Channel Design Emphasizing Fine Sediments and Survey of Alluvial Channel Sediment Transport

2021 ◽  
pp. 236-293
Keyword(s):  
Sediment Transport ◽  
Channel Design ◽  
Fine Sediments ◽  
Alluvial Channel

Stable alluvial channel design using evolutionary neural networks

2018 ◽  
Vol 566 ◽  
pp. 770-782 ◽  
Author(s):  
Saba Shaghaghi ◽  
Hossein Bonakdari ◽  
Azadeh Gholami ◽  
Ozgur Kisi ◽  
Jalal Shiri ◽  
...  
Keyword(s):  
Neural Networks ◽  
Channel Design ◽  
Evolutionary Neural Networks ◽  
Alluvial Channel

scholarly journals Empirical Studies in Alluvial Streams

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Levent Yilmaz
Keyword(s):  
Single Channel ◽  
Empirical Studies ◽  
Laboratory Data ◽  
Fine Sediments ◽  
Channel Interaction ◽  
Variable Curvature ◽  
Alluvial Channel ◽  
Channel Patterns ◽  
Bed Material ◽  
River Meandering

Meander flow takes place in one single channel which oscillates more orless regularly with amplitudes that tend to increase with time. Meandersare found in beds of fine sediments with gentle slopes. In this study, effortwill be made to investigate meanders’ turbulent boundary layer and toimprove the present knowledge about the river meandering phenomena. Itis assumed that the development of the perturbations which develop intomeanders or braids, is longer than the width of the channel. Interaction between the flow and mobile boundaries produces channel patterns which areclassified as meandering or braided. It is therefore long compared with theripples or dunes which cover the bed of such a channel and whose wavelength is shorter than the width of the channel. The variation of resistance toflow and rate of transport of bed material with velocity are discussed brieflyand taken into account. Meander flow and meander shear stress distribution of the channel are described. The basis is a steady, two-dimensionalmodel of flow in an alluvial channel with variable curvature. The meanderdevelopment is described by forcing a travelling, small-amplitude channelalignment wave on the system, and determining the growth characteristicsof the wave. Laboratory data are used to verify the formulas.

The Intrusion of Fine Sediments into a Stable Gravel Bed

1979 ◽  
Vol 36 (2) ◽  
pp. 204-210 ◽  
Author(s):  
Robert L. Beschta ◽  
William L. Jackson
Keyword(s):  
Sediment Transport ◽  
Pore Space ◽  
Particle Diameter ◽  
Experimental Tests ◽  
Gravel Bed ◽  
Fine Sediments ◽  
Median Particle Diameter ◽  
Key Words Sediment ◽  
Median Particle ◽  
Flow Variables

A rectangular flume was used to study variables affecting the intrusion of fine sands into a stable gravel streambed. The amount of intrusion by sand (median particle diameter 0.5 mm) was determined under varied conditions of discharge, depth, velocity, flume slope, and rates of sediment transport. During all experimental tests, sand particles were trapped in voids within the upper 10 cm of an initially clean gravel bed (median particle diameter 15 mm), forming a barrier to further intrusion. An analysis of flow variables showed that flow conditions, as indexed by Froude number, significantly (90% confidence level) affected intrusion amounts, possibly by influencing the rate and depth of formation of the sand seal. Intrusion amounts, expressed as a percent of total volume, varied from 2 to 8%. Two replications used a finer grade sand (median particle diameter 0.2 mm) that intruded more and, in one case, completely filled the gravel pore space (25% by volume), further indicating that particle size, and not hydraulic variables, may have a more important influence on the total amount of intrusion. Key words: sediment transport, intrusion, streambed, substrates, riffles, sedimentation

Review and assessment of the theories of stable alluvial channel design

2012 ◽  
Vol 39 (4) ◽  
pp. 481-487 ◽  
Author(s):  
Vishal Deshpande ◽  
Bimlesh Kumar
Keyword(s):  
Channel Design ◽  
Alluvial Channel

scholarly journals Flocculation processes and sedimentation of fine sediments in the open annular flume – experiment and numerical modeling

2013 ◽  
Vol 1 (1) ◽  
pp. 437-481 ◽  
Author(s):  
I. Klassen ◽  
G. Hillebrand ◽  
N. R. B. Olsen ◽  
S. Vollmer ◽  
B. Lehmann ◽  
...  
Keyword(s):  
Experimental Data ◽  
Fractal Dimension ◽  
Sediment Transport ◽  
Process Model ◽  
Settling Velocity ◽  
Numerical Models ◽  
Sediment Concentration ◽  
Small Scale ◽  
Fine Sediments ◽  
Aggregation Processes

Abstract. The prediction of cohesive sediment transport requires numerical models which include the dominant physico-chemical processes of fine sediments. Mainly in terms of simulating small scale processes, flocculation of fine particles plays an important role since aggregation processes affect the transport and settling of fine-grained particles. Flocculation algorithms used in numerical models are based on and calibrated using experimental data. A good agreement between the results of the simulation and the measurements is a prerequisite for further applications of the transport functions. In this work, the sediment transport model (SSIIM) was extended by implementing a physics-based aggregation process model based on McAnally (1999). SSIIM solves the Navier-Stokes-Equations in a three-dimensional, non-orthogonal grid using the k-ε turbulence model. The program calculates the suspended load with the convection-diffusion equation for the sediment concentration. Experimental data from studies in annular flumes (Hillebrand, 2008; Klassen, 2009) is used to test the flocculation algorithm. Annular flumes are commonly used as a test rig for laboratory studies on cohesive sediments since the flocculation processes are not interfered with by pumps etc. We use the experiments to model measured floc sizes, affected by aggregation processes, as well as the sediment concentration of the experiment. Within the simulation of the settling behavior, we use different formulas for calculating the settling velocity (Stokes, 1850 vs. Winterwerp, 1998) and include the fractal dimension to take into account the structure of flocs. The aim of the numerical calculations is to evaluate the flocculation algorithm by comparison with the experimental data. The results from these studies have shown, that the flocculation process and the settling behaviour are very sensitive to variations in the fractal dimension. We get the best agreement with measured data by adopting a characteristic fractal dimension nfc to 1.4. Insufficient results were obtained when neglecting flocculation processes and using Stokes settling velocity equation, as it is often done in numerical models which do not include a flocculation algorithm. These numerical studies will be used for further applications of the transport functions to the SSIIM model of reservoirs of the Upper Rhine River, Germany.

High-Order Velocity Moments of Turbulent Boundary Layers in Seepage Affected Alluvial Channel

2018 ◽  
Vol 140 (8) ◽  
Author(s):  
Anurag Sharma ◽  
Bimlesh Kumar
Keyword(s):  
Boundary Layer ◽  
Sediment Transport ◽  
Turbulent Boundary Layer ◽  
Seepage Flow ◽  
Streamwise Velocity ◽  
High Order ◽  
Alluvial Channel ◽  
Even Order ◽  
Logarithmic Law ◽  
Velocity Moments

In this work, we have performed the flume study to analyze the high-order velocity moments of turbulent boundary layer with and without downward seepage. Sediment transport experiments were done in the laboratory for no seepage (NS), 10% seepage (10%S), and 15% seepage (15%S) cases. Measures of streamwise velocity variance were found increasing with seepage, which lead to increase in sediment transport with seepage. Results show that the variance of streamwise velocity fluctuation follows logarithmic law with distance away from the bed, within inner layer. This observation is also valid for even-order moments obtained in this work. The results show that the (2p-order moments)1/p also follows logarithmic law. The slopes Ap in the turbulent boundary layer seem fairly unaffected to NS and seepage flow but follows nonuniversal behavior for NS and seepage runs. The computed slope based on the Gaussian statistics does not agree well with the slope obtained from the experimental data and computed slope are reliable with sub-Gaussian performance for NS flow and super-Gaussian behavior for seepage flow.

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