Article
A Multilayer Shallow Water Approach for Polydisperse Sedimentation with Sediment Compressibility and Mixture Viscosity
Author/s | Bürger, Raimund
Fernández Nieto, Enrique Domingo ![]() ![]() ![]() ![]() ![]() ![]() ![]() Osores, Víctor |
Department | Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII) |
Date | 2020 |
Published in |
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Abstract | A three-dimensional multilayer shallow water approach to study polydisperse
sedimentation and sediment transport in a viscous fluid is presented. The fluid is assumed
be loaded with finely dispersed solid particles that ... A three-dimensional multilayer shallow water approach to study polydisperse sedimentation and sediment transport in a viscous fluid is presented. The fluid is assumed be loaded with finely dispersed solid particles that belong to a finite number of species that differ in density and size. The model formulation allows one to recover the global mass and linear momentum balance laws of the mixture. The model incorporates compressibility of the sediment and viscosity of the mixture through a viscous stress tensor. As a consequence of a dimensional analysis applied to the global mass conservation and linear momentum balance equations, the horizontal components of the compression term and the horizontal terms of the viscous stress tensor may be neglected. This results in a final model that is vertically consistent with the classical one-dimensional vertical model. Numerical simulations illustrate the coupled solids volume fraction and flow fields in various scenarios and the effect of the compressibility and viscosity terms. Various bottom topographies give rise to recirculation of the fluid and high solids volume fractions on the bottom. |
Funding agencies | Ministerio de Economía y Competitividad (MINECO). España |
Project ID. | MTM 2015-70490-C2-2-R
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Citation | Bürger, R., Fernández Nieto, E.D. y Osores, V. (2020). A Multilayer Shallow Water Approach for Polydisperse Sedimentation with Sediment Compressibility and Mixture Viscosity. Journal of Scientific Computing, 85 (2) |
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