Aviation Commons^™

Artificial Intelligence Decision Support And Pilot Performance, Aarohi Srivastava

Discovery Day - Daytona Beach

The integration of artificial intelligence (AI) into aviation decision support systems (DSS) introduces new opportunities for pilots. While these systems offer considerable benefits, ensuring safe and optimal human-AI interaction requires further research. In the case of student pilots, trust calibration, system transparency, and appropriate reliance are all factors that influence the operational success of an integrated AI system. The systems are designed with the goal of decreasing cognitive workload, increasing situational awareness (SA), and providing data-based recommendations to help the pilot make quick and accurate decisions. This study will evaluate the effects of disclosed vs undisclosed AI accuracy on student …

Human Factors Challenges In Automated Flight Operations, Jorge Ivan Gonzalez Rivera, Zoe Guyette, Emma Hatten, Katie Huynh, Benjamin Marsh

Discovery Day - Daytona Beach

Automation complacency, a critical aviation hazard, is commonly seen amongst flight crews in high-automation commercial flight decks. This issue occurs when over-reliance on automated systems leads to a decline in manual flying expertise and situational awareness, posing a severe risk of loss of control in-flight (LOC-I) and catastrophic accidents. To bridge the safety gap between current operational demands for efficiency and the regulatory requirement for pilot proficiency, this study proposes the Manual Flight Compliance and Monitoring System (MFCMS). This solution integrates engineering and administrative controls to reduce automation-related risks by mandating 15 minutes of manual flight per hour during cruise …

Mob-Air: Sensing Package Development For Maritime Search And Rescue Uav, Rachel Jacobsen, Liam Abraham, Ethan Thomas, Madeline Thomson, Nikolaos Triantafilloy

Discovery Day - Daytona Beach

Man-overboard (MOB) search and rescue (SAR) operations present a persistent maritime challenge, where rapid and reliable detection of a person in the water is critical to mission success. MOB-Air is developing a modular sensing package for an unmanned aerial system (UAS) to enhance SAR missions through autonomous human detection in maritime environments. This capability directly supports Navy maritime operations by improving overboard recovery, reducing search timelines, and enabling persistent aerial monitoring in contested or resource-constrained environments. The system evaluates thermal and visual imaging sensors using a custom horizontal-rail testing frame with a mobile payload. A ROS 2–based software architecture supports …

Assessing Computer Vision Based Conflict Detection In Uas Traffic Monitoring Under Secure Communication Constraints, Fadjimata Issoufou Anaroua

Doctoral Dissertations and Master's Theses

The rapid growth of Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) is creating a new low-altitude airspace ecosystem where drones, air taxis, service suppliers, communication networks, sensors, and ground-based monitoring systems must work together safely. Within this ecosystem, UAS Traffic Management (UTM) is expected to provide a digital framework for coordinating operations beyond traditional air traffic control. However, reliable integration also requires resilient monitoring methods that can detect non-cooperative aircraft, protect communication links, and maintain timely situational awareness under real-world constraints.

This dissertation examines how computer vision can support cooperative monitoring systems such as Remote ID and ADS-B …

Evaluating Uav Visual-Inertial Odometry Trajectory Error And Feature-Level Metrics Over Repetitive Floor Patterns, Anass El Mekkoussi

Doctoral Dissertations and Master's Theses

Visual-Inertial Odometry (VIO) is a widely used state estimation technique for Uncrewed Aerial Vehicle (UAV) navigation in environments where Global Navigation Satellite System (GNSS) signals are unavailable. VIO systems that rely on visual feature tracking are susceptible to performance degradation when operating over surfaces containing repetitive visual textures, where visually similar features can produce ambiguous correspondences that introduce errors into the trajectory estimate. Despite the prevalence of repetitive textures in indoor UAV operating environments such as warehouses, manufacturing facilities, and infrastructure corridors, the specific impact of different repetitive pattern geometries on per-surface VIO accuracy has received limited systematic study, and …

Demonstrating Sysml V2’S Utility With Syside And Syson For Systems Modeling, Quinn Galen

Student Research Symposium (SRS)

This study highlights the practical utility of SysML v2’s kernel language, a formal, text based foundation for consistent, cross tool model definitions, in Model Based Systems Engineering (MBSE), using Air Traffic Management (ATM) as an illustrative example. SysIDE, an open source textual editor, enables rapid model creation with the kernel’s concise syntax, allowing users to define system components and behaviors (e.g., ATM radar or flight path interactions) with real time validation. SysON, a web based graphical tool, complements this by facilitating collaborative visualization of system architectures. Using ATM as an example case, we can showcase how the kernel language enhances …

Ergonomics Of A Pilot Workstation And Aircraft Interactions On A Cessna 172 Nav Iii, Nicole Beaulieu

Student Research Symposium (SRS)

This study analyzes the ergonomic aspects of the Cessna 172 Navigator III, a common flight training aircraft. The research investigated the interactions between pilots and the aircraft, focusing on pilot fatigue, workstation design, anthropometric data, and pilot interactions with controls. The study included surveys, interviews, and anthropometric measurements involving three pilots with varying experience levels, alongside physical measurements of the cockpit and a workstation ergonomic assessment.. Participants reported issues with limited physical space, particularly impactful to the pilot’s posture and ability to manipulate controls. Display visibility and interaction were areas of concern, often requiring pilots to lean in awkward postures. …

Uncertainty Quantification, Propagation & Conjunction Assessment In Orbital Mechanics Using Generalized Polynomial Chaos Expansion & 2-Dimensional Conjunction Plane Analysis Techniques, Monalisa Karim

Mechanical and Aerospace Engineering Theses

Uncertainties, that are inherent to dynamic models, can be associated with state initial conditions, force modelling errors, navigation and actuation errors. In system modelling stochastic differential equations are used to represent dynamic phenomena with uncertainties, for which the solutions are probability density functions of quantities of interest characterizing the realization of the stochastic processes. In Polynomial Chaos Expansion (PCE) propagation, these solutions are represented as weighted sums of multivariate spectral polynomials that are functions of the input random variables. Generalized polynomial chaos expansion (gPC) is an extension to the original homogenous PCE which projects the random solution onto a basis …

Instructional Fidelity In Virtual Flight: Applying A Structured Learning Model For Vr-Based Pilot Training, Lindsay Gouedy, Bryce Jarrell, Mary Fendley, Brandon Wolf

Journal of Aviation/Aerospace Education & Research

As immersive training technologies reshape the future of aviation education, this study explores the impact of integrating Virtual Reality (VR) into a structured instructional model for B-52 pilot training. With the development and implementation of the I-BUFF (Integrated B-52 Unit Flight Familiarization) model, an innovative framework built upon the 4C/ID (Four Component Instructional Design) and SEEV (Salience, Effort, Expectancy, Value) models, this research evaluates whether structured VR environments improve training transfer and accelerate task proficiency for in-air refueling tasks. A sample of 233 pilot trainees was assessed across three groups: traditional training (non-VR unstructured), VR semi-structured, and VR fully structured …

Utilising Video Recordings To Assess Student Pilot Performance: An Exploratory Study During A Simulated Training Flight, Bradley Moncion, Shi Cao, Allison Lynch, Suzanne K. Kearns, Elizabeth Irving, Ewa Niechwiej-Szwedo

Journal of Aviation/Aerospace Education & Research

In ab initio flight training, the quality of the feedback a flight instructor provides their student is essential to their success. While other high-performance and safety-critical industries have incorporated the use of video recordings into training and assessments, the aviation industry generally has not. There are some studies addressing the potential benefits of video recordings in training professional pilots, but there is a lack of research at the ab initio level. In this study, five flight instructors assessed the performance of student pilots conducting a simulated training flight using a 4-point marking scale. The flights instructors were then tasked with …

Evaluation Of Tactile Cueing Embedded In An Aviation Headset On Pilot Altitude Control, Nicholas D. Wilson, Jessica Van Bree, Matthew Cleveland, Sunny Charakuru, Thomas Petros, Richard Ferraro, Kouhyar Tavakolian

Journal of Aviation/Aerospace Education & Research

This study evaluated the effectiveness of tactile cueing integrated into a pilot’s headset on pilot altitude control during simulated instrument conditions. Pilots typically rely on visual and auditory inputs to maintain situational awareness, but in high-workload or instrument meteorological conditions (IMC), these channels can become overloaded. One underutilized alternative for alerting is a tactile cueing apparatus. Using an X-Plane simulation of a Piper Archer equipped with a G-1000 avionics suite, 39 FAA-certified pilots flew two precision approaches. The experimental group (n = 20) received haptic cues via ear seal-embedded tactors when deviating from assigned altitude or glideslope. The control group …

Barriers To Modernizing Aviation Maintenance Technician Education To Meet Emerging Industry Needs, Durwa Chavan

All Theses

Modernizing aviation maintenance education is essential to keep pace with emerging technologies, including electric propulsion systems and advanced avionics. As aircraft systems become more digitized and interconnected, there is a growing demand for qualified technicians who can conduct advanced diagnostics and maintenance. However, training programs have not kept pace with these technological shifts, creating a gap between workforce preparation and industry needs.

Using a qualitative research approach, this study conducted semi-structured interviews with industry professionals, educators, and regulatory personnel to identify gaps in existing training programs and Airman Certification Standards (ACS). This study addresses the disconnect between current aviation maintenance …

A Feasibility Study Into The Usability And Application Of An Unmanned Aerial Vehicle For Aircraft Inspection And Quality Assurance Inspections, Reece P. Bhave

Journal of Aviation Technology and Engineering

The global aviation industry is often characterized as one of the safest modes of transportation in the modern world. With an abundance of quality assurance inspections and checks to determine operations safety, modern-day commercial aircraft that are utilized for passenger and cargo flights are held to a higher safety standard defined by regulatory bodies, such as the Federal Aviation Administration in the United States of America and the European Union Aviation Safety Agency in the European Union. While these quality standards are maintained via a series of inspections, checks, and preventative maintenance procedures, they are limited to only visual or …

A Technical And Statistical Analysis Of Unleaded Aviation Fuel (Ul94) Adoption In A High- Volume Collegiate Aviation Environment, Nicholas D. Wilson, Ryan Guthridge, Brandon Wild, Jeremy Roesler, Daniel Kasowski, Nick Geinert, Aaron Terbest, Aaron Fettig, Robert Kraus

Journal of Aviation Technology and Engineering

The University of North Dakota (UND) adopted unleaded aviation fuel (UL94) for approximately a four-month period in the summer and early fall of 2023. The UL94 fuel was used in all reciprocating engine fleets based at the university’s primary training airport, Grand Forks International Airport in North Dakota. During the operational implementation of UL94, the UND flew 46,600 flight hours, consuming 386,778 gallons of fuel across all fleets powered by Lycoming engines. After approximately two months of using UL94, operational reports and maintenance inspections began to indicate potential for exhaust valve seat recession (EVSR), although early indications were limited in …

Köppen-Geiger Climate Effects On F-15 Readiness Spares Package Parts, Maximus A. Fan

Theses and Dissertations

Readiness Spares Packages (RSP) are critical to deployed operations. Future demands of the Air Force require squadrons to operate in different climate environments from home stations. RSPs can sustain aircraft maintenance operations for up to 30 days. Currently, failure rates of parts within the RSP are assumed to be constant. This research aims to explore whether there is a difference in F-15 RSP failure rates when Koeppen climate classifications are taken into effect. The Koeppen-Geiger system classifies area climates based on the geography, elevation, and location. The history of operations and diversity of F-15 locations make the aircraft an ideal …

From Tarmac To Timetable: A Data-Driven Study Of Airline Delay Performance In Nigeria, Kelechi V. Iwuagwu

Dissertations, Theses, and Capstone Projects

This capstone project investigates the patterns, causes, and impacts of flight delays in the Nigerian aviation sector from January 2024 to January 2025. Utilizing a dataset containing flight details—including scheduled and actual departure/arrival times, routes, and airline information—the study employs advanced data analytics and visualization techniques to uncover critical insights. The research highlights discrepancies between scheduled and actual flight performance, identifies delay patterns across airlines and timeframes, and explores the ripple effects of delays on subsequent flights.

Furthermore, Nigerian passengers frequently express frustrations over flight delays, cancellations, and poor communication from airlines, yet no publicly available data systematically documents these …

An Msbe–Driven Advanced Air Mobility Post–Disaster Response System, Olabode A. Olanipekun

Graduate Theses and Dissertations (2019 - present)

In this work, an overarching conceptual design model towards the realization of a proposed Advanced Air Mobility Post–Disaster Response System (AAMPDR system) was explored through the focal lenses of systems thinking (ST), socio–technical systems (STS) and model–based systems engineering (MBSE) paradigms. Initially aimed at providing intervention for casualties and aerial support to emergency rescue workers on the ground in the event of a hurricane disaster around the Gulf shore of the Mobile bay area, Mobile city, AL., the scope of this research subsequently expanded to include a global outlook. Thereafter, culminating in the development of a generalized AAMPDR system model …

Machine Learning Techniques To Detect Anomalies In T-38 Flight Sensor Data, Sydney M. Wekamp

Theses and Dissertations

Accurate sensors are critical for ensuring the safety of aircrew. However, detecting faulty sensors remains a significant challenge for the Test Pilot School at Edwards Air Force Base in California. Current methods rely on either student pilots identifying anomalies or waiting for sensors to fail completely before repairs are made—an approach that lacks reliability and consistency. This research aims to address these shortcomings by implementing machine learning techniques to detect sensor faults proactively. To date, applying machine learning to a dataset of this size, encompassing numerous sensors on the same aircraft, is unprecedented. The project focuses on establishing strong baseline …

Evaluating Weather Effects On Sortie Generation Using Discrete Event Simulation, Markus Case

Theses and Dissertations

United States Air Force (USAF) operations rely on sortie generation, a complex system involving aircraft maintenance, operational planning, munitions, security forces, and aircrew. Failures in any of these areas can jeopardize a mission, and extreme weather events such as lightning, high winds, and snow further complicate operations. This thesis examines the impact of extreme weather on sortie generation, focusing on developing a data-driven discrete-event simulation (DES) to predict generation timelines and identify high-risk areas. The model allows users to adjust key inputs, including the month, number of aircraft, processing times, and personnel/equipment availability. By simulating real-world conditions, the model helps …

Understanding Avionics Maintenance Training Student Outcomes In A Student-Centered Active Learning Environment, Scott M. Wyman

Theses and Dissertations

This study examines the effects of active learning compared to didactic methodologies on two soft skills, namely teamwork and self-efficacy using regression analyses and connected letter reports. Learning styles and personality traits were used as predictors. Findings indicate significant interaction effects between methodology, aural learning style, and personality traits on self-efficacy and teamwork ability. The findings highlight the nuanced role of learner traits in shaping teamwork outcomes across instructional methods. While active learning supports soft skills, individual differences must be considered in instructional design to optimize teamwork in technical education settings.

Machine Learning With Flight Data Recorder Data For Flight Fuel Consumption Predictions, Adam C. Levandowski

Theses and Dissertations

This study applies advanced Machine Learning (ML) to Flight Data Recorder (FDR) data for fuel consumption predictions. It explores feature engineering, model selection, and Hyper-Parameter Optimization (HPO) across all flight phases. Baseline models like Ordinary Least Squares (OLS) regression, Multi- Layer Perceptrons (MLPs), and decision trees are compared to Deep Neural Networks (DNNs), Recurrent Neural Networks (RNNs) with Gated Recurrent Unit (GRU) layers, and XGBoost. Results analyze segmentation strategies, tailored features, and model performance. A counterfactual analysis compares ML models to operational fuel predictions, demonstrating their deployment potential. Findings establish a foundation for future ML-driven advancements in aviation fuel optimization.

Reinforcement Learning For Aeromedical Evacuation In Nonstationary Combat Environments, Micah J. Kartchner

Theses and Dissertations

This research formulates the medical evacuation (MEDEVAC) dispatching problem as a sequential decision process and investigates the application of reinforcement learning under nonstationary conditions. We model the dynamic arrival rate of MEDEVAC requests using a nonstationary Hawkes process and design a Double Deep Q-Network algorithm that incorporates belief states to anticipate future requests. Through computational experimentation, we analyze the impact of belief formulation on decision quality and system performance. Results indicate that policies incorporating belief states significantly outperform myopic dispatching policies, reducing urgent casualty wait times by up to 49.68% and increasing on-time evacuations by up to 21.91%.

Symbology Detection And Numerical Recognition For T-38 Heads-Up Display Recordings, Ben T. Hepner

Theses and Dissertations

The extraction of symbology and numerical data from the T-38 Heads-Up Display (HUD) enhances post-flight analysis and supports real-time decision-making. This research develops a deep learning pipeline using YOLO-based object detection and Optical Character Recognition (OCR) to analyze HUD video data. Model evaluations showed mAP0.5:0.95 ranging from 0.422 (YOLOv11m, hard test set) to 0.696 (YOLOv8m, medium test set), demonstrating robust symbology detection. Numeric detection performed well (mAP_0.5:0.95 = 0.764), but OCR struggled with glare and resolution limitations, achieving a recognition accuracy of 17.35%. These results validate deep learning for HUD data extraction but highlight the need for improved robustness …

Proximal Policy Optimization Applied To The Beyond Visual Range Air Combat Maneuvering Problem, Daniel B. Joseph

Theses and Dissertations

Artificial intelligence (AI) grows ever-more important in warfighting. Emerging technologies allow for the use of AI to control aircraft and weapons systems. This research investigates the application of reinforcement learning (RL) through the Proximal Policy Optimization (PPO) algorithm to a two-versus-two (2v2) beyond-visual-range (BVR) air combat maneuvering problem (ACMP). Implemented in the Advanced Framework for Simulation, Integration, and Modeling (AFSIM), the methodology frames the engagement as a Markov decision process, wherein an autonomous RL agent learns continuous control decisions—throttle, pitch, roll, and yaw—under a cooperative communication scheme. A multi-phase curriculum-learning approach facilitates the progressive acquisition of flight stability, weapon deployment, …

Learning To Dogfight: Proximal Policy Optimization Vs. Double Deep Q Network For 2v2 Air Combat With Directed Energy Weapons In Afsim, Caden W. Wilson

Theses and Dissertations

This research utilizes reinforcement learning (RL) to train two blue agents each imbued with a directed energy weapon (DEW) in a 2v2 within visual range air combat maneuvering problem. A phased solution approach is employed to repeatedly tune and train several RL algorithm implementations: Proximal Policy Optimization (PPO) and Double Deep Q Network (DDQN). Phase I of training includes reward shaping for basic flight elements such as altitude, airspeed, and target proximity. Phase II of training builds off policies developed in Phase I, but rewards emphasize winning the aerial engagement by any means necessary. DDQN significantly outperforms PPO in Phase …

Designing An Interactive Application To Prevent Runway Incursion: A Systems Engineering Approach, Yixuan Cheng, Dahai Liu, Dennis Vincenzi, Donald S. Metscher

Journal of Aviation Technology and Engineering

Runway incursion is a leading cause of serious incidents and accidents at airports. A common cause of runway incursions is unfamiliarity with the airport layout. To address this, we designed an electronically interactive application intended as a practice tool for pilots during flight preparation. The aim of this application is to improve pilots’ familiarity with airports, ultimately helping to reduce runway incursions, with the goals of being interactive, affordable, easily accessible, and designed for use on mobile devices. We applied a systems engineering approach that adheres to human factors engineering principles to ensure user-friendly design and optimization of the interaction …

Quantifying The Transfer Effectiveness Of An Artificial Intelligence-Based Simulator Pre-Training Program For Student Pilots, Ryan Guthridge

Journal of Aviation/Aerospace Education & Research

Since the airline pilot shortage was initially studied in 2016, the pilot hiring model has been significantly impacted, with airlines hiring qualified pilots at unprecedented rates. The COVID-19 pandemic has slowed this hiring rate, however it is expected that airline hiring will soon increase to a rate higher than initially expected (Bureau of Transportation Statistics, 2022). With this dynamic, certified flight instructors are often the most qualified recruits for airlines, due to the number of hours and experience they have gained in the flight training organization. In turn, certified flight instructors are in short supply for flight training organizations worldwide. …

Empowering Precision Forecasting: Self-Supervised Lstm For Hourly Pressure And Temperature Prediction, Anand Shankar, Deepak K. Singh, Mantosh Kumar, Pankaj Kumar, Pradhan Parth Sarthi

Journal of Aviation/Aerospace Education & Research

The most important parts of any flight are landing and takeoff, and an aircraft's takeoff configuration must balance the regulated takeoff weight, runway length, and weather conditions to ensure a safe departure and arrival. In addition to runway length, wind, temperature, pressure, and visibility determine the total allowed takeoff weight and the economic viability of any trip. Thus, any meteorological office involved in flight planning and operation at any airport must accurately assess these factors, known as takeoff data. This research paper suggests multivariate self-supervised LSTM-based models to accurately predict the temperature and pressure (MSLP) of the takeoff data. The …

The State Of Uas Operations At Airports, A Perspective From Airport Managers, Damon Lercel, Sarah M. Hubbard

Journal of Aviation/Aerospace Education & Research

As the number of Uncrewed Aircraft Systems (UAS) operating in our National Airspace System (NAS) increases, so do UAS operations near or at an airport. The accelerating technology in Advanced Air Mobility (AAM) and related business opportunities will only further increase UAS operations at airports. This continued growth in new UAS technologies and applications introduces new hazards and risks to the airport environment. This proliferation of UAS highlights the importance of airports developing a robust Safety Management System (SMS) that includes specific UAS risk mitigations. There is currently little empirical data regarding UAS traffic around airports and there is no …

An Operational Field Study: A Comparison Of Piloting Uncrewed Underwater Vehicles And Uncrewed Aircraft Systems, David Thirtyacre, Joseph Cerreta, Pete Miller, Kimberly Luthi, Jolee Thirtyacre

Publications

and operations, the ability to cross-train personnel in both Uncrewed Underwater Vehicles and Small Uncrewed Aircraft System operations has become a focal point for efficiency and workforce optimization. This study presents a comparative analysis of the operational and human factor considerations involved in piloting mini UUV and sUASs, highlighting the key similarities and differences in control methods, environmental influences, navigation, emergency procedures, and situational awareness. A qualitative experimental field study was conducted between July 2024 and October 2024, involving real-world deployments of both systems in maritime and aerial environments. Findings indicated that while UUV and sUAS operators relied on remote …