Date of Award
Master of Science (MS)
Ocean Engineering and Marine Sciences
Robert J. Weaver
Kelli Z. Hunsucker
Deniz Velioglu Sogut
Richard B. Aronson
Erosion and accretion are coastal processes that directly affect the safety of coastal communities. Dimensionless parameters, such as the Shields and Ursell number, have historically been used to predict sediment motion in the nearshore region based on shear stress and wave linearity. This study uses particle image velocimetry to measure the velocity field of sediment within a wave flume and calculate these parameters for various wave profiles. Five regular wave trials and five irregular wave trials were run within the wave flume at varying depths to model how net transport changes as waves approach the shoreline. An instantaneous Shields number was calculated for every 1/960th of a second for each trial. The cnoidal Ursell number was iteratively solved for each trial. Through an analysis of pixel intensities of high-frame rate camera captured images, a method of calculating the instantaneous active bed thickness at a single point within the wave flume was created. From the particle image velocimetry derivations and active bed thickness measurements, net transport and average flux rates were calculated and compared to the dimensionless parameters. Through a comparison between the experimental measurements and four theoretical models, the validity of particle image velocimetry for deriving dimensionless parameters is assessed. Results show the successful application of the active bed thickness method and Shields number derivations. A considerable discrepancy is seen between the Ursell number and expected net transport and errors are discussed. The dependency of accurate particle image velocimetry derivations on proper light illumination and suspended sediment rates is observed. This study highlights the importance of various factors in completing particle image velocimetry studies and improves the application of nearshore modeling for future research.
Hoch, Caroline, "Predicting Near-Bed Sediment Transport through Particle Image Velocimetry" (2023). Theses and Dissertations. 1273.