U.S. Federal Aviation Administration Safety Management System Regulations: An Informal Policy Evaluation,
2025
Embry Riddle Aeronautical University - Prescott
U.S. Federal Aviation Administration Safety Management System Regulations: An Informal Policy Evaluation, Brian J. Roggow
Publications
The United States (US) Federal Aviation Administration (FAA) revised 14 CFR § Part 5 Safety Management Systems, effective May 28, 2024. US air carriers have one year to modify their existing Safety Management System (SMS), whereas commuter and on-demand operators, commercial air tour operators, certain production certificate holders, and certain holders of a type certificate must implement an SMS within three years. The sociopolitical and legal rule-making processes are complex. This research evaluates the most recently revised FAA SMS regulations through the lens of prevailing literature, theories, and standard practices. Policy assessments and evaluations by non-governmental stakeholders can further inform …
Distribution Comparisons Of Eac Cost Growth For Aircraft Work Breakdown Structure Elements,
2025
USAF Aerospace Systems Directorate
Distribution Comparisons Of Eac Cost Growth For Aircraft Work Breakdown Structure Elements, Kyle P. Marquis, Edward D. White, Brandon M. Lucas, Robert D. Fass, Jonathan D. Ritschel, Shawn M. Valentine
Faculty Publications
This article analyzes and investigates the distribution of cost growth of the Estimate at Completion (EAC) for the Work Breakdown Structure (WBS) elements of approximately 60 historical United States Acquisition Category I Research, Development, Test and Evaluation aircraft programs. Using the method of maximum likelihood in conjunction with the Akaike Information Criterion, the authors suggest that both the lognormal and Weibull distributions provide relatively good fit to EAC cost growth, with the lognormal slightly edging out the Weibull. As a summarized finding, the authors present their empirical results for the mean, coefficient of variation (CV), the 15th and 85th percentiles …
Occupational Safety Culture In Modern Aviation Maintenance,
2025
Embry-Riddle Aeronautical University
Occupational Safety Culture In Modern Aviation Maintenance, Sang-A Lee
Journal of Aviation Technology and Engineering
Aviation maintenance is paramount to the safety and efficiency of global air travel. Disturbingly, 2022 data revealed an unprecedented surge in severe injuries among aircraft maintenance technicians in the United States, prompting renewed scrutiny of the aviation maintenance occupational safety culture. In light of these developments, a systematic literature review was conducted to discern the influential factors shaping this safety culture, especially considering the industry’s rapid technological advancements. The review process involved meticulous key word searches, stringent article selection criteria, and qualitative data analysis software to interpret findings. From the synthesis of 35 peerreviewed articles, nine pivotal constructs emerged: (1) …
Aircraft Leasing And Its Effects On Ireland's Airline Sector,
2025
Fort Hays State University
Aircraft Leasing And Its Effects On Ireland's Airline Sector, Aaron Christian, Jeanne Sumrall
SACAD: Scholarly Activities
The aircraft leasing industry sits at the heart of Ireland’s aviation sector, making Ireland the global leader in the business. The presence of major leasing companies’ headquarters, including Avolon, SMBC and AerCap, in Ireland, allows for country to benefit from these companies’ revenue. In return, Ireland provides the companies with supportive tax and regulatory frameworks that benefit the aviation sector. The research on this topic explores different ways aircraft leasing contributes to airline efficiency through cost reductions and fleet modernization while minimizing financial risks associated with aircraft acquisition by utilizing computer programs. Operational modeling has become an essential tool for …
Lessons Learned From The Warsaw Airport,
2025
CHA Consulting, Inc.
Lessons Learned From The Warsaw Airport, Nathan Lienhart, Nicholas King
Purdue Road School
An overview of two recent projects that are currently under construction at Warsaw Municipal Airport. The presentation provides project background and details, along with project nuances and lessons learned.
Using Thermal Camera Drones In Beef Cattle Roundup,
2025
Utah State University
Using Thermal Camera Drones In Beef Cattle Roundup, Justin Wyatt Clawson, Eric Galloway, Shalyn Drake, Shawn Barstow, Ross Israelsen, Michael Pate
All Current Publications
Using drones with thermal sensors can be an effective tool in finding and collecting livestock from summer mountain ranges in the West. Drones can complete searches in much less time than required on horseback in demonstrated areas. Using drones reduces the workload of the rider and horse, saving time and energy and reducing the risk of injury. With proper training and certification, livestock producers can use drones to locate cattle and perform many other cost-cutting operations.
Palindrome: A Bi-Directional Multi-Object Detection Framework For Relative Navigation And Autonomous Docking,
2025
Air Force Institute of Technology
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,
2025
Air Force Institute of Technology
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,
2025
Air Force Institute of Technology
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,
2025
Air Force Institute of Technology
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,
2025
Air Force Institute of Technology
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,
2025
Air Force Institute of Technology
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,
2025
Air Force Institute of Technology
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,
2025
Air Force Institute of Technology
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 (mAP0.5:0.95 = 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,
2025
Air Force Institute of Technology
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,
2025
Air Force Institute of Technology
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 …
An Overview Of Aeronautical Occurrences Related To Safety In Brazil And The United States,
2025
Federal University of Uberlândia
An Overview Of Aeronautical Occurrences Related To Safety In Brazil And The United States, Diogo Carlos Rodrigues, Giuliano Gardolinski Venson, Odenir De Almeida
Journal of Aviation Technology and Engineering
This essay presents a comparative analysis of the aeronautical occurrences registered in Brazil and in the United States from 2012 to 2021. The study was carried out through several segmentations of the occurrences and the aircrafts involved. Statistical data from the websites of Brazil’s Center for Investigation and Prevention of Aeronautical Accidents and the US National Transportation Safety Board was used for the comparative analysis. The evolution of the number of aircraft registered in each country was evaluated, and although the number of aircraft in the United States is much higher than in Brazil, the US occurrence rate is lower. …
Beyond The Blue Skies: A Comprehensive Guide For Risk Assessment In Aviation,
2025
Embry-Riddle Aeronautical University
Beyond The Blue Skies: A Comprehensive Guide For Risk Assessment In Aviation, Leila Halawi, Mark Miller, Sam Holley
Publications
Risk assessment in aviation is a critical process that safeguards the safety and reliability of operations. Aviation operations encompass inherent risks, from mechanical failures to human errors and environmental factors. The significance of these risks may be severe, leading to accidents, injuries, and loss of life. Recognizing and mitigating risks is supreme in this dynamic environment, where emerging technologies and innovation constantly reshape this industry. This chapter includes an in-depth explanation of risk management and analysis, leading to the core elements of risk assessment specifically for aviation operations. We will describe the process and explore some of the applications and …
Introduction To Drones,
2025
Utah State University
Introduction To Drones, Shawn Barstow, Justin Wyatt Clawson, Shalyn Drake, Eric Galloway, Michael Pate
All Current Publications
Unmanned aircraft have advanced so much that they are completing tasks and integrating into all aspects of our lives. They deliver, survey, collect data, and complete assigned tasks with more efficiency and lower cost than many currently used techniques. The Federal Aviation Administration (FAA) completely supports UAS in the National Airspace System (NAS) and continually updates information in this new and exciting field. This fact sheet will help you identify how you can legally fly drones and become an integral part of aviation’s vast and ever-progressing world.
The Case Of The Unexpected Attorney,
2025
Embry-Riddle Aeronautical University - Prescott
The Case Of The Unexpected Attorney, Sarah Nilsson
Publications
Associate Professor of Applied Aviation Science Sarah Nilsson shares her professional experiences and insights in the areas of aviation and aviation law.
