Aviation Commons^™

Zfq-50 "Radiance", Craig Slovensky, Michael Rath Iii, Kyan Spaete, Long P. Nguyen, Woo Hyun Lee, Roman Czerniejewski

Discovery Day - Daytona Beach

This project presents the preliminary design of the ZFQ-50 "Radiance", a Collaborative Unmanned Vehicle (CUV) built around the VerdeGo VH-5 blended turbofan intended for military defense applications. This design presents a novel aircraft coupled with a powerplant that blends traditional combustion thrust with electrical power output, an new and evolving capability within the aerospace industry. This aircraft was sized considering multiple constraint parameters, configuration trade studies, CFD analysis, and mission requirements including carrier assisted take-off and landing, an effective operational range, and a loiter period with 40 kW of continuous power output from the powerplant. The selected configuration allows for …

Classification Of Sequential Factors In Aviation Accident Cause Prediction, Sophia Nasca, Addyson Wolfe

Discovery Day - Daytona Beach

Uncovering the root causes of aviation accidents is a critical component of improving aviation safety. Traditional approaches are largely reactive, relying on post-incident analysis rather than proactively identifying risk factors. This project addresses the need for proactive safety by using a multi-source dataset that integrates aviation accident records, weather conditions, and maintenance data extracted from investigative reports. The objective of this work is to move beyond predicting broad probable causes and instead model the sequence of contributing factors that lead to aviation incidents. Using the Swiss Cheese Model, the study will capture layered failures across operational, environmental, and maintenance domains. …

Small Uas Detection: Threat Intelligence & Risk Management Project, Tyler Johnson

Discovery Day - Daytona Beach

The TRANSPORTATION SECURITY ADMINISTRATION / FEDERAL AIR MARSHAL SUAS DETECTION: THREAT INTELLIGENCE & RISK MANAGEMENT PROJECT addresses the emerging safety and security challenges posed by the rapid growth of small Unmanned Aircraft Systems (sUAS) in complex airspace environments. This study analyzed 92 days of sensor-captured Remote Identification (RID) data collected near Fort Lauderdale-Hollywood International Airport (FLL) to assess operational behaviors, aviation risk, and ground risk associated with drone activity. The primary objective of this research is to identify patterns of unauthorized or hazardous sUAS operations to enhance situational awareness and inform actionable risk-mitigation strategies. The analysis identified 335 flights from …

Case Study - China Airlines Flight 006, Jaxon Daniels, Ryan Lutwin, Jacob Patterson, Elizabeth Bosan, Ronyn Orrell

Discovery Day - Daytona Beach

On February 19, 1985, China Airlines Flight 006, a regularly scheduled flight from Taipei, Taiwan, to Los Angeles, California, experienced a serious in-flight upset while cruising at high altitude. The aircraft subsequently entered a steep, uncontrolled spiral dive, during which it experienced extreme G-forces and sustained structural damage. After regaining control, the crew diverted the aircraft to San Francisco International Airport, where it landed safely (National Transportation Safety Board, 1986). The Human Factors Analysis and Classification System (HFACS) framework helps to identify and analyse the organizational elements and conditions that lead to aviation accidents (Small, 2020). Aviation accidents are not …

An Innovative Approach To Real-Time Noise Monitoring And Detection In Airport Ramp Operations, Grace Hamilton, Nicole E. Egan, Anderson Peralta, Deyaneira Rodriguez, Maria G. Valentinez

Discovery Day - Daytona Beach

Airport ramp personnel are routinely exposed to hazardous noise levels exceeding occupational safety thresholds, increasing the risk of permanent hearing loss, degraded communication, and operational incidents. Traditional ramp noise management relies primarily on periodic monitoring and personnel protective equipment (PPE), which limits real-time hazard recognition and a proactive risk mitigation strategy. The purpose of this study is to evaluate the safety and financial effectiveness of implementing a real-time noise monitoring and detection system within airport ramp operations in alignment with Safety Management System (SMS) principles. A literature review, Preliminary Hazard Analysis (PHA), and financial cost-benefit analysis were conducted to compare …

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 …

Ai-Driven Scheduling Algorithms For Private Aviation, Tayan Benson, Jessica Buskey, Gabriel Camacho, Caitlyn A. Gabrinowitz

Discovery Day - Daytona Beach

Private aviation scheduling is complex and dynamic, requiring frequent aircraft repositioning based on demand and operational constraints, unlike fixed commercial airline schedules. As fleets grow beyond 300 aircraft, traditional deterministic methods become too slow, leading to the use of approaches such as genetic algorithms, but neural network-based methods have not seen in-depth exploration. This project models aircraft scheduling as a network, where airports and flights form a graph. It explores advanced AI methods, including graph neural networks and spatio-temporal graph neural networks (STGNNs), to capture both network structure and time constraints. The goal is to generate efficient daily schedules from …

Fatigue And Circadian Disruption In Long-Haul Ferry Pilots: Human Factors Challenges And Mitigation Strategies, Parneet Makkar

Discovery Day - Daytona Beach

Fatigue and circadian rhythm disruption present significant human factors challenges in long-haul aviation operations, particularly for ferry pilots (pilots responsible for transporting aircraft long distances between locations) who often travel across multiple time zones before beginning flight duties. Circadian rhythms regulate the human sleep-wake cycle and are closely tied to cognitive performance, alertness, and coordination. Rapid travel across time zones can disrupt these rhythms, producing symptoms commonly associated with jet lag such as sleep disturbances, fatigue, and reduced cognitive functioning. For ferry pilots, long travel periods and irregular schedules may increase the likelihood of fatigue before flight operations even begin. …

Predicting Passenger Demand On National Flights Departing From Hartsfield-Jackson Atlanta International Airport (Atl) In 2024, Brooklyn Gossett, Ana Yu Wen

Discovery Day - Daytona Beach

The aviation industry relies heavily on accurate demand forecasting to guide critical decisions regarding route planning, capacity management, and pricing strategy. Misjudging passenger demand can result in significant revenue loss and operational inefficiency, making it essential for airlines and analysts to identify the key drivers of flight patronage. This study investigates the factors that most significantly predict the number of passengers on domestic flights departing from Hartsfield-Jackson Atlanta International Airport (ATL) during the 2024 calendar year. Using passenger and route data sourced from the Bureau of Transportation Statistics (BTS) and the U.S. Department of Transportation (DOT), a multiple regression analysis …

An Evaluation Of Machine Learning Models' Efficacy In Determining Uav Spoofing Attacks, Nicolas Machado, Jaxon Selzer

Discovery Day - Daytona Beach

An Evaluation of Machine Learning Models' Efficacy in Determining UAV Spoofing Attacks - The rapid integration of Unmanned Aerial Vehicles (UAVs) into urban airspace has introduced significant cybersecurity concerns, particularly due to vulnerabilities in Automatic Dependent Surveillance–Broadcast (ADS-B), which lacks authentication and encryption. This project addresses the problem of detecting spoofing and data manipulation attacks that can compromise UAV safety and mission reliability. The objective of this work is to evaluate the effectiveness of machine learning–based anomaly detection, specifically Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) networks, as protocol-agnostic solutions for identifying anomalous UAV behavior. To achieve this, …

Fault-Aware Flight Path Assessment For Evtols Using An Integrated Air Traffic Management Environment, John Clardy, Edison Alberto Martinez Samaniego

Discovery Day - Daytona Beach

This study introduces a simulation framework to evaluate Fault-Aware Flight Paths for electric vertical takeoff and landing (eVTOL) aircraft within an integrated air traffic management environment. By combining an air traffic management system with intelligent trajectory generation frameworks, the approach assesses the development of safe, adaptive, and fault-aware flight paths that account for traffic interactions, airspace features, and specific operational constraints. Real-world historical airspace traffic data was used to accurately simulate complex and congested operational conditions. The main goal is to evaluate the operational impact of integrating eVTOL operations into the National Airspace System, with a focus on conflict detection, …

A System Safety Approach To Assuring Artificial Intelligence Enabled Functions In Civil Aviation, Evan Bear, Quinn Galen

Discovery Day - Daytona Beach

Artificial intelligence and machine learning techniques are increasingly proposed for use in safety-critical civil aviation functions including perception decision support and pilot assistance. Existing aviation safety and certification standards such as ARP4754A and DO-178C were developed under assumptions of determinism explicit requirements and complete behavioral specification which do not directly apply to learning-enabled systems. This mismatch has created uncertainty regarding how artificial intelligence enabled avionics can be safely assured and certified. This paper presents a system safety approach for assuring artificial intelligence enabled functions within existing aviation certification frameworks. In this approach safety assurance is based on explicitly identifying the …

Design And Implementation Of A Synchronized Data Acquisition System For An Ihlp Cessna 182 Testbed, Celso Ferreira De Moura, Mariano Chavez Rangel

Discovery Day - Daytona Beach

This work presents the design and implementation of a fully integrated data acquisition system for a full scale Integrated High Lift Propulsion testbed based on a Cessna 182Q, with emphasis on hardware integration, sensor reliability, and time synchronization. A centralized architecture was developed in LabVIEW to acquire, process, and store data from both analog and digital sensors, including air data systems, inertial measurement units, control positions, and propulsion instrumentation. Analog sensors were carefully calibrated to ensure accurate conversion to engineering units, while digital sensors were incorporated into a unified framework to maintain consistency across all measurements. All ADC, GPS, INS, …

Real-Time Fused Sensor System For Early Onboard Detection Of Weather Phenomena, Sanjana Singh

Discovery Day - Daytona Beach

Weather-related hazards continue to be a major cause of operational interruptions and safety issues in the aviation sector. Atmospheric phenomena, including turbulence, microbursts, convective storms, and rapidly changing boundary-layer conditions, can arise quickly and often occur on spatial scales that are not adequately addressed by regional forecasting systems. These phenomena particularly endanger aircraft flying at low altitudes, such as general aviation planes, unmanned aerial vehicles (UAVs), and those during takeoff and landing Although meteorological forecasting systems and ground-based radar networks offer important regional insights, they may fail to detect localized atmospheric variations encountered along specific flight routes. Consequently, pilots and …

Professionalism And Performance Expectations In The Modern Aviation Industry, Anayah Smith, Spencer Baldock Spencer Baldock

Discovery Day - Daytona Beach

The aviation industry operates as a highly regulated, safety-critical environment in which professionalism and consistent performance are essential to maintaining operational safety and reliability. However, emerging shifts in workforce composition, communication styles, and technology integration have created misalignment between traditional professional standards and evolving employee expectations. Established aviation cultures emphasize structured procedures, formal feedback mechanisms, and communication hierarchy, while newer entrants, shaped by digital communication norms and contemporary academic environments, often expect continuous feedback, collaborative leadership, and adaptive performance evaluation. Prior research on crew resource management, human error frameworks, and generational work values highlights how inconsistencies in communication, feedback expectations, …

An Exploration Into Aviation Safety & Security In Nigeria, Hana Marz, Nicholas Degarmo, Kathrine Lopez, Michael Chrisman

Discovery Day - Daytona Beach

Aviation safety and security standards are fundamental for enabling the reliability and sustainability of aviation operations. Aviation safety and security are influenced by organizational and institutional standards, as well as the application of human factors principles. This paper aims to explore the regional variances of aviation safety and security culture within Nigeria. Nigeria has taken steps to align with international aviation standards, offering insight into how the region shapes its regulatory environment, organizational culture, and how cultural factors affect safety and security practices. However, Nigeria continues to face challenges such as inconsistent regulatory enforcement and limited safety reporting, which impact …

Development Of Proposed Airworthiness Certification Criteria For Interference-Tolerant Radio Altimeter Systems, Matheus B. Furstenberger

Student Works

Radio altimeters provide height-above-ground information to flight deck displays and multiple safety-critical aircraft systems, however legacy certification standards were not developed for high-power terrestrial wireless services operating in adjacent C-Band spectrum. This study addressed the absence of a consolidated airworthiness certification framework for interference-tolerant radio altimeter systems installed on Title 14 Code of Federal Regulations Part 25 transport category airplanes. An archival research synthesis was conducted using publicly available regulations, proposed and final rules, technical standard orders, advisory circulars, airworthiness directives, industry standards, spectrum-management documents, technical studies, and stakeholder comments. Qualitative content analysis and source triangulation were used to identify …

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 …

An Evaluation Of The “Police Response To Uncrewed Aircraft Systems Operations” Online Training Program, Anthony Galante, Leila Halawi

Publications

This study evaluates the impact of the “Police Response to Uncrewed Aircraft Systems Operations” online training program of officers from the Daytona Beach Police Department (DBPD). By measuring the effectiveness of the training through pretest and posttest assessments and considering variables such as educational background, length of service, and rank, this research underscores the training’s potential to enhance UAS response capabilities. Employing a self-selection sampling method, the study engaged 82 voluntary participants from the DBPD, revealing significant improvement across all groups in UAS knowledge and confidence levels. Despite limitations, these findings offer compelling evidence of the training’s efficacy and advocate …

Classification Of Aircraft Checklist Usability Problems Using Natural Language Processing, Borvorn Kasemtanakul

Doctoral Dissertations and Master's Theses

The use of checklists has been identified as a recurring issue in aviation accident investigations, highlighting the need for continued improvement in aircraft checklist design. However, existing aviation safety taxonomies do not systematically address checklist usability problems. Therefore, a systematic classification of these problems is needed to support the extension of existing aviation safety taxonomies and to facilitate safety data analysis for checklist design improvements. Furthermore, applications of Natural Language Processing (NLP) techniques in aircraft checklist research remain underexplored, despite their potential to identify meaningful patterns in textual safety data.

This exploratory research aimed to develop a data-driven classification of …

Enhancing Virtual Reality Cockpit Procedure Training With Haptic Feedback, Christian K. Jaedicke

Doctoral Dissertations and Master's Theses

Pilot training is time-consuming and costly, and not all phases require full-flight simulators or actual aircraft. Virtual reality (VR) offers a potential means to reduce cost and duration while supporting practical cockpit procedure training. While prior research in the VR domain suggests that providing haptic feedback can support training of muscular control and increase perceived immersion, it remains unclear whether haptic feedback improves spatial cognition in an unfamiliar VR environment. This study examined whether haptic feedback and cockpit complexity affected response time and position error under limited-visibility, time-constrained conditions in a VR cockpit environment (i.e., a quasi-blindfold cockpit check).

Grounded …

Evaluating The Safety Efficiency Of U.S. Air Traffic Control Tower Operations Using Data Envelopment Analysis, Kenneth James Gilbert Ii

Doctoral Dissertations and Master's Theses

Air traffic control (ATC) tower safety efficiency remains inadequately measured despite critical workforce challenges, including staffing shortages, training pipeline constraints, and geographic retention difficulties. This mixed-methods study developed and validated a comprehensive framework for measuring tower safety efficiency by integrating subject-matter expert insights with multi-model data envelopment analysis (DEA) across 66 Federal Aviation Administration (FAA) tower facilities from 2016 to 2024. Six focus group interviews with experienced professionals (100% with > 20 years of experience), averaging 96.4 minutes, identified critical efficiency factors through systematic coding, achieving substantial inter-rater reliability (Cohen's kappa 𝜅 = .68). Qualitative findings showed that staffing shortages don't …

Are Single-Pilot Operations An Advantage Or A Disadvantage?, Ezgi Berte Erme

International Journal of Aviation, Aeronautics, and Aerospace

This study aims to investigate the potential benefits and drawbacks of Single-Pilot Operations (SPO) and to provide actionable insights for commercial airlines. A qualitative research design was employed, with data collected via online interviews and analyzed thematically and descriptively using MAXQDA 24. The findings indicate that pilots perceive several advantages of SPO, including the power of automation, learning artificial intelligence, minimizing human error, cockpit systems designed for artificial intelligence, more effective decision-making/speed-up in response time, reduced labor costs, reduced pilot fatigue, and reduced need for human factor/performance. Conversely, the perceived disadvantages include diminished lack of situational awareness, lack of communication …

Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca

Publications

As artificial intelligence transforms aviation, aerospace, and autonomy-related sectors, higher education must adapt to meet evolving workforce demands. This session shares emerging findings from a nationwide study led by Embry-Riddle Aeronautical University, focused on employer perceptions of AI adoption, responsible use, and workforce preparedness in domains including uncrewed systems, space systems, robotics, and advanced air mobility. Based on a structured survey and follow-up interviews, the presentation explores how organizations are using AI tools, from generative platforms to enterprise systems, and defining effective and inappropriate use in operational contexts. Participants will gain insight into critical concerns (e.g., data privacy, compliance, security, …

Clear-Air Turbulence Climatology And Trends, Liam Rodgers, Mark Sinclair

Publications

Clear‑air turbulence (CAT) is a major aviation hazard that occurs near airline cruising altitudes in both cloud and cloud‑free environments. Its lack of a distinct visual signature makes detection and avoidance difficult. CAT is associated with wind shear near jet streams, gravity waves, and Kelvin–Helmholtz instability and may be further enhanced by climate change. This study examines the climatology, spatial distribution, seasonal variability, and trends of CAT over the contiguous United States.

Pilot Reports (PIREPs) from 2001–2025 between 100 and 400 hPa are analyzed alongside jet stream, shear, and stability diagnostics derived from NCEP–NCAR Reanalysis data. Proxies such as inverse …

Digital Twin–Oriented Certification Architecture For Advanced Air Mobility, Daniel Pleffken

International Journal of Aviation, Aeronautics, and Aerospace

Advanced Air Mobility (AAM) systems introduce certification challenges associated with distributed propulsion, increasing software reliance, and tightly coupled architectures. These characteristics evolve within regulatory environments that are still adapting to emerging vehicle concepts. While digital engineering practices are increasingly adopted during system development, certification workflows remain largely document-centric, limiting lifecycle traceability and consistent reasoning about change impacts as designs and regulatory interpretations evolve. This paper proposes a Digital Twin–oriented certification architecture that integrates regulatory knowledge, system representations, Means of Compliance (MoCs), and verification artifacts within a unified model-based environment. The architecture is organized around four elements: regulatory structuring, Model-Based Systems …

Safety-Aware Trajectory Generation For Increased Autonomy In Advanced Air Mobility, Edison Alberto Martinez Samaniego

Doctoral Dissertations and Master's Theses

Advanced Air Mobility (AAM) envisions highly automated aircraft that will enable short and medium range transportation. Unlike conventional aviation, these vehicles are expected to operate closer to populated areas and with increased levels of autonomy, making safe operation under abnormal or degraded conditions a critical requirement. Failures or performance degradation can reduce the maneuvering capability of an aircraft, causing trajectories planned under nominal conditions to become dynamically unfeasible.

This thesis presents a trajectory generation and replanning framework designed to maintain safe and feasible flight under reduced flight envelope conditions for a lift+cruise eVTOL aircraft. A unified control architecture based on …

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 …

Artificial Intelligence In Aviation: Benefits, Concerns, And Regulations, Aarohi Srivastava

Student Research Symposium (SRS)

As artificial intelligence (AI) becomes increasingly integrated into aviation systems, understanding its implications for safety and regulation is critical. This research examines the current state of AI implementation in aviation, exploring both transformative benefits and significant concerns in this high-stakes environment. AI's strengths, including rapid large-scale data processing, predictive capabilities, and pattern recognition, offer substantial operational advantages. However, these benefits must be balanced against key concerns including liability issues, potential loss of pilot competency through over-reliance, the "black box" problem of AI explainability, emergent system behaviors, and training requirements.  This project analyzes current regulatory frameworks from major aviation authorities including …