Author(s): Papanicolaou N. Athanasios; Mohamed Elhakeem; Ehab Abdelsalam
Linked Author(s):
Keywords: Bedload; Particle velocity; Advanced techniques
Abstract: Nowadays, the advances made in scientific visualization techniques have enhanced our capabilities of tracking sediment and measuring sediment rates. The focus of this study is to provide a new experimental approach to determine the displacement speed of particles rolling atop a well packed layer of spheres and provide a formula that describes the average displacement speed of particles as a function of the particles geometry and weight, settling velocity, and the frictional characteristics of flow. For this purpose, this study presents the measurements of the displacement speeds of three different sized spherical particles under varying flow conditions and bed roughness using Gravel Transport Sensor (GTS). The particles, ranging in size from 15. 9 to 25. 4 mm in diameter, primarily experienced motion due to rolling. The displacement speed information is required for the prediction of sediment fluxes, which can be used to model local sediment entrainment in natural gravel streams. For this purpose, a laboratory flume was used to perform 30 experimental runs. The tests were repeated 15 times, or until repeatability was established. Velocity profiles, shear stress, discharge, and bulk velocity were acquired for each run. An Acoustic Doppler Velocimeter (ADV) and Swoffer were used to obtain the velocity profiles. Sediment motion was monitored using a plan view from a digital camera mounted above the flume. Individual frames depicting a particle’s motion were produced using Asymetrix Digital Video Producer (DVP) and Adobe Photoshop 4. 0. Data translation software combined the individual frames to calculate the displacement speed of sediment motion. The results are compared with values predicted by bed load formulas developed by Sekine and Lee. Values observed in this experiment are greater than the values predicted by Sekine and less than the values predicted by Lee.
Year: 2007