Aviation Safety and Security Commons^™

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 …

Enhancing Aviation Safety: A Framework For Predictive Maintenance Using Generative Data Augmentation And Uncertainty Quantification, Muhammad Najjar

Student Research Symposium (SRS)

Predictive maintenance is a critical component of aviation safety, yet the development of accurate data-driven models is often hindered by the severe class imbalance inherent in real-world flight data; healthy flights are abundant, while flights preceding a failure are rare. This imbalance biases machine learning models, leading to poor detection of critical maintenance needs. This project addresses this challenge by leveraging the NGAFID aviation maintenance dataset to develop and validate an integrated predictive framework. We propose training a Time-series Generative Adversarial Network (TimeGAN) to synthesize high-fidelity, realistic "pre-maintenance" flight data. This synthetic data is used to create a balanced training …

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

Student Research Symposium (SRS)

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

An Exploration Of Aviation Safety And Security Culture In Nigeria And The United Arab Emirates (Uae), Nicholas Degarmo, Kathrine Lopez, Hana Marz, Cedric Leon, Michael Chrisman

Student Research Symposium (SRS)

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 and the United Arab Emirates (UAE). Both regions have taken great steps to align with international aviation standards, offering insight into how different regions shape their regulatory environments, organizational culture, and how cultural factors affect safety and security practices. While Nigeria continues to face challenges such as inconsistent …

The Wildlife Intelligence For Aviation Safety (Wild-Ai), Bao Khoa Tran

Student Research Symposium (SRS)

Wildlife strikes pose a significant safety risk and economic burden to the aviation industry. Over 291,000 strikes have been reported in the U.S. since 1990, causing an estimated $248 million in annual losses. The Wild-AI (Wildlife Intelligence for Aviation Safety) project leverages cutting-edge technologies, including large language models (LLMs), machine learning (ML), explainable AI (XAI), and Unmanned Air Vehicles (UAV) imagery, to enhance wildlife hazard management at airports. Wild-AI transforms traditional Wildlife Hazard Assessments (WHAs) by integrating advanced data analytics and UAV monitoring. By utilizing historical wildlife-strike data and ML algorithms, we will identify key predictors of damaging strikes, such …

Enhancing Wildlife Strike Risk Assessment Through Large Language Model–Driven Data Analysis, Bill Deng Pan

Student Research Symposium (SRS)

Wildlife strikes remain a persistent safety and economic concern across global aviation operations, highlighting the need for advanced analytical methods to improve risk assessment and mitigation. Traditional statistical approaches to wildlife-strike data, while effective for structured variables such as altitude, phase of flight, or aircraft type, often overlook valuable insights embedded in the unstructured narrative components of strike reports. This study proposes the application of Large Language Models (LLMs) for the automated extraction, classification, and interpretation of information within the Federal Aviation Administration (FAA) Wildlife Strike Database. Using natural language processing (NLP) techniques, LLMs will be utilized to identify key …

Injuries And Accidents On Airport Ramps, Kavya Banarjee

Student Research Symposium (SRS)

Media coverage of aircraft incidents/accidents often triggers public scrutiny and heightened anxiety. But behind that are injuries and fatalities caused on the airport ramps; incidents like these are rarely covered by the media but pose just as much of a safety concern as an aircraft incident. This paper aims to inform aviation industry professionals and airline executives about the causes of incidents and accidents on the airport ramp; it also covers the importance of finding and implementing solutions for safety. The methodology for this paper focuses on research and analysis of publicly available information. Relevant data and perspectives were gathered …

Crew Resource Management Analyzed In Guyana Military Accident, Kaylee Lall

Student Research Symposium (SRS)

"In December 2023, a Guyana Defence Force Bell 412EP helicopter crashed in mountainous jungle terrain near the Venezuela border, killing five of the seven personnel on board. Preliminary investigation findings indicate the probable cause of the accident was pilot error, rather than mechanical failure. Due to deteriorating weather conditions, the crew deviated from the standard route and elected to fly under visual flight rules (VFR) along the Mazaruni River. The combination of limited visibility, rising mountainous terrain, and potential spatial disorientation likely contributed to this controlled flight into terrain.

This case study applies the SHELL model to analyze the interactions …