Wind tunnel and computational study of the stoss slope effect on the aeolian erosion of transverse sand dunes

Faria, Raquel; Ferreira, Almerindo D.; Sismeiro, João L.; Mendes, João C.F.; Sousa, António C.M.

doi:10.1016/j.aeolia.2011.07.004

Cited by 40 publications

(9 citation statements)

References 31 publications

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“…The role of topography in influencing wind, and thus the aeolian transport regime and resultant landforms, is complex. Studies have addressed the impact at scales from individual landform to synoptic scale, and with a diverse range of methods including numerical modeling (e.g., Tsoar et al, ; White & Tsoar, ), computational fluid dynamics (Faria et al, ; Huang et al, ), and wind tunnel experimentation (Bullard et al, ; Bullard & Nash, ; Iversen & Rasmussen, ; Iversen & Rasmussen, ; Rasmussen et al, ; White & Tsoar, ). Broadly, four categories of mechanisms can be drawn from the diverse literature which might be used to explain the observed pattern of dune deflection.…”

Section: Discussionmentioning

confidence: 99%

Long‐Wavelength Sinuosity of Linear Dunes on Earth and Titan and the Effect of Underlying Topography

et al. 2019

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On both Earth and Titan, some linear dunefields are characterized by curvilinear patterning atypical of the regularity and straightness of typical longitudinal dunefields. We use remotely sensed imagery and an automated dune crestline detection algorithm to analyze the controls on spatial patterning. Here it is shown that topography can influence the patterning, as dune alignments bend to deflect downslope under the influence of gravity. The effect is pronounced in a terrestrial dunefield (the Great Sandy desert, Australia) where substantial topography underlies, but is absent where the dunefield is underlain by subdued relief (southwestern Kalahari). This knowledge allows the inference of subtle topographic changes underlying dunefields from dunefield patterning, where other sources of elevation data may be absent. This methodology is explored using the Belet Sand Sea of Titan, where likely areas of topographic change at resolutions finer than those currently available from radar altimetry are inferred.

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Section: Discussionmentioning

confidence: 99%

Long‐Wavelength Sinuosity of Linear Dunes on Earth and Titan and the Effect of Underlying Topography

et al. 2019

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“…Profiles such as the vertical distribution of the wind velocity U ( y ), the turbulent kinetic energy k ( y ), and the energy dissipation ε ( y ) at the inlet are therefore simplified using equations , , and assuming a constant shear stress (Table ) with height (Richards & Hoxey, ):

U ((), y) = \frac{u_{*}}{k} italicln ((), \frac{y + y_{0}}{y_{0}}),

k ((), y) = \frac{u_{*}^{2}}{\sqrt{C_{μ}}},

ε ((), y) = \frac{u_{*}^{3}}{k ((), y + y_{0})},

where U ( y ) is the wind velocity at a height of y (m), κ = 0.40 is the von Karman constant (Richards & Norris, ), u * is the wind shear velocity assuming a constant shear velocity with height, y is the height above the surface, y 0 is the surface roughness length (0.1 mm), and C μ = 0.085 is a constant in renormalization group k − ε (Richards & Norris, ). In addition, to generate a pressure gradient in the flow direction, fully developed conditions, that is, zero gradient along the streamwise direction, were assumed, and the relative static pressure ( P = 0 ) was set equal to zero at the outlet (Araújo et al, ; De Lima et al, ; Faria et al, ; Tian et al, ).…”

Section: Methodsmentioning

confidence: 99%

“…where U(y) is the wind velocity at a height of y (m), κ = 0.40 is the von Karman constant (Richards & Norris, 2011), u * is the wind shear velocity assuming a constant shear velocity with height, y is the height above the surface, y 0 is the surface roughness length (0.1 mm), and C μ = 0.085 is a constant in renormalization group k − ε (Richards & Norris, 2011). In addition, to generate a pressure gradient in the flow direction, fully developed conditions, that is, zero gradient along the streamwise direction, were assumed, and the relative static pressure (P = 0) was set equal to zero at the outlet (Araújo et al, 2013;De Lima et al, 2015;Faria et al, 2011;Tian et al, 2013).…”

Section: Boundary Conditionsmentioning

confidence: 99%

Effects of Wind Velocity and Nebkha Geometry on Shadow Dune Formation

et al. 2019

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Flow dynamics and sand deposition processes over nebkhas were investigated using computational fluid dynamics simulations, wind tunnel experiments, and field measurements. The computational fluid dynamics simulations showed that nebkha width affects both the elongation and broadening of the wind shadows. The length of the wind shadows decreased as the wind shear velocity increased, following a power function, irrespective of the width and height of the nebkha. There are some uncertainties about the effect of the aspect ratio of the nebkha on the formation of wind shadows as a result of the omission of the transport of sand in the simulations. It is suggested that the length of wind shadows is dependent on the absolute values of nebkha width and height rather than the nebkha aspect ratio. Although the numerical results were consistent with the results of the wind tunnel experiments, the wind tunnel experiments showed that the height of the nebkha had a negative effect on the elongation of the shadow dunes. The sedimentary structures revealed by ground‐penetrating radar surveys of the dunes in the Taitema Dry Lake, in the eastern Taklimakan Desert, China, showed that the formation of shadow dunes can be divided into three phases. Shadow dunes are initially controlled by horizontal separation flow and then elongate following the same growth mechanisms as linear dunes, eventually breaking up into isolated barchans or short, temporary linear dunes. However, the formation of shadow dunes does not necessarily call for the three phases depending on the local wind regime and sediment supply.

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“…Field observations suggest that the turnover time of dunes in nature may range from months to years (Pye and Tsoar, 2009;Ewing et al, 2015) and the evolutionary processes associated with the turnover time lengths are not yet in-depth explored. Several small-scale experiments have been conducted to achieve complete evolutionary process, such as those in wind tunnels Dauchot et al, 2002;Kroy et al, 2002;Faria et al, 2011) and in water channels (Hersen, 2005;Groh et al, 2008;Franklin and Charru, 2011). Small-scale experiment has advantages in quantifying the influence of various controllable factors.…”

Section: Introductionmentioning

confidence: 99%

Evolution of crescent-shaped sand dune under the influence of injected sand flux: scaling law and wind tunnel experiment

et al. 2017

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This paper studies the evolution of crescent-shaped dune under the influence of injected flux. A scaling law and a wind tunnel experiment are carried out for comparison. The experiment incorporates a novel image processing algorithm to recover the evolutionary process. The theoretical and experimental results agree well in the middle stage of dune evolution, but deviate from each other in the initial and final stages, suggesting that the crescent-shaped dune evolution is intrinsically scale-variant and that the crescent shape breaks down under unsaturated condition.

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Wind tunnel and computational study of the stoss slope effect on the aeolian erosion of transverse sand dunes

Cited by 40 publications

References 31 publications

Long‐Wavelength Sinuosity of Linear Dunes on Earth and Titan and the Effect of Underlying Topography

Long‐Wavelength Sinuosity of Linear Dunes on Earth and Titan and the Effect of Underlying Topography

Effects of Wind Velocity and Nebkha Geometry on Shadow Dune Formation

Evolution of crescent-shaped sand dune under the influence of injected sand flux: scaling law and wind tunnel experiment

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