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A field study was conducted to examine the turbulent properties of the flow around a naturally formed cluster bedform. This was carried out on a mountain river using a 3D acoustic Doppler velocimeter (ADV). Concurrent with this objective, the ability of the ADV to make measurements in a shallow flow over a cobble bed ([h.sub.o]/[d.sub.84] = 1.75) was examined. ADV measurements in natural clear-water shallow flows around obstacles are inherently difficult to obtain due to (1) signal interference between the acoustic reflections from the boundary and the ADV sample volume; (2) regions of high turbulent intensity, such as in local detached shear layers; and (3) low concentrations of suspended particles passing through the ADV sampling volume. These processes result in velocity time series that contain a significant amount of spikes, lower-than-average signal-to-noise ratios, and lower than average correlation values. A filtering process that optimized the removal of bad points while retaining a sufficient number of points to describe the velocity time series histogram was developed. In general, flow over the study section can be described by an inner roughness layer dominated by large roughness and detached flow, and an outer flow that exhibits a form of log scaling. It was found that the cluster acts to locally modify this structure by shifting the elevation of the roughness layer and the zone of primary production and dissipation of turbulent energy up towards the center of the water column. Mean and turbulent statistics, energy distributions, spectral properties, and a quadrant analysis are presented to characterize the flow around the cluster. CE Database subject headings: Turbulent flow; River beds; Bedforms; Gravel; Mountain streams; Measuring instruments; Flow measurement.

The present study examines the flow around a self-occurring cluster bed form and the use of general computation fluid dynamics methods for hydraulic and geophysical flow applications. This is accomplished through a comprehensive experimental/numerical investigation. In the laboratory, cluster bed forms are first formed from movable sediment, and laser Doppler velocimeter measurements of two-dimensional fluid velocity are then taken around a formed cluster. A three-dimensional (3D) Reynolds averaged Navier-Stokes simulation of the physical cluster and flow conditions is then conducted using near-wall, shear stress transport (SST) turbulence modeling with the inclusion of hydraulic roughness, [k.sub.s] (R = 31,150, [k.sub.s]/h = 0.1, [k.sup.+.sub.s] = 274, i.e., in the fully rough regime). SST near-wall modeling is advantageous compared to the more widely used wall functions approach for flows with significant roughness and flow separation because the model equations can be integrated down to the wall. Therefore, SST near-wall modeling makes no a priori assumption that the law of the wall is valid throughout the wall region of the flow. Additionally, it has the ability to intrinsically handle boundary roughness through the boundary condition for turbulent specific dissipation at the wall, allowing for wall functions to be bypassed in accounting for roughness effects. The study shows that in the wall region surrounding the cluster, flow is 3D and quite complex, with different scales of embedded flow structures dominating the cluster wake and leading to flow heterogeneities in pressure and bed-shear stress. Results also indicate that near-wall modeling with SST compared favorably with the experimental flow data without tuning of model constants. DOI: 10.1061/(ASCE)0733-9429(2007) CE Database subject headings: Bedforms; Microstructures; Turbulent flow; Numerical models; Simulation; Computational fluid dynamics technique; Hydraulic engineering.

This study explores the use of an automated image-based method for characterizing grain-size distributions (GSDs) of exposed open-framework gravels by comparing the GSDs measured with the image-based method to distributions obtained with two pebble-count methods. Selection of grains for the two pebble-count methods was carried out using a gridded sampling frame and the heel-to-toe Wolman walk method at six field sites. At each site, 500-particle pebble-count samples were collected with each of the two pebble-count methods and digital images were systematically collected over the same sampling area. For the methods used, pebble counts collected with the gridded sampling frame were assumed to be the most accurate representations of the true grain-size population. Therefore, results from the image-based method were compared to the grid-derived GSDs for accuracy estimates; comparisons between the grid and Wolman walk methods were conducted to give an indication of possible variation between commonly used methods for the particular field sites used in the study. The grain-size comparisons were made at two spatial scales. At the larger scale, results from the image-based method were integrated over the sampling area required to collect the 500-particle pebble-count samples. At the smaller sampling scale, the image derived GSDs were compared to those from 100-particle, pebble-count samples obtained with the gridded sampling frame. The comparison shows that the image-based method performed reasonably well on five of the six study sites. For those five sites, the image-based method slightly underestimated all grain-size percentiles relative to the pebble counts collected with the gridded sampling frame, but the method performed well in estimating the median grain size (the average bias for ψ5, ψ50, and ψ95 was 0.07ψ, 0.04ψ, and 0.19ψ, respectively). The Wolman pebble-counts yielded coarser results than the pebble counts obtained with the gridded sampling frame, especially for the smaller percentiles (the average bias for ψ5, ψ50, and ψ95 was 0.20ψ, 0.16ψ, and 0.04ψ, respectively). Oversegmentation of large pitted grains in the image-analysis procedures was identified as a leading cause for failure of the image-based method at one of the sites. It is likely that lower degrees of oversegmentation and physical particle orientation contributed to the slight underestimation of all grain-size percentiles in the image-based method. [ABSTRACT FROM AUTHOR]

Laboratory experiments are a convenient way to study morphodynamic processes associated with subaqueous fans. However, the flows driving such systems can be difficult to hydraulically characterize due to the shallowness of the flows, the spatial and temporal dynamics of the autogenic channels, and the mixing at the interface of the ambient fluid and density current. The objective of this study is to develop a set of methods to quantify hydraulic variables in laterally unconstrained and morphologically active density currents. Herein, a methodology is presented capable of characterizing a density current flow field with direct application to submarine fan experiments. This is done with a combination of: (1) particle tracking velocimetry (PTV) analysis of tracers within the density current, (2) flow width measurements from overhead images, and (3) solution of the mass and volume conservation equations in one-dimension to obtain layer-averaged velocity, depth, and fractional excess density. [ABSTRACT FROM AUTHOR]