres, we modify the spherical drag law with three shape-dependent functions to develop a new drag law for non-spherical particles. Combined with an iterative procedure, a new model is thus obtained to predict the settling velocity of non-spherical particles of various shapes and materials. Further applications in hydrochorous propagule dispersal and sediment transport are projected based on deeper understanding of the settling process.
Keywords
Drag coefficient, Settling velocity, Sphericity, Non-spherical particles, Particle Reynolds number, shape-dependent functions
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This preprint is under consideration at Environmental Science and Pollution Research. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
Fan Yang
Wuhan University School of Water Resources and Hydropower Engineering
Corresponding Author
ORCiD: https://orcid.org/0000-0003-4306-4402
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 16 Mar, 2021
No community comments so far
Reviews received
Received 16 Mar, 2021
Reviewers invited
Invitations sent on 14 Mar, 2021
Editor assigned
On 23 Feb, 2021
First submitted
On 22 Feb, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
The settlement of non-spherical particles, such as propagules of plants and natural sediments, are commonly observed in riverine ecosystems. The settling process is influenced by both particle properties (size, density and shape) and fluid properties (density and viscosity). Therefore, the drag law of non-spherical particles is a function of both particle Reynolds number and particle shape. Herein, a total of 828 settling data are collected from the literatures, which cover a wide range of particle Reynolds number (0.008–10000). To characterize the influence of particle shapes, sphericity is adopted as the general shape factor, which varies from 0.421 to 1.0. By comparing the measured drag with the standard drag curve of spheres, we modify the spherical drag law with three shape-dependent functions to develop a new drag law for non-spherical particles. Combined with an iterative procedure, a new model is thus obtained to predict the settling velocity of non-spherical particles of various shapes and materials. Further applications in hydrochorous propagule dispersal and sediment transport are projected based on deeper understanding of the settling process.
Figure 1
Figure 2
Figure 3
Figure 4
The full text of this article is available to read as a PDF.
This is a list of supplementary files associated with this preprint. Click to download.
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