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Displaying 253-264 of 274 Results

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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).

UAV-based tools in forest environments

  • PI Scott Post

  • Measuring turbulent wind forces in forests to understand the forces on UAVs in flight, with a goal of being able to keep a UAV in position to mm tolerance. 
Undergraduate students’ perceived barriers to research in online education

  • PI Emily Faulconer

    CO-I John Griffith

    CO-I Zachary Dixon

    CO-I Donna Roberts

  • This study explored differences in student interests, perceived benefits, and perceived barriers to undergraduate research across ERAU's distance and residential campuses.
Understanding Factors that Influence Anesthesia Handoffs

  • PI Elizabeth Lazzara

    CO-I Joseph Keebler

  • Communication is an essential aspect of quality patient care in modern medicine, yet mishaps in communication during handoffs (i.e., the transition of a patient between two or more providers) happen frequently. The purpose of this project was to understand the factors that influence handoffs between anesthesia providers and clinicians within the post anesthesia care unit. 
Understanding the Coupled Dynamics of Particles and Wall Turbulence

  • PI Ebenezer Gnanamanickam

  • ​This work focuses on understanding the coupled interactions between large and heavy solid particles, on a particle bed, and a gaseous (air) carrier phase turbulent boundary layer developing over the bed.
Understanding the Coupled Interactions Between Hair-Like Micromechanoreceptors and Wall Turbulence

  • PI Ebenezer Gnanamanickam

  • ​This research focuses on understanding the interactions between turbulent flows and long (high aspect ratio), flexible hair-like microstructures or micropillars inspired by those encountered in nature. Some examples include lateral line sensors in fish, airflow sensors in bats and hair cover of animals such as seals and bats.
Unmanned Aircraft Systems (UAS) Application to Support Aircraft Rescue and Fire Fighting (ARFF)

  • PI Brent Terwilliger

    CO-I David Ison

    CO-I Dennis Vincenzi

    CO-I Dahai Liu

  • This continuing research project features refinement of UAS application methods to support of ARFF responses. Previously, modeling and simulation, in combination with UAS attribute performance models, was implemented to better understand challenges, limitations, and potential benefits of UAS support. However, based on the findings and recommendations of the original inquiry, the research will be expanded to include examination of operator knowledge, skills, and abilities (KSAs), performance rating standards, and appropriate training requirements and delivery approaches.

Usability of Urban Air Mobility: Quantitative and Qualitative Assessments of Usage in Emergency Situations

  • PI Scott Winter

    CO-I Stephen Rice

    CO-I Sean Crouse

  • ​The purpose of these studies is to determine the usability of urban air mobility (UAM) vehicles in the emergency response to natural disasters and the ideal locations for their take-off and landing sites to occur, consistent with the Center's Theme 2. UAM involves aerial vehicles, mostly operated autonomously, which can complete short flights around urban areas, although their applications are expanding to rural operations as well. While initially designed to support advanced transportation mobility, these vehicles could offer numerous advantages in the emergency response to natural disasters. Through a series of four studies with over 2,000 total participants, quantitative and qualitative methods will be used to identify UAM vehicles' usability in response to natural disasters. The studies will examine the types of natural disasters and types of missions where UAM could be considered usable, along with the creation of a valid scale to determine vertiport usability. Interviews will also be conducted to provide qualitative insights to complement the quantitative findings.
Using Interpretable Artificial Intelligence (AI) for Validation of Autonomous Vehicle Decision Making in Simulation

  • PI M. Ilhan Akbas

  • ​Autonomous Vehicle Validation and Verification AV V&V testing produces multi-variate time series data as output, which is evaluated to determine testing coverage.
Using Machine Learning to Improve Forecasting of Deep Convection

  • PI Christopher Hennon

    CO-I Ronny Schroeder

    CO-I Curtis James

    CO-I Abd AlRahman AlMomani

  • We are working to train a neural network to forecast the initiation time, location, and intensity of thunderstorms. These results will support operations during the proposed CONVECT project and could ultimately aid operational forecasting during the North American Monsoon (NAM).
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.

UUV-UAS Operational and Training Shared KSAs

  • PI David Thirtyacre

    CO-I Joseph Cerreta

  • Uncrewed Underwater Vehicles (UAV) and Uncrewed Aircraft Systems (UAS) operate in a similar fashion. However, there are major differences in the environment and control methods. This research investigates the similarities and differences and makes recommendations on effective cross training.