An experimental study of the dynamics of saltation within a three-dimensional framework

O’Brien, Patrick; Neuman, Cheryl McKenna

doi:10.1016/j.aeolia.2017.09.003

Cited by 14 publications

(16 citation statements)

References 36 publications

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“…Particle diameter ( d ) was calculated by averaging the measurements in pixels for each set of image pairs within each camera frame and converting this value to millimeter ( d p ) using a scaling factor. Explained in detail in O'Brien and McKenna Neuman (), a correction factor then must be applied to account for errors arising from particle rotation, flaring, stretching and complex particle geometry, as well as frame noise reduction and particle image identification. The magnitude of this correction ( ζ ), however, is relatively small (1.03 to 1.06).…”

Section: Resultsmentioning

confidence: 99%

“…As described in detail in O'Brien (2018) and O'Brien and McKenna Neuman (2016, 2017, the particle tracking velocimetry (PTV) system operated at the Trent Environmental Wind Tunnel facility consists of a 1 W, 532 nm, Nd-Yag laser, a pco.dimax HD™ high-speed camera, and software developed in-house that automatically identifies and tracks particles using a method known as Expected Particle Area Searching (EPAS). Note.…”

Section: Particle Tracking Velocimetry Sampling Design and Efficiencymentioning

confidence: 99%

“…Direct measurements of τ p are even more difficult to obtain, as they require detailed information on the velocities (both impact and ejection) and mass (diameter) of all particles traveling through a vertical transect of the flow. Only within the last several years have particle tracking technologies (PTV) become sufficiently refined to measure these attributes simultaneously (O'Brien & McKenna Neuman, , ; O'Brien ). As a consequence, τ p usually has been inferred, from either vertical profiles of τ − τ a or numerical simulation (Kok et al, , Duran et al, , Pähtz & Durán, , ).…”

Section: Introductionmentioning

confidence: 99%

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Experimental Validation of the Near‐Bed Particle‐Borne Stress Profile in Aeolian Transport Systems

O’Brien

Neuman

2019

JGR Earth Surface

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Self‐regulation of sediment transport by wind is widely assumed to derive from the partitioning of momentum from the fluid flow to the particle cloud. Consequently, the fluid stress on the bed surface is suggested by some to drop below that required to entrain particles, while the cloud is sustained by particle ricochet and splash that derive from the impacts of particles moving ballistically along the bed surface. While these theoretical constructs underpin present‐day numerical models of aeolian saltation, the particle‐borne stress has never been measured directly in either a laboratory or field setting. Such measurements are required for model validation and calibration of numerical simulations and were undertaken in vertical profile in the Trent Environmental Wind Tunnel using particle tracking velocimetry. Test sand was normally distributed with a median diameter of 590 μm. Particle momentum was calculated from the diameter and velocity of each image pair captured using high‐speed photography and then summed within each elevation band. The median diameter of the air‐borne particles was found to increase with friction velocity (u*), suggestive of sorting of the bed surface, and to decrease with elevation. Within a two‐dimensional framework, the vertical and windward components of the particle velocity were found to increase with elevation, with u* having little to no influence. Confirming the results of previous numerical simulations, these experiments show that the normalized particle‐borne stress increases exponentially toward the bed surface; however, within the lowest few millimeters where particle splash dominates, no consistent change is observed with elevation.

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Section: Resultsmentioning

confidence: 99%

Section: Particle Tracking Velocimetry Sampling Design and Efficiencymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Experimental Validation of the Near‐Bed Particle‐Borne Stress Profile in Aeolian Transport Systems

O’Brien

Neuman

2019

JGR Earth Surface

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“…Typically, B ≈ C/ 2 ≈ 1. All aerodynamically lifted sand particles are entrained with resultant velocity of 0:63 ffiffiffiffiffiffiffiffiffi ffi τ w =ρ p (Anderson & Hallet, 1986) and angle of 36° (Namikas, 2003). It is noteworthy that η a and τ *p (henceforth termed "resistance level") in equation 7 will observably influence the simulated results.…”

Section: The Motion Of Sand Particlesmentioning

confidence: 99%

The Influence of Surface Stress Fluctuation on Saltation Sand Transport Around Threshold

2020

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Multiscale wind velocity fluctuation and complex inertial response of sand saltation to wind variations give rise to intermittent and nonuniform sand transport, which greatly challenges the prediction of transport rate under wind conditions around saltation threshold. In this paper, three-dimensional sand saltation within simulation domain of wind tunnel scale is modeled based on large eddy simulation of turbulent wind. Special attention is paid to the prediction of surface shear stress and consequently aerodynamic entrainment. When the wall stress model considering the influence of large-scale turbulent structures was employed in case of relatively small resistance level for calculating particle aerodynamic entrainment, the model results predict sand transport below the impact threshold. The sand transport rate in this regime increases exponentially with mean wall stress, in contrast to the standard power law-like behavior above the impact threshold. Aerodynamic entrainment and strong transport events lag behind high-speed fluids sweep on a large scale even in wind tunnel, but the spatiotemporal variability of small-scale sand transport is still unclear and quite complex due to transport inertia.

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“…This seems to support Owen's hypothesis again. Recently, O'Brien and Neuman (2016Neuman ( , 2017Neuman ( , 2019 used an improved particle tracking technique (PTV-EPAS) to make a more precise measurement of the particle trajectories, kinetic energy, flux density, and particle-borne stress in aeolian transport systems. Their results showed that the impact velocity of particles has no dependency on the frictional wind speed.…”

Section: Introductionmentioning

confidence: 99%

Modeling the effect of saltation on surface layer turbulence

Huang

2020

Earth Surf Processes Landf

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Particle–turbulence interaction has been a research focus in the field of pneumatic transport, especially in aeolian environments. However, knowledge regarding the effect of saltating particles on the turbulence characteristics is very limited. In this article, a process of sand‐laden flow from forming sand streamers to stability is investigated via a coupled mathematical model of wind‐blown sand that includes the spatiotemporal development. The variations in the turbulence characteristics, such as the mean velocity and turbulence intensity in clean air or sand‐laden flow field, are analyzed. The results show that the splash process of sand grains near the wall decrease the wind speed in the saltation layer and destroy the low‐speed streaks. Moreover, the profiles of streamwise turbulence intensity exhibit a transition from ‘decreasing’ to ‘increasing’ and approximately intersect at an ‘intensity focus’, which is presented for the first time. Furthermore, it was found that saltating particles could enhance the Reynolds stress. Meanwhile, it was also noticed that the shear stress at the wall surface is greater than the impact threshold and that there is a tendency towards the impact threshold. Therefore, saltation makes the particle Reynolds number of sand‐laden flow higher than that under non‐saltation conditions, thus changing the particles’ effect on the turbulence intensity. Gravity‐dominated saltation is probably the most essential difference between wind‐blown sand and other traditional two‐phase flows. © 2020 John Wiley & Sons, Ltd.

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An experimental study of the dynamics of saltation within a three-dimensional framework

Cited by 14 publications

References 36 publications

Experimental Validation of the Near‐Bed Particle‐Borne Stress Profile in Aeolian Transport Systems

Experimental Validation of the Near‐Bed Particle‐Borne Stress Profile in Aeolian Transport Systems

The Influence of Surface Stress Fluctuation on Saltation Sand Transport Around Threshold

Modeling the effect of saltation on surface layer turbulence

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