Date of Award
Master of Science
Dr. John Schwartz
Dr. James Coder and Dr. Jon Hathaway
The advances in particle tracking codes in the recent years has made possible to track the intermittent movement of a large number of sediment particles with precision and in an automated way. The present study used this technique to study the velocity of the particle while it is in motion, the length it travels once it gets mobilized until it deposits, and the time it rests once deposited until it gets mobilized again. New modeling equations were developed to predict these quantities for a wide range of flow conditions and sediment sizes. These equations were combined to predict the virtual velocity of sediment, which is an equivalent velocity that accounts for both the moving and the resting time periods. This laboratory experimental study involved controlled flume tests where spherical particles were transported by the flow on top of a well-packed bed. The moving particles were gravel size and their diameter ranges from 0.43 to 1.35 times the diameter of the bed particles. The sediment transport stage ranged from incipient motion conditions (where particles were in motion only 2% of the total time), all the way to general motion were the particles almost never rested. A total of 25 experimental conditions were tested using a combination of 7 different flows and 5 different particle diameters. The particle trajectory was monitored by a camera and tracked using an open source particle tracking code. For each condition the mean resting time, displacement length and displacement time were calculated. On average, 120 data points were collected for each condition to get an accurate estimate of the average values of these three components. Equations were developed to predict these components as a function of the flow condition and sediment size. These equations were then combined to predict the virtual velocity of the sediment particles. The results of this study give insight to the physics that dominates the particle transport. Further research is needed to expand the use of these equations for natural sediment beds so they can better predict sediment transport rates in rivers.
Kyriakopoulos, Theodoros, "LAGRANGIAN BEDLOAD MOVEMENT PREDICTION USING THE VIRTUAL VELOCITY APPROACH. " Master's Thesis, University of Tennessee, 2020.