Modelling of resuspension due to fish activity: Mathematical modeling and annular flume experiments

2017 ◽  
Vol 32 (3) ◽  
pp. 421-431
Author(s):  
Olya Skulovich ◽  
Catrina Cofalla ◽  
Caroline Ganal ◽  
Holger Schüttrumpf ◽  
Avi Ostfeld
Keyword(s):  
Mathematical Modeling ◽  
Flume Experiments ◽  
Annular Flume ◽  
Fish Activity

scholarly journals Sediment Transport of Fine Sand to Fine Gravel on Transverse Bed Slopes in Rotating Annular Flume Experiments

2018 ◽  
Vol 54 (1) ◽  
pp. 19-45 ◽  
Author(s):  
Anne W. Baar ◽  
Jaco de Smit ◽  
Wim S. J. Uijttewaal ◽  
Maarten G. Kleinhans
Keyword(s):  
Sediment Transport ◽  
Fine Sand ◽  
Flume Experiments ◽  
Annular Flume ◽  
Rotating Annular Flume ◽  
Fine Gravel

Modelling Erosion and Deposition of Cohesive Sediments from Hay River, Northwest Territories, Canada

2003 ◽  
Vol 34 (1-2) ◽  
pp. 125-138 ◽  
Author(s):  
David Milburn ◽  
B.G. Krishnappan
Keyword(s):  
Shear Stress ◽  
Northwest Territories ◽  
River Sediment ◽  
Critical Shear Stress ◽  
Cohesive Sediment ◽  
Cohesive Sediments ◽  
Bed Shear Stress ◽  
Flume Experiments ◽  
Annular Flume ◽  
Erosion Processes

A large volume sample of river-bed cohesive sediment and water from Hay River, Northwest Territories, Canada was collected during a spring field program in 2000 as part of a study on under-ice movement of sediment just before breakup. Controlled laboratory experiments were subsequently conducted on the Hay River water/sediments in a rotating annular flume at Burlington, Ontario, Canada to better understand the deposition and erosion processes of cohesive sediment transport. The deposition experiments in the rotating flume confirmed that the Hay River sediment is cohesive and the critical shear stress for deposition and the rates of deposition are a function of bed shear stress and the initial concentration of the sediment in suspension. The erosion experiments provided quantitative data on the critical shear stress for erosion and the rates of erosion as a function of bed shear stress and the age of the sediment deposit. The erosion experiments also indicated that the growth of the biofilm had an influence on the erosion characteristics of the Hay River sediment. Based on the data from the rotating circular flume experiments, a modelling strategy is proposed for calculating the under-ice transport of the cohesive sediments in the Hay River.

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

2018 ◽  
Vol 1 (2) ◽  
pp. 99-111
Author(s):  
Olya Skulovich ◽  
Caroline Ganal ◽  
Leonie K. Nüßer ◽  
Catrina Cofalla ◽  
Holger Schuettrumpf ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Mean Squared Error ◽  
Training Sample ◽  
River Rhine ◽  
Chemical Parameters ◽  
Flume Experiments ◽  
Annular Flume ◽  
Physical Chemical ◽  
Artificial Neural

Abstract 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.

Bulk drag coefficient of a subaquatic vegetation subjected to irregular waves: Influence of Reynolds and Keulegan-Carpenter numbers

2020 ◽  
pp. 34-42
Author(s):  
Thibault Chastel ◽  
Kevin Botten ◽  
Nathalie Durand ◽  
Nicole Goutal
Keyword(s):  
Drag Coefficient ◽  
Wave Height ◽  
Wave Attenuation ◽  
Empirical Relationship ◽  
Breaking Waves ◽  
Irregular Waves ◽  
Geometrical Parameters ◽  
Flume Experiments ◽  
Seagrass Meadows ◽  
Artificial Vegetation

Seagrass meadows are essential for protection of coastal erosion by damping wave and stabilizing the seabed. Seagrass are considered as a source of water resistance which modifies strongly the wave dynamics. As a part of EDF R & D seagrass restoration project in the Berre lagoon, we quantify the wave attenuation due to artificial vegetation distributed in a flume. Experiments have been conducted at Saint-Venant Hydraulics Laboratory wave flume (Chatou, France). We measure the wave damping with 13 resistive waves gauges along a distance L = 22.5 m for the “low” density and L = 12.15 m for the “high” density of vegetation mimics. A JONSWAP spectrum is used for the generation of irregular waves with significant wave height Hs ranging from 0.10 to 0.23 m and peak period Tp ranging from 1 to 3 s. Artificial vegetation is a model of Posidonia oceanica seagrass species represented by slightly flexible polypropylene shoots with 8 artificial leaves of 0.28 and 0.16 m height. Different hydrodynamics conditions (Hs, Tp, water depth hw) and geometrical parameters (submergence ratio α, shoot density N) have been tested to see their influence on wave attenuation. For a high submergence ratio (typically 0.7), the wave attenuation can reach 67% of the incident wave height whereas for a low submergence ratio (< 0.2) the wave attenuation is negligible. From each experiment, a bulk drag coefficient has been extracted following the energy dissipation model for irregular non-breaking waves developed by Mendez and Losada (2004). This model, based on the assumption that the energy loss over the species meadow is essentially due to the drag force, takes into account both wave and vegetation parameter. Finally, we found an empirical relationship for Cd depending on 2 dimensionless parameters: the Reynolds and Keulegan-Carpenter numbers. These relationships are compared with other similar studies.

Cerebral Blood Circulation in Premature Infants by Means of Mathematical Modeling

2015 ◽  
Vol 46 (S 01) ◽  
Author(s):  
R. Lampe ◽  
N. Botkin ◽  
V. Turova ◽  
T. Blumenstein ◽  
A. Alves-Pinto
Keyword(s):  
Mathematical Modeling ◽  
Premature Infants ◽  
Blood Circulation ◽  
Cerebral Blood Circulation
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