Published September 21, 2020 | Version v1.0
Dataset Open

The Plunging of Hyperpycnal Plumes on Tilted Bed by Three-Dimensional Large-Eddy Simulations

Authors/Creators

  • 1. School of Technology, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
  • 2. Department of Mechanical Engineering, University of California Santa Barbara, Santa Barbara, USA
  • 3. Department of Aeronautics, Imperial College London, London, SW7 2AZ, UK

Description

Abstract: Theoretical and experimental interest in the transport and deposition of sediments from rivers to oceans has increased rapidly over the last two decades. The marine ecosystem is strongly affected by mixing at river mouths, with for instance anthropogenic actions like pollutant spreading. Particle-laden flows entering a lighter ambient fluid (hyperpycnal flows) can plunge at a sufficient depth, and their deposits might preserve a remarkable record across a variety of climatic and tectonic settings. Numerical simulations play an essential role in this context since they provide information on all flow variables for any point of time and space. This work offers valuable Spatio-temporal information generated by turbulence-resolving 3D simulations of poly-disperse hyperpycnal plumes over a tilted bed. The simulations are performed with the high-order flow solver Xcompact3d, which solves the incompressible Navier-Stokes equations on a Cartesian mesh using high-order finite-difference schemes. Five cases are presented, with different values for flow discharge and sediment concentration at the inlet. A detailed comparison with experimental data and analytical models is already available in the literature. The main objective of this work is to present a new data-set that shows the entire three-dimensional Spatio-temporal evolution of the plunge phenomenon and all the relevant quantities of interest.

Description: Data from the five simulations are included (cases 2, 4, 5, 6, and 7). The output files from Xcompact3d were converted to NetCDF, including coordinates and metadata, aiming to be more friendly than raw binaries.

More details, including examples about how to read and plot the dataset using Python and xarray, are available at GitHub.

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Additional details

Related works

Cites
Journal article: 10.1016/j.softx.2020.100550 (DOI)
Continues
Journal article: 10.1029/2018JC014027 (DOI)
Is source of
Video/Audio: https://youtu.be/rUDY5UI0bG4 (URL)
Is supplemented by
Other: https://github.com/fschuch/the-plunging-flow-by-3D-LES (URL)
Presentation: https://youtu.be/n08U9l1Pgis (URL)

References

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