Displaying 193-204 of 287 Results

O

Organizational Design of Secondary Aviation/Aerospace/Engineering Career Education Programs
  • PI Susan Archer

    CO-I David Esser

  • Modern nations operate within a global economy, relying heavily on the aviation industry for efficient and effective transportation of passengers and goods. The Boeing 2018 Pilot and Technical Outlook Report indicated that over the next 20 years, the aviation industry will need almost two and a half million new aircrew and maintenance employees to meet anticipated global demand. The industry will also need engineers, aviation managers, and workers in other aviation and aerospace disciplines. Aviation and aerospace jobs require solid backgrounds in mathematics, science, and technology; the development of pre-college aviation / aerospace / engineering career education programs would presumably enhance student preparation in these areas and increase the workforce pipeline for the industry. The goal of this study was to identify and evaluate the underlying organizational factors of successful secondary aviation / aerospace / engineering career education programs, through application of measures traditionally associated with organizational theory.

P

Pilot Acceptance of Personal, Wearable Fatigue Monitoring Technology: An Application of the Extended Technology Acceptance Model
  • PI Rachelle Strong

    CO-I Dahai Liu

  • The research problem of pilot fatigue has been referenced as a causal factor for aircraft accidents in many United States National Transportation and Safety Board (NTSB) accident reports; however, the United States Code of Federal Regulations 14 CFR Part 117, Flight and Duty Limitations and Rest Requirements for Flight Crew Members, does not provide a tangible means of measuring fatigue for aircraft crew members. This problem is relevant to the airline industry and the travelling public because pilot fatigue is preventable as a causal factor in aviation accidents, and pilots need an accurate way to measure it. Adoption of a technology-based solution has been recommended by the NTSB.

Pilot Awareness of Current and LED Elevated Runway Guard Lighting
  • PI John French

  • Since airports require efficient use of limited funding, thus reducing annual operations costs is an important concern. A potentially dramatic way to reduce the cost associated with airport operations is to replace current incandescent lighting with light-emitting diode (LED) lights.

Pilot Response to Cybersecurity Events
  • ​The first research uses the pilot cybersecurity event and risk assessment station located in the Cybersecurity Engineering Lab (LB 131).
Pilot’s Willingness to Operate in Unmanned Aircraft System Integrated Airspace
  • PI Lakshmi Vempati

    PI Scott Winter

  • The interest in Unmanned Aircraft Systems (UAS) use for private, civil, and commercial purposes such as package delivery, inspection, surveillance, and passenger and cargo transport has gained considerable momentum. As UAS infiltrate the National Airspace System (NAS), there is a need to not only develop viable, safe, and secure solutions for the co-existence of manned and unmanned aircraft, but also determine public acceptance and pilot’s willingness to operate an aircraft in such an integrated environment. Currently there is little or no research on pilot’s perceptions on their willingness to operate an aircraft in UAS integrated airspace and airports.

Pilot-in-the-Loop UAS Mobile Research Test-Bed
  • PI Hever Moncayo

    CO-I May Chan

    CO-I Ashwini Agrawal

    CO-I Agustin Giovagnoli

  • This project aims to develop and implement a Mobile UAV Ground Control Station (GCS) supporting aviation safety research with pilot-in-the-loop capabilities using unmanned aerial systems platforms, in which flight conditions, such as systems failures, could be simulated in real-time to characterize pilot response, control laws performance, and human-machine and control laws interactions.
Platform for Investigating Concept Networks on the Instrumentality of Knowledge (PICNIK)
  • PI Matthew Verleger

  • This engineering education research project seeks to develop a concept network for engineering and a platform for helping students identify how concepts are connected across a curriculum.  The goal is to better understand and improve how students value the concepts being taught throughout their education.

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 cells 
    3. Cerebrospinal fluid (CSF) shunt experiment (student involvement) 
    4. Environment characterization of the suborbital vehicle experiment (student involvement)
PolyVerif: Open-Source Environment for Autonomous Vehicle Validation and Verification
  • PI M. Ilhan Akbas

  • ​Validation and Verification (V&V) of Artificial Intelligence (AI) based cyber physical systems such as Autonomous Vehicles (AVs) is currently a vexing and unsolved problem.
Porous Media
  • PI Harihar Khanal

    CO-I Ciprian Mancas

  • This project will build a mathematical and computational model for investigating growth and transport of micro-organisms in unsaturated soil described by the nonlinear Richards' equation with source terms. These source terms contribute to change the saturation function, or the microbial population density, in addition to the nonlinear diffusion.
Predicting General Aviation Accidents Using Machine Learning Algorithms
  • PI Bradley Baugh

    CO-I Bruce Conway

  • Aviation safety management is implemented through reactive, proactive, and predictive methodologies. Unlike reactive and proactive safety, predictive safety can predict the next accident and enable prevention before an actual occurrence. The study outlined here promotes predictive safety management through machine learning technologies using large amounts of data to facilitate predictive modeling.

Predicting Pilot Misperception of Runway Excursion Risk Through Machine Learning Algorithms of Recorded Flight Data
  • PI Edwin Odisho

    CO-I Dothang Truong

  • The research used predictive models to determine pilot misperception of runway excursion risk associated with unstable approaches. The Federal Aviation Administration defined runway excursion as a veer-off or overrun of the runway surface. The Federal Aviation Administration also defined a stable approach as an aircraft meeting the following criteria: (a) on target approach airspeed, (b) correct attitude, (c) landing configuration, (d) nominal descent angle/rate, and (e) on a straight flight path to the runway touchdown zone. Continuing an unstable approach to landing was defined as Unstable Approach Risk Misperception in this research. A review of the literature revealed that an unstable approach followed by the failure to execute a rejected landing was a common contributing factor in runway excursions.