Aviation Commons^™

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, …

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 …

Integrating Sustainability Into Aviation Training: Perspectives From Industry Professionals, Eva Maleviti, Sarah Talley

Publications

This paper is part of a broader research project aimed at identifying the most appropriate training materials, formats, and delivery methods for aviation sustainability content for future aviation professionals, starting from the early stages of their training. The current paper presents the data analysis and results of a short online survey targeting aviation professionals. Specifically, it provides preliminary data on sustainability perspectives from global aviation professionals. Through qualitative analysis, the creation of a baseline from a random sample of aviation professionals offers insight into their perspectives and how they could be influenced toward a more sustainable pathway. Additionally, the paper …

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. …

Analysis Of Public Acceptance Of Urban Air Mobility (Uam) Based On Air Travel Frequency, Seuggyun Jin, Kim O. Chambers

Journal of Aviation/Aerospace Education & Research

Urban Air Mobility (UAM) is an innovative air transportation system designed for efficient travel in urban and suburban areas, offering significant time saving compared to traditional ground transportation. However, concerns about UAM services, such as safety and noise, remain prominent. Understanding public acceptance of UAM is crucial to identifying potential customers and ensuring the sustainability of commercial UAM operations. This study utilizes an online survey from a total of 254 consumer attitudes on the scales of reliability, usefulness, behavioral intention, safety, and concerns to examine public acceptance of UAM based on people's air travel frequencies. Using a one-way ANOVA, the …

Generalizing Classification Of Pilot Workload: Transfer Learning Versus A Jepa-Inspired Transformer Architecture, Naim Barnett, Shivani Nagrecha, Morgan Glover, Clayton Harper, Justin Wilson, James Maher, Eric C. Larson

International Journal of Aviation, Aeronautics, and Aerospace

Within the context of learning, there poses difficulty when objectively measuring human performance. In this work, we investigate the evaluation of human performance via its relation to the individual's mental capacity by classification of cognitive load within the domain of aviation. By utilizing a mixed virtual and physical flight simulation environment in conjunction with biometric sensing, we create and evaluate the predictive capabilities of a Joint-Embedding Predictive Architecture (JEPA) and compare the architecture and results to traditional methods for transfer learning and domain adaptation. We find that our JEPA inspired architecture can achieve more than 70% accuracy of cognitive workload, …

Predictive Maintenance Analysis Of Turbofan Engine Sensor Data, Stanley A. Melkumian

The Journal of Purdue Undergraduate Research

Predictive maintenance in aviation and aerospace applications is among the most explored problems in machine learning (ML) and artificial intelligence (AI), and datasets such as NASA’s C-MAPPS turbofan engine degradation simulation data have proven invaluable, helping researchers explore numerous questions on engine performance, maintenance, and failure. The purpose of this study was to extend the current research on predicting the remaining useful life (RUL) of engines and their risk classification. Starting with simple yet under-investigated nonlinear survival and random forest models, the analysis implemented eXtreme Gradient Boosting (XGBoost) and long short-term memory (LSTM) from TensorFlow’s Keras library. For both regression …

Sustainable Flight Training Schools And Their Role To Meet Net Zero Targets, Eva Maleviti

Sustainability Conference

This presentation is part of a wider research project to identify the elements that must be considered regarding flight training schools’ role in aviation sustainability. Net Zero Pathways and goals, emission schemes, design specifications, and sustainable fuels are some of the most popular changes for airlines and manufacturers. Flight training schools must be at the forefront of promoting aviation sustainability to tomorrow’s professionals. The ICAO Carbon Offsetting Requirement Scheme for International Airlines (CORSIA) relies heavily on the firm and reliable information in the operators’ system. Proper emission calculation requires flight crews to feed valid and accurate flight information data. Hence, …

Unleaded Fuel For General Aviation, Carolina Anderson, Laura Garcia

Sustainability Conference

The Clean Air Act, passed in the late 1970s, mandating the removal of lead from most fuels due its detrimental effects on public health, yet piston-driven aircraft continue to rely on leaded aviation gas (AvGas 100LL). This fuel remains the last lead-containing fuel regulated by the Department of Transportation (DOT). Lead, added as tetraethyl lead (TEL), enhances octane levels and prevents engine detonation, vital for high-compression aircraft engines. In response to the health effects, regulating bodies like the Environmental Protection Agency (EPA) have tightened lead standards and are assessing the risk posed by AvGas. Research links even low-level lead exposure …

Smart Airports: Artificial Intelligence–Enabled Internet Of Things Networks Using Blockchain Technology, Edwin Ongola

Journal of Aviation Technology and Engineering

This article provides a perspective on how an internet of heterogeneous self-service airport terminal systems can be used for data collection, which is stored on a private or consortium blockchain depending on the ownership or operations of an airport or both. Such a setup would help to increase efficiency, reduce costs, and improve traveler experience at airport terminals. Moreover, it would allow airports to gather data directly from passengers as opposed to waiting to receive the same data from airlines. Subsequently, this data, now on a blockchain system, becomes a data source for other applications such as machine learning. In …

Data Recovery Beyond The Obvious Using Digital Forensic Techniques, Smit Chandrakant Nayak

Theses, Dissertations and Culminating Projects

Advancement in drone technology, particularly for smaller drones, are creating new research fields and potential applications, particularly with regard to smaller drones. On the other hand, these enhancements bring forth additional hurdles in terms of adaptability, homogeneity, and safety. The purpose of this study is to investigate the science and technology behind drones, as well as their applications, the many ways in which citizens implement them, and the risks, precautions, and privacy problems that are associated with their utilization. This article discusses the existing literature, as well as the available solutions for drone cybersecurity, the security challenges related with drones …

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 …

Igniting Passion:​ A Detailed Journey Through Rocketry Course Activities, Krish M. Patel, Hannah Caycedo, Joshua Gage, Josi Maness, Kevin Park, Mufeng Shen

SACAD: Scholarly Activities

This course is a semester-long adventure in rocketry, led by Dr. Paul Adams. It covers everything about building and flying rockets, starting from the basics to more advanced rocketry. Students learn how to build rockets and use equipment used I payload systems like and altimeter and a GPS. We also learned about the importance of safety involved with building and launching rockets.

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.

Using Natural Language Processing To Identify Mental Health Indicators In Aviation Voluntary Safety Reports, Michael Sawyer, Katherine Berry, Amelia Kinsella, R Jordan Hinson, Edward Bynum

National Training Aircraft Symposium (NTAS)

Voluntary Safety Reporting Programs (VSRPs) are a critical tool in the aviation industry for monitoring safety issues observed by the frontline workforce. While VSRPs primarily focus on operational safety, report narratives often describe factors such as fatigue, workload, culture, staffing, and health, directly or indirectly impacting mental health. These reports can provide individual and organizational insights into aviation personnel's physical and psychological well-being. This poster introduces the AVIation Analytic Neural network for Safety events (AVIAN-S) model as a potential tool to extract and monitor these insights. AVIAN-S is a novel machine-learning model that leverages natural language processing (NLP) to analyze …

Low-Resource Automatic Speech Recognition Domain Adaptation – A Case-Study In Aviation Maintenance, Nadine Amin, Tracy L. Yother, Julia Rayz

Journal of Aviation/Aerospace Education & Research

With timeliness and efficiency being critical in the aviation maintenance industry, the need has been growing for smart technological solutions that optimize and streamline the different underlying tasks (Bergkvist & Sabbagh, 2021). One such task is the technical documentation of the performed maintenance operations (Chandola et al., 2022). Instead of manual documentation, voice tools that transcribe spoken logbook entries allow technicians to document their work right away in a hands-free and time efficient manner. However, an accurate automatic speech recognition (ASR) model requires large training corpora (Siyaev & Jo, 2021a), which are lacking in the domain of aviation maintenance. In …

Fostering Trust In Artificial Intelligence In Commercial Aviation: An Exploratory Study, Leila Halawi, Mark Miller, Sam Holley

Publications

Artificial intelligence (AI) is a transformative force, compelling industries to adapt their operations, management systems, and workforce capabilities. The aviation sector finds itself at the forefront of this transformation, confronted with the imperative to navigate the complex dynamics of trust amidst AI's integration. Through a comprehensive survey involving 310 professionals from across the US commercial aviation sector, the research aims to shed light on the trust construct. The exploratory study provides critical insights for strategic AI adoption within the industry. A crosstabulation explored how employee trust in AI for decision-making differed across various demographic groups. In addition, a onesample T-test …

Virtual Reality & Pilot Training: Existing Technologies, Challenges & Opportunities, Tim Marron, Niall Dungan, Brian Mac Namee, Anna Donnla O'Hagan

Journal of Aviation/Aerospace Education & Research

The introduction of virtual reality (VR) to flying training has recently gained much attention, with numerous VR companies, such as Loft Dynamics and VRpilot, looking to enhance the training process. Such a considerable change to how pilots are trained is a subject that warrants careful consideration. Examining the effect that VR has on learning in other areas gives us an idea of how VR can be suitably applied to flying training. Some of the benefits offered by VR include increased safety, decreased costs, and increased environmental sustainability. Nevertheless, some challenges ahead for developers to consider are negative transfer of learning, …

Application Of Density Altitude Climatology To General Aviation Impacts, Thomas A. Guinn, Daniel J. Halperin, Sarah Strazzo

Journal of Aviation/Aerospace Education & Research

Density altitude (DA) plays a key role in flight safety because it helps pilots anticipate poor aircraft performance when temperatures are warmer than standard. In this study, a 30-year climatology of DA for the conterminous United States was created using the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis of the global climate (ERA5) dataset was applied to four separate DA-based, aircraft-performance, rules-of-thumb for general aviation (GA) flight. The goal was to demonstrate a technique to create educational visualization tools showing the variation of operational flight impacts with both month and location. Four such parameters were chosen to show …

Machine Learning - Hail Awareness Spatial Analysis Toolkit (Hasat), Haoruo Fu, Joseph P. Hupy, Chien-Tsung Lu, Zhenglei Ji

Journal of Aviation/Aerospace Education & Research

The National Airspace System (NAS) is a sophisticated network of air traffic control, navigation, and communication systems that play a critical role in ensuring the safe and efficient flow of air traffic across the United States. However, the occurrence of severe weather conditions, particularly hailstorms, poses a significant threat to flight safety within the NAS. To mitigate the risks associated with hail, aviation organizations have implemented a range of safety measures. This study utilized Esri’s ArcGIS as a mapping software to conduct a geospatial analysis of the impact of severe weather, particularly hail, on the NAS. The Hail Awareness Spatial …

Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman

College of Graduate Studies: Theses & Dissertations

Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …

Fundamentals Of Sustainability, Eva Maleviti

Publications

Fundamentals of Sustainable Aviation is the frst textbook to survey the critical feld of sustainability within the aviation industry. Taking a systems thinking approach, it presents the foundational principles of sustainability and methodically applies them to diferent aviation sectors. Opening with the basics of sustainability, emphasising the Sustainable Development Goals, the book then considers the environmental, economic and social dimensions of aviation. The following chapters apply these insights to aviation design, supply chains, operations, maintenance and facilities. The fnal chapter examines the concept of resilience in sustainable aviation. Overall, the textbook shows how future sustainability can be achieved by making …

Impact Of Weather Factors On Airport Arrival Rates: Application Of Machine Learning In Air Transportation, Robert W. Maxson, Dothang Truong, Woojin Choi

Publications

Weather is responsible for approximately 70% of air transportation delays in the National Airspace System, and delays resulting from convective weather alone cost airlines and passengers millions of dollars each year due to delays that could be avoided. This research sought to establish relationships between environmental variables and airport efficiency estimates by data mining archived weather and airport performance data at ten geographically and climatologically different airports. Several meaningful relationships were discovered from six out of ten airports using various machine learning methods within an overarching data mining protocol, and the developed models were tested using historical data.

The Private Pilot Check Ride: Applying The Spacing Effect Theory To Predict Time To Proficiency For The Practical Test, Michael Scott Harwin

Theses and Dissertations

This study examined the relationship between a set of targeted factors and the total flight time students needed to become ready to take the private pilot check ride. The study was grounded in Ebbinghaus’s (1885/1913/2013) forgetting curve theory and spacing effect, and Ausubel’s (1963) theory of meaningful learning. The research factors included (a) training time to proficiency, which represented the number of training days needed to become check-ride ready; (b) flight training program (Part 61 vs. Part 141); (c) organization offering the training program (2- or 4-year college/university vs. FBO); (d) scheduling policy (mandated vs. student-driven); and demographical variables, which …

Integrating External Sensors With Crazyflie Drones, Xiaowen Wang, Dheryta Jaisinghani, Andrew Berns

Summer Undergraduate Research Program (SURP) Symposium

• Drones are widely used: Mini drones such as Crazyflie 2.1 are used in a variety of fields.
• Grove Sound Sensor function: Grove Sound Sensor can capture sound, providing more application possibilities for drones.
• The potential of Crazyflie 2.1: Although Crazyflie 2.1 has the potential to be an integrated sensor platform, prior to this project, it was uncertain whether sensors could be connected on it.
• Project motivation: Our project aims to explore whether Crazyflie 2.1 can be connected to the Grove Sound Sensor and collect and process data from the sensor.
• Impact of the project: If successful, this project will open …

Measuring Radiation Protection: Partners From Across The Nuclear Enterprise Evaluate The Radiation Protection Of Us Army Vehicles, Andrew W. Decker, Robert Prins

Faculty Publications

Recent mounting nuclear threats and postures from adversary nation-states, such as Russia, China, North Korea, and Iran, represent a clear danger to the interests and security of the United States of America and its Allies. To meet these threats, the 2022 Nuclear Posture Review requires the Department of Defense (DoD) to design, develop, and manage a combat-credible U.S. military which, among other prioritizations, is survivable. A survivable force can generate combat power despite adversary attacks. As such, the US Army must prepare today to set the conditions for successful conventional warfare on the nuclear battlefields of tomorrow. Our Army cannot …

Fast And Accurate 3d Object Reconstruction For Cargo Load Planning, Adam R. Nasi

Theses and Dissertations

Cargo load planning involves efficiently packing objects into aircraft subject to constraints such as space and weight distribution. Currently, this is performed manually by loadmasters. The United States Air Force is investigating ways to automate this process in order to improve airlift operational readiness while saving money. The first step in such a process would be generating 3D reconstructions of cargo objects to be used by a load planning algorithm. To that end, this thesis presents a novel method for fast, scaled, and accurate 3D reconstruction of cargo objects. This method can scan a 2.5m×3m×2m object in less than 10 …

Using Embedded Systems And Augmented Reality For Automated Aerial Refueling, Nathaniel A. Wilson

Theses and Dissertations

The goal of automated aerial refueling (AAR) is to extend the range of unmanned aircraft. Control latency prevents a human from remotely controlling the receiving aircraft as it approaches a tanker. To conform with the size, weight, and power constraints of a small unmanned aircraft, an AAR system must execute in real-time on an embedded platform. This thesis explores the timing and computational performance of a NVIDIA Jetson AGX Orin to a state-of-the-art general-purpose computer using existing AAR algorithms. It also constructs an augmented reality framework as an intermediate step for testing vision-based AAR algorithms between virtual testing and expensive …

Examining Fuel Service System Failures Of The Usaf R11 Using Survival Analysis, Roed M.S. Mejia

Theses and Dissertations

Recent events show that fuel supply is a large contributor to the success or failure of a military operation in response to a contingency. Any future near-peer conflict will stress the supply chain and require fully operational vehicles to be ready for the primary mission sets they support. In the United States Air Force (USAF), the readiness of fuel distribution trucks is crucial to meeting those mission sets in global operations. Utilizing non-parametric and semi-parametric survival models, which do not assume specific probability distributions, this study analyzes maintenance data for R-11 trucks that refuel aircraft.