1-10 of 21 results
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Fusing Satellite and Drone Data with GIS to Create New Analytical Decision Support Tools for Varying Farm Types
PI Kevin Adkins
PI Nickolas Macchiarella
CO-I Ronny Schroeder
CO-I University of Michigan School for Environment and Sustainability (SEAS) and the Department of Ecology and Evolutionary Biology
The synergy between moderate resolution satellite imagery and fine resolution drone imagery, LiDAR data, and meteorological data, along with generally available GIS data, must be identified and optimized. These data will be integrated to produce a variety of products that help identify what tools, inputs, and management strategies most effectively contribute to an increase in the productivity and resilience of an important agricultural system to a major weather or climate related disturbance.
Read moreCategories: Faculty-Staff
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GUMP: General Urban Area Microclimate Predictions Tool
PI Kevin Adkins
CO-I Nickolas Macchiarella
CO-I National Aeronautics and Space Administration NASA
Hyperlocal weather predictions are often necessary in order to determine whether a particular sUAS route will be safe to fly. The General Urban area Microclimate Predictions tool (GUMP) seeks to provide such predictions through the use of machine learning (ML) models and computational fluid dynamics (CFD) simulations. The computed wind flow field is converted into an intuitive risk map for sUAS operators through the use of appropriate thresholds on wind velocities.
Read moreCategories: Faculty-Staff
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Evaluating Preflight Weather Briefing Strategies
PI Elizabeth Blickensderfer
CO-I Thomas Guinn
CO-I Robert Thomas
The objective of this grant is to examine General Aviation (GA) pilots’ capability to conduct Preflight Weather self-briefings as compared to using Flight Services to obtain weather briefings. Previous research indicates that GA pilots are increasingly conducting weather self-briefings during preflight (Duke et al., 2019). Additional research indicates that GA pilots have moderately low performance when interpreting aviation weather observation and forecast products (Blickensderfer et al., 2019). Research is needed to assess and understand the attitudes, knowledge, and performance of GA pilots conducting self-briefings to identify possible gaps and, in turn, provide recommendations for future system design and pilot training.
Read moreCategories: Faculty-Staff
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Using Virtual Reality to Identify Cybersecurity Threats for Navy Midshipmen
PI Andrew Dattel
CO-I Omar Ochoa
CO-I Daniel Friedenzohn
CO-I Trevor Goodwin
CO-I Harry Brodeen
This research is investigating the training of U.S. Navy Midshipman enrolled in the Reserve Officer Training Corps (ROTC) at Embry-Riddle Aeronautical University (ERAU) to identify cyber and security threats in a simulated bridge of a Navy vessel. Midshipmen will receive classroom instruction, as well as training in a virtual reality bridge simulator. The knowledge and skills training the midshipmen received is intended to transfer to the applications of midshipmen’s future positions and careers.
Read moreCategories: Faculty-Staff
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UAS Parameters, Exceedances, Recording Rates for ASIAS
PI David Esser
The project was to support aggregation of UAS flight data with commercial, general aviation and surveillance data, to develop enhanced safety analyses for NAS stakeholders, support UAS integration in the NAS, and support the Unmanned Aircraft Safety Team (UAST).
Read moreCategories: Faculty-Staff
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UAS Flight Data Research in Support of ASIAS (Aviation Safety Information and Analysis Sharing)
PI David Esser
This research will aggregate high quality UAS flight data with commercial and general aviation flight data and surveillance data, in order to develop enhanced safety analyses for NAS stakeholders and to support UAS integration in the NAS.
Read moreCategories: Faculty-Staff
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Workplace Accident Survey
PI Mark Friend
Random employees of unspecified companies will be interviewed to ID cause(s) of accidents in which they were involved. The goal is to determine if they could have been prevented by adjustments to the overall sysem.
Read moreCategories: Faculty-Staff
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Implementing Active Learning Techniques in an Undergraduate Aviation Meteorology Course
PI Daniel Halperin
PI Joseph Keebler
CO-I Robert Eicher
CO-I Thomas Guinn
CO-I Kim Chambers
Student feedback from end-of-course evaluations repeatedly indicated a desire to change the format of the course by de-emphasizing the PowerPoint-based lectures. The goal of the present study was to determine whether including a set of new active-learning techniques in an Aviation Weather course would result in better student understanding (as measured by exam scores) and make the course more engaging (as measured by end-of-course evaluations). During 2018-19, three instructors implemented five different active-learning techniques into their classes (i.e., the experimental group), while two instructors continued to use the unrevised course materials (i.e., the control group). The new active-learning techniques, described below, included daily quizzes, polling questions, flipped classroom sessions, in-class activities, and assertion-evidence-based lectures. All sections used the same assignments and exams, allowing for direct assessment of the effectiveness of the active-learning techniques. Analyses of Variance (ANOVA) tables were used to determine the statistical significance of the differences in exam scores. Indirect assessments in the form of end-of-course evaluations were also examined.
Read moreCategories: Faculty-Staff
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Adding Tropical Cyclone Verification Capabilities to the Model Evaluation Tools – Tropical Cyclone (MET-TC) Software
PI Daniel Halperin
Producing reliable tropical cyclone (TC) genesis forecasts is an operational priority. The National Hurricane Center uses several TC genesis guidance products for their Tropical Weather Outlook. Furthermore, global model output is used in many TC genesis guidance products and is considered an important source of deterministic TC genesis forecast guidance. This project creates a standard framework for verifying deterministic and probabilistic TC genesis forecasts using the TC-Gen tool in the Model Evaluation Tools software package.
Read moreCategories: Faculty-Staff
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PLD Space Suborbital Microgravity Research
PI Pedro LLanos
This project involves the design, development, integration, testing, validation, and verification of various payloads to be flown aboard PLD Space’s MIURA-1 suborbital rocket.
1. Magnetic Active Propellant Management Device (MAPMD) experiment (student involvement)2. In-vitro experiment comprised of both T-cells and Cancer cells3. Cerebrospinal fluid (CSF) shunt experiment (student involvement)4. Environment characterization of the suborbital vehicle experiment (student involvement)
Read moreCategories: Faculty-Staff
1-10 of 21 results