Aviation Commons^™

Color-Coding: An Aid Or Hindrance In A Multi-Unmanned Aerial Vehicle Supervisory Control Task, Austin Daniel Wood

Theses and Dissertations

The purpose of the current study was to investigate the effect of coding types (i.e., alphanumeric coding, color-coding, and redundant color + alphanumeric coding) for vehicle identification and status information on pilots’ recognition performance, situational awareness (SA), and workload for a multi-vehicle operations ground control station (GCS) supervisory control task. With the aviation industry's push towards operators supervising and controlling multiple vehicles, it is pertinent to identify design features that support the capabilities and limitations of human operators. The current study employed a within-subjects, repeated-measures experimental design, in which a sample of 33 students with aviation experience performed three trials, …

Helicopter Pilots’ Safety Behaviors: Identifying Factors That Affect Risk Perception Among Helicopter Pilots, Khaled J. Alzaabi

Theses and Dissertations

Helicopter operations frequently take place in complex, high-risk environments, where pilots continuously assess hazards and make critical decisions under pressure. Despite standardized procedures, regulations, and training designed to enhance safe operations, helicopter pilots may perceive risk differently when encountering similar flight situations. Understanding the factors that influence helicopter pilots’ perception of risk is essential for improving helicopter operation safety.

The purpose of this study was to investigate the effect of various factors on risk perception among helicopter pilots. Using an explanatory correlational design, the study assessed whether helicopter pilots’ demographics, flight experience, and affective domain factors explain differences in their …

Examining The Relationship Between Title 14 Code Of Federal Regulations (Cfr) Part 147 Maintenance School Aviation Maintenance Technician (Amt) Instructor Experience And Instructor Pass Rates For Airmen Certification Standards (Acs) Element Subject Areas, Richard Lyman Johnson

Theses and Dissertations

This quantitative, correlational study examined the relationship between Aviation Maintenance Technician (AMT) instructor experience and student pass rates in 14 CFR Part 147 maintenance schools. Data were collected from February to August 2025 using purposive and snowball sampling, which yielded 67 complete responses. Instructor experience, measured in months of A&P-rated maintenance work prior to teaching, ranged from 1 to 684 months (M = 253.54, SD = 197.97). Student pass rates, defined as the proportion of students passing ACS element subject area courses, ranged from .52 to 1.00 (M = .95, SD = .07). Most instructors were male, White, over 50 …

Impacts Of Climate Disruption On Mobility Aircraft Performance In The Pacaf Region, Hannah M. Dauterman

Theses and Dissertations

This thesis investigates the projected impacts of climate disruption on the performance and fuel management of the C-17 Globemaster III, a critical mobility aircraft in the Pacific Air Forces (PACAF) region. As rising global temperatures reduce air density, the performance of aircraft is compromised, resulting in increased fuel consumption, as well as the potential for extended runway requirements and diminished cargo capacity. Using climate projection data from Coupled Model Intercomparison Project Phase 6 (CMIP6), this research analyzes future air temperature trends and their implications for C-17 fuel consumption. Results suggest that by 2049, the U.S. Air Force may incur an …

Designing The Protocol For An Experimental Flight Simulation Study Encouraging Fuel Efficient Behavior, Thomas S. Reardon

Theses and Dissertations

This study designed and tested an experimental instrument to examine how pilots respond to fuel efficiency feedback in a flight simulator. A standardized flight plan, script, and hardware setup were created using X-Plane 12 software and physical flight simulator hardware. The chosen sortie guided participants from Monterey Regional Airport to Moffett Federal Airfield using instrument flight rules (IFR). The flight script provided step-by-step guidance to ensure consistent behavior across participants. The simulator was mapped to match real cockpit controls and allowed for precise data collection including flight time, altitude, heading, and fuel use. The goal was to support a larger …

Designing An Experiment To Create And Evaluate Behavioral Changes In Air Force Pilots' Fuel Efficiency, Jackson Macias

Theses and Dissertations

Fuel represents over 70% of the logistical resupply demand within the Department of Defense, with the United States Air Force accounting for most of that consumption. While prior fuel efficiency efforts have primarily focused on technical upgrades, this research explores how behavioral interventions can influence pilot decision-making and operational energy outcomes. Using the Theory of Planned Behavior (TPB) as a guiding framework, this study investigates the effects of targeted behavioral strategies on pilots’ attitudes, subjective norms, perceived behavioral control, intentions, and actual fuel-efficient behaviors. A quasi-experimental design was applied through a controlled pilot study using simulator flights. Six participants were …

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 …

Palindrome: A Bi-Directional Multi-Object Detection Framework For Relative Navigation And Autonomous Docking, Liam A. Weinfurtner

Theses and Dissertations

This work introduces a bi-directional, multi-object detection framework that integrates pose estimates from both receiver- and tanker-mounted cameras to improve accuracy and redundancy. A modular YOLO-based detection pipeline is trained using synthetic and real imagery, leveraging a bootstrap transfer learning approach to enhance sim-to-real performance. System evaluation in both virtual and real-world environments demonstrates improved detection robustness, pose estimation accuracy, and scalability. These advancements contribute to the development of AI-driven vision systems for AAR and other autonomous docking applications.

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%.

Enhancing Reliability Of A 3d Cargo Scanning System, Gabriel F. Bartolomei

Theses and Dissertations

Recent advancements in 3D cargo scanning and machine learning offer solutions to improve cargo processing reliability. This study enhances a 3D cargo scanning system by addressing software crashes, connectivity failures, and image accuracy issues limiting its operational effectiveness. A systematic approach identified the primary causes of system failures. System updates were implemented, followed by 30 pre- and post-update trials to evaluate reliability improvements. Statistical t-tests showed a significant reduction in failures, although processing time slightly increased. Results indicated that targeted hardware and software updates enhanced cargo scanning efficiency and dependability. Future work will focus on refining sensor calibration, optimizing network …

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 …

Training-Informed Air Traffic Control Workforce Scheduling, Eli Winett

Theses and Dissertations

The Radar Control Facility (RCF) at Eglin Air Force Base creates monthly workforce schedules. Adherence to regulations must be verified manually and no evaluation criteria exist to compare schedules. A mixed-integer program model for air traffic controllers allocates workers across 19 positions for a user-defined number of weeks of 24-hour operations. Across eight consecutive months, this model produced schedules to nearly eliminate all shifts with critical shortages from the reference schedules. Without civilian overtime work, gains in positional coverage require a 35% increase in overtime work for military workers and 35% reduction in monthly training instances. We recommend users adopt …

Evaluating The Influence Of Evtol Pilot Interface Visual Density And Information Density On Pilot Situation Awareness, Workload, And Search Performance, Bhoomin Bhupendrabhai Chauhan

Theses and Dissertations

The purpose of the current study was to investigate the influence of levels of visual density (VD) and information density (ID) of an electrical vertical take-off and landing (eVTOL) aircraft pilot interface on pilot situation awareness (SA), workload, and search performance. An eVTOL aircraft is a novel aircraft design that is able to perform vertical take-off and landing similar to a rotorcraft and transition to a forward flight, similar to a fixed-wing aircraft. These aircraft are envisioned to operate in urban environments at lower altitudes, necessitating efficient, clear, and concise pilot interfaces to ensure safety and operational effectiveness. The study …

The Effect Of Weather On Atc Complexity And Traffic Volume In Washington Air Route Traffic Control Center (Zdc) High Sectors, Amber Mccraw

Theses and Dissertations

The purpose of this study was to investigate the effect of weather on ATC complexity and traffic volume in ZDC high sectors in clear vs. convective weather using the AS&T Complexity Tool. This relationship was examined from a combined sector and individual sector perspective using both raw data and daily means for ATC complexity and traffic volume. This study employed an ex post facto effects-type design that used flight trajectory data from the FAA’s System-Wide Information Management (SWIM) Flight Data Publication Service (SFDPS) and weather data from NOAA spanning the year of 2019.

The primary analysis involved raw ATC complexity …

An Investigation Into In-Flight Loss Of Control Accidents Due To Horizontal Stabilizer Changes On The Piper Cherokee, Connor John Geran

Theses and Dissertations

Loss of Control (LOC) while in-flight in General Aviation (GA) has been the subject of intense research by academic institutions and regulatory agencies in recent years [4] [9] [11] [19] [20] [21]. This interest is primarily due to a disproportionate number of all aircraft accidents occurring within the GA category of flight, with 94% of accidents in 2022 occurring within GA, caused primarily by pilot LOC, with 42% of accidents having LOC as the listed cause. Research into this subject at FIT yielded the results that many common GA aircraft tend to experience a strong pitch up response after undergoing …

Representation Learning For Generative Models With Applications To Healthcare, Astronautics, And Aviation, Van Minh Nguyen

Theses and Dissertations

This dissertation explores applications of representation learning and generative models to challenges in healthcare, astronautics, and aviation.

The first part investigates the use of Generative Adversarial Networks (GANs) to synthesize realistic electronic health record (EHR) data. An initial attempt at training a GAN on the MIMIC-IV dataset encountered stability and convergence issues, motivating a deeper study of 1-Lipschitz regularization techniques for Auxiliary Classifier GANs (AC-GANs). An extensive ablation study on the CIFAR-10 dataset found that Spectral Normalization is key for AC-GAN stability and performance, while Weight Clipping fails to converge without Spectral Normalization. Analysis of the training dynamics provided further …

Evaluation Of Vtol-Capable Cargo Uavs For Dispersible Airfield Logistics In The Usindopacom Aor, Maria C. Chedzoy

Theses and Dissertations

This research models and analyzes the ability of commercial cargo UAVs to rapidly evacuate logistics from an airfield to proximal, outlying destinations, particularly in the USINDOPACOM AOR. This is a tenet of Agile Combat Employment by the USAF, which seeks to mitigate the effect of kinetic threats by near-peer adversaries. The analysis sets forth a binary linear program to minimize the total time to evacuate a fixed amount of logistics from an airfield. Parameters include the cargo UAV with its performance specifications, number of cargo loading points at the airfield, number of destinations for cargo evacuation, and subset of destinations …

Rotorcraft Assisted Aircraft Inspection System: Creation And Component Assessment, Adam J. Warren

Theses and Dissertations

Aircraft require frequent inspections to perform their missions safely. Current visual inspection methods are time-consuming and dangerous for inspection personnel, but they are necessary to spot flaws that could endanger the aircraft during flight. This research explores a set of methods for transforming a set of target inspection criteria into camera specifications that will allow a UAS aircraft inspection system to perform inspections on the top skin of an aircraft. Given the minimum distance for the UAS to fly above the aircraft, minimum flaw size to search for on the aircraft, minimum number of pixels to display that flaw size, …

Examining The Effect Of Contractor Logistics Support On The Reliability Of Military Aircraft, Rodrigo S. Campos De Moura

Theses and Dissertations

This study utilizes survival analysis for examining the effect of Contractor Logistics Support (CLS) on the reliability of military aircraft before and after implementing CLS. The provider of CLS in this study is the original equipment manufacturer that designed and produced the target aircraft of this study, the Embraer A-29 Super Tucano.

The Impact Of Solar Angle And Cloud Shadows On 3d Reconstruction Of Rolling Stock Cargo, Carlina M. Ostrand

Theses and Dissertations

Meeting the relentless demand for more efficient air cargo transportation is paramount. This paper explores an innovative approach, harnessing cutting-edge stereoscopic vision technology to create 3D point clouds of rolling stock cargo, adaptable to varying solar angles and cloud shadow conditions. A virtual cargo image is generated by systematically organizing depth and location points. Accuracy is rigorously tested across six camera positions offering detailed, real-time insights for optimized cargo loading in unpredictable outdoor conditions. The findings reveal the impact of solar positioning, cloud coverage, & camera placement, pushing the boundaries of possibilities for cargo logistics in challenging environments.

Digital Airworthiness: Development Of A Sysml Based Framework For The Usaf Airworthiness Process, Justin T. Moore

Theses and Dissertations

In 2018 USAF decided to move towards a digital transition for programs and processes. To maximize the impact of initial transition efforts the airworthiness process was identified as a candidate for digital implementation. The airworthiness process is mandated for nearly every system or modification that flies. The airworthiness process identifies specific tasks that must be performed and artifacts that must be produced. This research worked to develop a framework that utilizes SysML to pattern these processes and the required artifacts. A system agnostic, importable library was developed using custom stereotypes and relationships for the purpose of application to digital system …

An Investigation Of Torso Muscle Fatigue And Its Relation To Discomfort During Vertical Vibration Exposure, Nathan H. Hodges

Theses and Dissertations

Military and civilian helicopter pilots often experience back pain attributed to vibration exposure during flight and sustained poor posture, known as the "helicopter hunch." This study investigated torso muscle activation using surface electromyography (EMG) to assess the relationship between discomfort and muscle fatigue. Eight subjects were exposed to different vibration frequencies over two-hour periods, with EMG data collected every five minutes. Significant differences in muscle activation were observed before and after vibration exposure, suggesting increased muscle activation during vibration compared to prolonged seating alone. Discomfort surveys indicated higher discomfort during vibration.

Utilization Of The System Engineering Design Process To Design And Test A Low-Cost Infectious Aerosol Control Mechanism For Patient Aeromedical Evacuation, Sara Shaghaghi

Theses and Dissertations

The aeromedical evacuation of military patients is a critical component of care for Armed Forces members. The Air Force’s ability to transport patients relies on the technology and systems available. A vital transport responsibility is keeping the patient and medical personnel safe during transport. The historical and legacy systems provide reliable transport mechanisms for the Armed Forces’ patients infected with high-level biological agents, but drawbacks must be considered. This dissertation will discuss the development, conceptual design, and initial evaluation of a new low-cost, litter-mounted patient transport system, Biological-Mitigation in Patient Transport (B-MIPT), using the “V” model of the system engineering …

Fair Fault-Tolerant Approach For Access Point Failures In Networked Control System Greenhouses, Mohammed Ali Yaslam Ba Humaish

Theses and Dissertations

Greenhouse Networked Control Systems (NCS) are popular applications in modern agriculture due to their ability to monitor and control various environmental factors that can affect crop growth and quality. However, designing and operating a greenhouse in the context of NCS could be challenging due to the need for highly available and cost-efficient systems. This thesis presents a design methodology for greenhouse NCS that addresses these challenges, offering a framework to optimize crop productivity, minimize costs, and improve system availability and reliability. It contributes several innovations to the field of greenhouse NCS design. For example, it recommends using the 2.4GHz frequency …