Statistical mechanics of sediment transport.
2011-12
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Statistical mechanics of sediment transport.
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2011-12
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Accurate prediction of the evolution of rivers and landforms under varying climatic and human-induced conditions requires quantification of the total sediment transported by a river. Based on a series of controlled laboratory experiments conducted at the St. Anthony Falls laboratory, University of Minnesota, we demonstrated that (a) bedload sediment transport at very small time scales can be an order of magnitude larger or smaller than the long-time average; (b) bed morphodynamics can be inferred from the spectral properties of turbulent velocity fluctuations above the bed; and (c) the nature of scaling and the degree of complexity and non-linearity in bed elevation fluctuations and sediment transport rates depend on the bed shear stress. These results are discussed in the context of understanding and exploring the dependence of sediment transport scaling on near-bed turbulence, bed topography, and particle-size distribution, and deriving stochastic transport models which give rise to the observed scaling. They also form the foundation of relating microscale dynamics of particle movement to the macroscale statistics of sediment transport via minimum complexity stochastic models.
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University of Minnesota. Ph.D. dissertation. December 2011. Major: Civil engineering. Advisor: Efi Foufoula-Georgiou. 1 computer file (PDF); xxi, 217 pages.
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Singh, Arvind. (2011). Statistical mechanics of sediment transport.. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/120031.
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