Geometry prediction for wave-generated bedforms

Mogridge, G.R.; Davies, M.; Willis, D.H.

doi:10.1016/0378-3839(94)90039-6

Cited by 56 publications

(117 citation statements)

References 15 publications

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“…Orbital ripples, for which both wavelength and height depend directly on d o , and steepness is constant, occur for [Nielsen, 1981;Grant and Madsen, 1982;Mogridge et al, 1994;Styles and Glenn, 2002;Faraci and Foti, 2002;Grasmeijer and Kleinhans, 2004;Williams et al, 2005]. The predictions tend to differ most for suborbital ripples.…”

Section: Ripple Dimensionsmentioning

confidence: 95%

“…It is also important to the interpretation of bed forms found in the geologic record. Numerous field and laboratory studies have advanced the understanding of the relationship between wave forcing and ripple geometry, and, although significant uncertainty remains, numerous empirical predictive expressions for wave ripple wavelength and height have been proposed [e.g., Nielsen, 1981;Grant and Madsen, 1982;Wiberg and Harris, 1994;Mogridge et al, 1994;Xu and Wright, 1995;Styles and Glenn, 2002;Grasmeijer and Kleinhans, 2004;Williams et al, 2005]. Investigation of bed forms produced by noncolinear combinations of waves and currents has been much more limited, despite the frequent occurrence of such flows in coastal waters.…”

Section: Introductionmentioning

confidence: 99%

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Bed forms created by simulated waves and currents in a large flume

et al. 2007

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[1] The morphology and evolution of bed forms created by combinations of waves and currents were investigated using an oscillating plate in a 4-m-wide flume. Current speed ranged from 0 to 30 cm/s, maximum oscillatory velocity ranged from 20 to 48 cm/s, oscillation period was 8 s (except for one run with 12 s period), and the median grain size was 0.27 mm. The angle between oscillations and current was 90°, 60°, or 45°. At the end of each run the sand bed was photographed and ripple dimensions were measured. Ripple wavelength was also determined from sonar images collected throughout the runs. Increasing the ratio of current to wave (i.e., oscillatory) velocity decreased ripple height and wavelength, in part because of the increased fluid excursion during the wave period. Increasing the ratio of current to waves, or decreasing the angle between current and waves, increased the three-dimensionality of bed forms. During the runs, ripple wavelength increased by a factor of about 2. The average number of wave periods for evolution of ripple wavelength to 90% of its final value was 184 for two-dimensional ripples starting from a flat bed. Bed form orientations at the end of each run were compared to four potential controlling factors: the directions of waves, current, maximum instantaneous bed shear stress, and maximum gross bed form normal transport (MGBNT). The directions of waves and of MGBNT were equally good predictors of bed form orientations, and were significantly better than the other two factors.

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Section: Ripple Dimensionsmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Bed forms created by simulated waves and currents in a large flume

et al. 2007

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“…The common method requires a prediction of ripple geometry and there is no lack of published empirical relationships from laboratory and field measurements relating ripple dimensions to flow and sediment characteristics (e.g., Miller and Komar 1980, Nielsen 1981, Grant and Madsen 1982, Kos'yan 1988, Wikramanayake and Madsen 1994, Wiberg and Harris 1994, Mogridge et al 1994, Faraci and Foti 2002, Williams et al 2004, O'Donoghue et al 2006. Each formula performs well against the data used in its formulation, as expected, but generally much less successfully under reasonably different conditions.…”

Section: Common Methodsmentioning

confidence: 81%

Predicting Movable Bed Roughness in Coastal Waters

Humbyrd

Madsen

2011

Int. Conf. Coastal. Eng.

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Accurately predicting movable bed roughness is essential to the analyses of transport processes, but when the bottom is rippled, as it commonly is in the coastal environment, characterizing the roughness is less straightforward than when the bottom is flat. The common method of predicting roughness, while effective, unnecessarily predicts ripple geometry and requires a model-dependent factor, which varies widely, relating ripple geometry and bottom roughness. We have therefore developed an alternative, more direct method of predicting bed roughness in the ripple regime: the wave energy dissipation factor is predicted from flow and sediment information and then any desired theoretical friction factor model is used to back-calculate the roughness. This paper describes the common and proposed methods of predicting roughness and presents results of preliminary testing of the methods with field data. Both methods adequately predict current velocities in wave-current field flows, with the proposed method yielding the smaller RMS-error of 3.1 cm/s. Remaining questions concerning the appropriate near-bottom orbital velocity required to describe field conditions must be resolved when additional field data becomes available.

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“…There are many formulas for predicting ripple parameters (Khelifa and Ouellet, 2000;Mogridge et al, 1994;Nielsen, 1992). Khelifa and Ouellet (2000)'s method was employed in this study, which has been verified by many experimental and field data and can be used for both wave-only and combined wave-current conditions.…”

Section: A) Ripple Predictionmentioning

confidence: 91%

Modelling and Analysis of Fine Sediment Transport in Wave-Current Bottom Boundary Layer

Zuo¹

2018

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Although all care is taken to ensure integrity and the quality of this publication and the information herein, no responsibility is assumed by the publishers, the author nor IHE Delft for any damage to the property or persons as a result of operation or use of this publication and/or the information contained herein. A pdf version of this work will be made available as Open Access via http://repository.tudelft.nl/ihe. This version is licensed under the Creative Commons To my family AbstractThe evolution and utilization of estuarine and coastal regions are greatly restricted by sediment problems. Inspired by the Caofeidian sea area in Bohai Bay, China, this study aims to better understand silty sediment transport under combined action of waves and currents, especially in the wave-current bottom boundary layer (BBL), and to improve our modelling approaches in predicting estuarine and coastal sediment transport.Field observations were carried out in northwestern Caofeidian sea area of Bohai Bay and field data were collected on several other silt-dominated coasts. Analysis shows that silt-dominated sediments are sensitive to flow dynamics: the suspended sediment concentrations (SSCs) increase rapidly under strong flow dynamics (i.e., waves or strong tidal currents which can stir up sediments), and high concentrations cause heavy sudden back siltation in navigation channels. In the following, details of silty sediment transport are studied, focusing on the BBL and high concentration layer (HCL).From laboratory experiments and theoretical analysis, an expression for sediment incipient motion is proposed for silt-sand sediment under combined wave and current conditions. The Shields number was revised by adding the cohesive force and additional static pressure, leading to an extended Shields curve.To study the HCL, a process based 1DV model was developed for flow-sediment dynamics near the bed in combined wave-current conditions. Based on the physical processes, special approaches for sediment movement were introduced, including approaches for different bed forms (rippled bed and 'flat-bed'), hindered settling, stratification effects, mobile bed effects, reference concentration and critical shear stress. The HCL was simulated and sensitivity analysis was carried out by the 1DV model on factors that impact the sediment concentration in the HCL. The results show that the HCL is affected by both flow dynamics and bed forms; the thickness of the HCL is about twice the height of the wave boundary layer; bed forms determine the shape of the concentration profile near the bottom, and flow dynamics determine the magnitude. For finer sediment, stratification effects and mobile bed effects impact the sediment concentration greatly.Finally, based on the 1DV model, the formulations of the mean sediment concentration profile of silty sediments were studied. By solving the time-averaged diffusion equation for SSC and considering the effects of bed forms, stratification and hindered settling, expressions for time-averaged SSC profile...

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Geometry prediction for wave-generated bedforms

Cited by 56 publications

References 15 publications

Bed forms created by simulated waves and currents in a large flume

Bed forms created by simulated waves and currents in a large flume

Predicting Movable Bed Roughness in Coastal Waters

Modelling and Analysis of Fine Sediment Transport in Wave-Current Bottom Boundary Layer

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