School of Plant and Environmental Sciences

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https://hdl.handle.net/10919/91436
SPES was formed in 2017 from three departments: Crop and Soil Environmental Sciences; Horticulture; and Plant Pathology, Physiology, and Weed Science.

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Browsing School of Plant and Environmental Sciences by Department "Aerospace and Ocean Engineering"

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    Intercomparison of Small Unmanned Aircraft System (sUAS) Measurements for Atmospheric Science during the LAPSE-RATE Campaign
    Barbieri, Lindsay; Kral, Stephan T.; Bailey, Sean C. C.; Frazier, Amy E.; Jacob, Jamey D.; Reuder, Joachim; Brus, David; Chilson, Phillip B.; Crick, Christopher; Detweiler, Carrick; Doddi, Abhiram; Elston, Jack; Foroutan, Hosein; González-Rocha, Javier; Greene, Brian R.; Guzman, Marcelo I.; Houston, Adam L.; Islam, Ashraful; Kemppinen, Osku; Lawrence, Dale; Pillar-Little, Elizabeth A.; Ross, Shane D.; Sama, Michael P.; Schmale, David G. III; Schuyler, Travis J.; Shankar, Ajay; Smith, Suzanne W.; Waugh, Sean; Dixon, Cory; Borenstein, Steve; de Boer, Gijs (MDPI, 2019-05-10)
    Small unmanned aircraft systems (sUAS) are rapidly transforming atmospheric research. With the advancement of the development and application of these systems, improving knowledge of best practices for accurate measurement is critical for achieving scientific goals. We present results from an intercomparison of atmospheric measurement data from the Lower Atmospheric Process Studies at Elevation—a Remotely piloted Aircraft Team Experiment (LAPSE-RATE) field campaign. We evaluate a total of 38 individual sUAS with 23 unique sensor and platform configurations using a meteorological tower for reference measurements. We assess precision, bias, and time response of sUAS measurements of temperature, humidity, pressure, wind speed, and wind direction. Most sUAS measurements show broad agreement with the reference, particularly temperature and wind speed, with mean value differences of 1.6 ± 2.6 ∘ C and 0.22 ± 0.59 m/s for all sUAS, respectively. sUAS platform and sensor configurations were found to contribute significantly to measurement accuracy. Sensor configurations, which included proper aspiration and radiation shielding of sensors, were found to provide the most accurate thermodynamic measurements (temperature and relative humidity), whereas sonic anemometers on multirotor platforms provided the most accurate wind measurements (horizontal speed and direction). We contribute both a characterization and assessment of sUAS for measuring atmospheric parameters, and identify important challenges and opportunities for improving scientific measurements with sUAS.
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    Wind Dispersal of Natural and Biomimetic Maple Samaras
    Nave, Gary K.; Hall, Nathaniel; Somers, Katrina; Davis, Brock; Gruszewski, Hope A.; Powers, Craig W.; Collver, Michael; Schmale, David G. III; Ross, Shane D. (MDPI, 2021-03-29)
    Maple trees (genus Acer) accomplish the task of distributing objects to a wide area by producing seeds, known as samaras, which are carried by the wind as they autorotate and slowly descend to the ground. With the goal of supporting engineering applications, such as gathering environmental data over a broad area, we developed 3D-printed artificial samaras. Here, we compare the behavior of both natural and artificial samaras in both still-air laboratory experiments and wind dispersal experiments in the field. We show that the artificial samaras are able to replicate (within one standard deviation) the behavior of natural samaras in a lab setting. We further use the notion of windage to compare dispersal behavior, and show that the natural samara has the highest mean windage, corresponding to the longest flights during both high wind and low wind experimental trials. This study demonstrated a bioinspired design for the dispersed deployment of sensors and provides a better understanding of wind-dispersal of both natural and artificial samaras.