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- All Subjects: saltation
- Creators: Dorn, Ron
- Creators: Koschinsky, Julia
Spatial-Temporal Analysis of Barrett Freshmen 2007-2012: Source Area Analysis and Poisson Regression
Description
In order to help enhance admissions and recruiting efforts, this longitudinal study analyzed the geographic distribution of matriculated Barrett freshmen from 2007-2012 and sought to explore hot and cold spot locations of Barrett enrollment numbers using geographic information science (GIS) methods. One strategy involved   weighted mean center and standard distance analyses for each year of data for non-resident (out-of-state) freshmen home zip codes. Another strategy, a Poisson regression model, revealed recruitment "hot and cold spots" across the U.S. to project the expected counts of Barrett freshmen by zip code. This projected count served as a comparison for the actual admissions data, where zip codes with over and under predictions represented cold and hot spots, respectively. The mean center analysis revealed a westward shift from 2007 to 2012 with similar distance dispersions. The Poisson model projected zero-student zip codes with 99.2% accuracy and non-zero zip codes with 73.8% accuracy. Norwalk, CA (90650) and New York, NY (10021) represented the top out-of-state cold spot zip codes, while the model indicated that Chandler, AZ (85249) and Queen Creek, AZ (85242) had the most in-state potential for recruitment. The model indicated that more students have come from Albuquerque, NM (87122) and Aurora, CO (80015) than anticipated, while Phoenix, AZ (85048) and Tempe, AZ (85284) represent in-state locations with higher correlations between the variables included, especially regarding distance decay, and the than expected numbers of freshmen. The regression also indicated the existence of strong likelihood of attracting Barrett students.
ContributorsKostanick, Megan Elizabeth (Author) / Rey, Sergio (Thesis director) / Dorn, Ron (Committee member) / Koschinsky, Julia (Committee member) / Barrett, The Honors College (Contributor) / School of Geographical Sciences and Urban Planning (Contributor) / School of Politics and Global Studies (Contributor)
Created2013-05
Description
Sediment transport by atmospheric flows shapes landscapes on Earth and other planets. Improving the ability to quantify and predict sand transport by windblown (aeolian) processes has important implications for managing erosion, land degradation, desertification, dust emissions, air quality, and other climate change hazards and risks. Despite progress since Bagnold's seminal works in the 1930s, the most frequently used aeolian sand transport equations show discrepancies between predicted and observed transport rates upwards of 300%. Differences of this magnitude strongly support re-examining how fundamental physical aeolian processes are expressed in predictive equations. Wind tunnel experiments using a Particle Imaging Velocimetry/Particle Tracking Velocimetry (PIV/PTV) system with a high-speed camera and high-powered laser were conducted to visualize fluid motions and sand particle trajectories to provide simultaneous measurements of wind flow and sand transport to re-examine the fundamental physical relationships between flow dynamics, sediment motions, and bedform development.
The first experiment of this dissertation focuses on the characteristics of near-surface sand transport in the saltation cloud. From PTV particle trajectories, mean particle velocities appear independent of freestream wind speed, while velocity distribution characteristics (such as modality) and particle concentration intermittency vary with increasing sand transport. Particle trajectories from rippled bed runs show evidence of local slope influence on near-bed particle vectors.
The second experiment used manual sand grain tracking to quantify particle-bed splash interactions. Results highlight that common rebound and ejecta functions do not sufficiently represent aeolian saltation splash events. Data indicate a shadowing effect of ripples, suggesting feedback between the saltation cloud, splash events, and bedform migration.
The third experiment used dual PIV/PTV analysis to quantify fluid-particle interactions and compare sand concentrations with fluid stresses and turbulence characteristics through the saltation cloud. Results show that increased saltation leads to the disappearance of the constant fluid stress region, changes in aerodynamic roughness length, and increases in turbulence intensities. Leveraging technology advancements and multiple analysis methods, these results provide new, detailed information on the relationships between flow dynamics, sediment motions, and the presence of ripple bedforms. These novel empirical data illustrate some needed corrections to the theoretical and numerical frameworks for quantifying aeolian sand transport.
ContributorsKelley, Madeline (Author) / Schmeeckle, Mark (Thesis advisor) / Walker, Ian (Thesis advisor) / Dorn, Ron (Committee member) / Swann, Christy (Committee member) / Arizona State University (Publisher)
Created2023