Study on the 3D Hydrodynamic Characteristics and Velocity Uniformity of a Gravity Flow Circular Flume

Flumes have been widely used in water conservancy science and environmental science research. It is of great significance to obtain the hydrodynamic characteristics and flow field uniformity in the flume. In this study, a new type of annular flume was taken as an example. The 3D flow field was simulated by using a commercial computational fluid dynamics (CFD) code, and was also measured by acoustic doppler velocimeter (ADV) to verify the simulation results. The average relative error range was between 8.37% and 9.95%, the simulated results basically reflected the actual situation of the flow field. On this basis, the structural characteristics of flow field were analyzed. A new calculation method of flow velocity uniformity was presented according to the flow characteristics of natural open channels. The velocity uniformity in the straight channel was calculated and analyzed based on this method, and the influence of speed on the velocity uniformity was further discussed. The length of uniform section was negatively correlated with the rotational speed (average velocity), which was between 39 cm and 101 cm in the straight, and the uniformity coefficient was less than 10%. Finally, the water flow characteristics in the straight channel without wheel were compared with the natural open channel flow. The longitudinal velocity was well fitted with the Prandtl logarithmic distribution formula (R2 > 0.977), and the application feasibility of the flume was analyzed. This study can provide technical support for the development and application of annular flume.

Bedload transport in rivers, size matters but so does shape

Bedload transport modelling in rivers takes into account the size and density of pebbles to estimate particle mobility, but does not formally consider particle shape. To address this issue and to compare the relative roles of the density and shape of particles, we performed original sediment transport experiments in an annular flume using molded artificial pebbles equipped with a radio frequency identification tracking system. The particles were designed with four distinct shapes and four different densities while having the same volume, and their speeds and distances traveled under constant hydraulic conditions were analyzed. The results show that particle shape has more influence than particle density on the resting time between particle displacement and the mean traveling distance. For all densities investigated, the particle shape systematically induced differences in travel distance that were strongly correlated (R2 = 0.94) with the Sneed and Folks shape index. Such shape influences, although often mentioned, are here quantified for the first time, demonstrating why and how they can be included in bedload transport models.

Mud-clast armoring and its implications for turbidite systems

ABSTRACT Seafloor sediment density flows are the primary mechanism for transporting sediment to the deep sea. These flows are important because they pose a hazard to seafloor infrastructure and deposit the largest sediment accumulations on Earth. The cohesive sediment content of a flow (i.e., clay) is an important control on its rheological state (e.g., turbulent or laminar); however, how clay becomes incorporated into a flow is poorly understood. One mechanism is by the abrasion of (clay-rich) mud clasts. Such clasts are common in deep-water deposits, often thought to have traveled over large (more than tens of kilometers) distances. These long travel distances are at odds with previous experimental work that suggests that mud clasts should disintegrate rapidly through abrasion. To address this apparent contradiction, we conduct laboratory experiments using a counter rotating annular flume to simulate clast transport in sediment density flows. We find that as clay clasts roll along a sandy floor, surficial armoring develops and reduces clast abrasion and thus enhances travel distance. For the first time we show armoring to be a process of renewal and replenishment, rather than forming a permanent layer. As armoring reduces the rate of clast abrasion, it delays the release of clay into the parent flow, which can therefore delay flow transformation from turbidity current to debris flow. We conclude that armored mud clasts can form only within a sandy turbidity current; hence where armored clasts are found in debrite deposits, the parent flow must have undergone flow transformation farther up slope.

Experimental Investigation of Erosion Characteristics of Fine-Grained Cohesive Sediments

In this short communication, the erosion process of the fine, cohesive sediment collected from the upper River Taw in South West England was studied in a rotating annular flume located in the National Water Research Institute in Burlington, Ontario, Canada. This study is part of a research project that is underway to model the transport of fine sediment and the associated nutrients in that river system. The erosion experimental data show that the critical shear stress for erosion of the upper River Taw sediment is about 0.09 Pa and it did not depend on the age of sediment deposit. The eroded sediment was transported in a flocculated form and the agent of flocculation for the upper River Taw sediment may be due to the presence of fibrils from microorganisms and organic material in the system. The experimental data were analysed using a curve fitting approach of Krone and a mathematical model of cohesive sediment transport in rotating circular flumes developed by Krishnappan. The modelled and measured data were in good agreement. An evaluation of the physical significance of Krone’s fitting coefficients is presented. Variability of the fitting coefficients as a function of bed shear stress and age of sediment deposit indicate the key role these two factors play in the erosion process of fluvial cohesive sediment.

Prediction of erosional rates for cohesive sediments in annular flume experiments using artificial neural networks

Artificial neural network is used to predict development of suspended sediment concentration in annular flume experiments on cohesive sediment erosion. Natural sediment for the experiments was taken from the River Rhine and subjected to a consecutive increase in the bed shear stress. The development of the suspended particulate matter (SPM) was measured and then utilized for artificial neural network training, validation, and testing, including independent testing on new data sets. Several network configurations were examined, in particular, with and without autoregressive input. Additionally, relative importance of auxiliary physical-chemical parameters was analyzed. Artificial neural network with autoregressive input showed very high precision in the SPM prediction for all independent test cases achieving average mean squared error 0.034 and regression value 0.998. It was found that for an abundant training sample, the SPM parameter itself is enough to obtain high quality prediction. At the same time, physical-chemical parameters may provide some improvement to the artificial neural network prediction in cases that comprise values unprecedented in the training sample.