1-10 of 14 results
-
Development of a Safety Performance Decision-Making Tool for Flight Training Organization
PI Marisa Aguiar
CO-I Carolina Anderson
Title 14 of the Code of Federal Regulations (CFR) Part 141 flight training organizations are actively pursuing ways to increase operational safety by introducing advanced risk assessment and decision-making techniques. The purpose of the dissertation was to create and validate a safety performance decision-making tool to transform a reactive safety model into a predictive, safety performance decision-making tool, specific to large, collegiate Title 14 CFR Part 141 flight training organizations, to increase safety and aid in operational decision-making. The validated safety decision-making tool uses what-if scenarios to assess how changes to the controllable input variables impact the overall level of operational risk within an organization’s flight department.
Read moreCategories: Graduate
-
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.
Read moreCategories: Graduate
-
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.
Read moreCategories: Graduate
-
Examining Unstable Approach Predictors Using Flight Data Monitoring Information
PI David Carroll
CO-I David Esser
The approach and landing phase of flight is statistically the most dangerous part of flying. While it only accounts for 4% of flight time, it represents 49% of commercial jet mishaps. One key to mitigating the risks involved in this flight segment is the stabilized approach. A stabilized approach requires meeting rigorous standards for many flight parameters as the aircraft nears landing. Exceeding any of these parameters results in an unstable approach (UA). The energy management (EM) accomplished by the flight crew, represented by the EM variables in the study, influences the execution of a stabilized approach.
Read moreCategories: Graduate
-
Cost Optimization Modeling for Airport Capacity Expansion Problems in Metropolitan Areas
PI Woo Jin Choi
CO-I Dothang Truong
The purpose of this research was to develop a cost optimization model to identify an optimal solution to expand airport capacity in metropolitan areas in consideration of demand uncertainties. The study first analyzed four airport capacity expansion cases from different regions of the world to identify possible solutions to expand airport capacity and key cost functions which are highly related to airport capacity problems. Using mixedinteger nonlinear programming (MINLP), a deterministic optimization model was developed with the inclusion of six cost functions: capital cost, operation cost, delay cost, noise cost, operation readiness, and airport transfer (ORAT) cost, and passenger access cost. These six cost functions can be used to consider a possible trade-off between airport capacity and congestion and address multiple stakeholders’ cost concerns.
Read moreCategories: Graduate
-
Student Engagement in Aviation MOOCs: Identifying Subgroups and Their Differences
PI Jennifer Edwards
CO-I Mark Friend
The purpose of this study was to expand the current understanding of learner engagement in aviation-related Massive Open Online Courses (MOOCs) through cluster analysis.
Read moreCategories: Graduate
-
An Exploratory Study of General Aviation Visual to Instrument Meteorological Condition Contextual Factors
PI James Hartman
CO-I Mark Friend
The purpose of this dissertation was to bridge the existing literature gap of outdated contextual factor (CF) research through examination and determination of current General Aviation (GA) Title 14 Code of Federal Regulations (CFR) Part 91 visual flight rules (VFR)-into-instrument meteorological condition (IMC) contextual factors. Contextual factors are a multifaceted arrangement of pertinent events or occurrences contributing to pilot accidents in weather-related decision-making errors.
Read moreCategories: Graduate
-
An Investigation of Factors that Influence Passengers’ Intentions to Use Biometric Technologies at Airports
PI Kabir Kasim
CO-I Scott Winter
This research investigated the factors that influence passengers’ intentions to choose the use of biometrics over other methods of identification. The current study utilized a quantitative research method via an online survey of 689 persons from Amazon ® Mechanical Turk ® (MTurk) and employed structural equation modeling (SEM) techniques for data analysis. The study utilized the theory of planned behavior (TPB) as the grounded theory, while perceived usefulness and perceived ease of use were included as additional factors that could influence individuals’ intentions to use new technology.
Read moreCategories: Graduate
-
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.
Read moreCategories: Graduate
-
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.
Read moreCategories: Graduate
1-10 of 14 results