Computing flow and sediment transport over bedforms

Nelson, Jonathan M.; Burman, Aaron R.; Shimizu, Yasuyuki; McLean, S. R.; Shreve, Ronald L.; Schmeeckle, M. W.

doi:10.1201/9781439833896.ch93

Cited by 5 publications

(4 citation statements)

References 1 publication

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“…Many approaches have been and are used to model dune dimensions, varying from equilibrium dune height predictors (e.g., Yalin 1964;Allen 1978;Van Rijn 1984) to different forms of stability analysis (e.g., Kennedy 1963;Engelund 1970;Fredsøe 1974;Yamaguchi and Izumi 2002). Recently, models have been developed that calculate the turbulent flow field over bedforms, in some cases in combination with morphological computations (e.g., Nelson et al 2005;Tjerry and Fredsøe 2005;Shimizu et al 2009;Paarlberg et al 2009;Nabi et al 2012Nabi et al , 2013a. These models are valuable to study detailed hydrodynamic processes, but can be computationally intensive.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Spatial Lag in Bed-Load Transport Processes and Its Effect on Dune Morphology

et al. 2017

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In the present study, two bed-load transport models are introduced in an existing idealized dune model. These allow for the modeling of the spatial lag between the sediment transport rate and bed shear stress along dune surfaces. This lag is an important factor in determining transitions between bedform regimes. Results of the original dune model (using an equilibrium transport formula) are compared with (1) a new model version that directly models spatial lag with a relaxation equation and ( 2) a new model version including pick-up and deposition processes. Both bed-load models use mean particle step length as an important parameter, which is varied to assess which value is appropriate for the dune regime. Laboratory experiments are simulated with the model. This shows that the results are best with the pick-up and deposition model version, combined with a step length of 25 times the particle diameter. It is furthermore shown that in principle the model is also able to wash out fully grown dunes, by increasing the step length parameter.

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Section: Introductionmentioning

confidence: 99%

Modeling of Spatial Lag in Bed-Load Transport Processes and Its Effect on Dune Morphology

et al. 2017

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“…The flow properties in the experiments were measured in single parts of the dunes. The results of the experiments were used to validate numerous numerical researches [22,23,36,47]. One of the experimental cases [6] was selected to evaluate the numerical calculation in this study.…”

Section: Model Setupmentioning

confidence: 99%

“…The physical experimental data of dune profiles and conditions were obtained from the previous research [6]; these data have been widely used and proven to be accurate in previous studies [2,23,32,35,36,47,48]. We employed the OpenFOAM (The OpenFOAM Foundation Ltd. London, United Kingdom) toolbox, an open-source CFD platform based on a cell-centered finite volume method.…”

Section: Introductionmentioning

confidence: 99%

Optimal Strategy to Tackle a 2D Numerical Analysis of Non-Uniform Flow over Artificial Dune Regions: A Comparison with Bibliography Experimental Results

Ahn

Lee

Park

2020

Water

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Flow simulation over a dune requires the proper input of roughness coefficients. This study analyzed a numerical simulation of open-channel turbulent flow over two-dimensional fixed dunes to reveal the effect of roughness on the dune bottom, and to determine the optimized combination of the turbulence scheme and the roughness height formula. The most appropriate roughness values and turbulence models were applied using Reynolds-averaged Navier–Stokes models. Seven methods were chosen to estimate the bed roughness properties at the inlet boundary section. The results of all cases calculated with the OpenFOAM toolbox were compared with laboratory experimental data for model validation. The performances of all bed roughness variations were evaluated according to the stream-wise and depth-wise directions with nondimensional values. Consequently, it was revealed that the combination of bottom roughness length scale at the inlet boundary and the k-ω shear-stress transport (SST) model was the most suitable for the flow separation zone and turbulent properties near the channel bottom.

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“…The result is that researchers turn to numerical models and physical experiments to gain insight into bedrock river erosion. Computational fluid dynamics (CFD) has been successfully applied to geomorphic problems in modeling the flow structures and subsequent sediment transport downstream of dunes (Schmeeckle, 2015; Schmeeckle et al., 1999). It is therefore a useful tool for exploration of variations in block geometry and its influence on the susceptibility of a block to plucking.…”

Section: Introductionmentioning

confidence: 99%

Toward Entrainment Thresholds in Fluvial Plucking

2021

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The erosion of river channels into rock controls landscape evolution. By setting the lower erosional boundaries for hillslopes, such bedrock channels control the relief of mountainous drainage basins and communicate climatic and tectonic signals across a landscape (Howard et al., 1994;Whipple et al., 2000;Whipple & Tucker, 1999). A bedrock channel must at least for some fraction of time be locally free of alluvial cover, although between flood events the bed is often alluviated (Howard et al., 1994). Once it is exposed, lowering of the bedrock channel occurs through two main erosional mechanisms: abrasion and plucking.Abrasion, or the removal of bedrock by sediment grain impacts with the bed, has been studied extensively through models, fieldwork, and experiments (e.g.,

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Computing flow and sediment transport over bedforms

Cited by 5 publications

References 1 publication

Modeling of Spatial Lag in Bed-Load Transport Processes and Its Effect on Dune Morphology

Modeling of Spatial Lag in Bed-Load Transport Processes and Its Effect on Dune Morphology

Optimal Strategy to Tackle a 2D Numerical Analysis of Non-Uniform Flow over Artificial Dune Regions: A Comparison with Bibliography Experimental Results

Toward Entrainment Thresholds in Fluvial Plucking

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