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Articles 451 - 480 of 196023
Full-Text Articles in Entire DC Network
Quantitative Analysis Of A Single Operator’S Flight Behavior In Simulation, Zackrey Schraeder
Quantitative Analysis Of A Single Operator’S Flight Behavior In Simulation, Zackrey Schraeder
Discovery Day - Daytona Beach
Uncrewed Aircraft Systems (UAS), or more commonly known as drones, have become increasingly used for a variety of applications, and more research has emerged studying the human-machine interaction and pilot performance metrics. Current research focuses on desired behaviors or aggregated pilot data which does not provide a holistic picture of an individual pilot’s flight behaviors, which are shaped by their own experience, preferences, and risk tolerance. The study investigates whether an individual pilot’s flight behaviors can be considered a pattern or if there is enough flight-to-flight variability to consider the behaviors inconsistent. A series of 20 flights were conducted in …
Modernization Of Deicing Operations Utilizing Uncrewed Aircraft Systems, Christopher Sidor, Hunter Lisle, Zackrey Schraeder
Modernization Of Deicing Operations Utilizing Uncrewed Aircraft Systems, Christopher Sidor, Hunter Lisle, Zackrey Schraeder
Discovery Day - Daytona Beach
Modernization of Deicing Operations Utilizing Uncrewed Aircraft Systems The use of Uncrewed Aircraft Systems (UAS), commonly known as drones, has become more apparent in everyday life within the United States (US). The Airport Cooperative Research Program (ACRP) has provided an opportunity to utilize drones to improve quality of life and operational efficiency at airports across the US. Students from Embry-Riddle Aeronautical University under the callsign Team Frostbite, consists of Hunter Lisle, Zakrey Schraeder, and Christopher Sidor. The team provides a potential solution utilizing UAS to measure the efficiency of deicing applications at Patrick Leahy Burlington International Airport (BTV) in Burlington, …
Learning Casual Structures From Aviation Accident Narratives Using Natural Language Processing And Graph-Based Knowledge Representation, Stephanie Ramsey, Katherine Hoffsetz, Madeline Gorman, Logan Lambeth
Learning Casual Structures From Aviation Accident Narratives Using Natural Language Processing And Graph-Based Knowledge Representation, Stephanie Ramsey, Katherine Hoffsetz, Madeline Gorman, Logan Lambeth
Discovery Day - Daytona Beach
Understanding the complex causal relationships underlying aviation accidents is critical for improving safety and preventing future incidents. However, much of this information exists in unstructured narrative reports, making large-scale analysis difficult. This project aims to automatically extract and model causal chains from National Transportation Safety Board (NTSB) accident narratives using a combination of traditional natural language processing (NLP) techniques, transformer-based architectures, and graph-based knowledge representation. Traditional NLP methods, including named entity recognition, dependency parsing, and rule-based pattern matching, will be used to identify structured cause–effect relationships. These approaches will be compared with transformer-based models, including a lightweight encoder for classification …
Exploring Generation Z Pilots' Approach To Training Automation: An Interview Study, Mary Bender
Exploring Generation Z Pilots' Approach To Training Automation: An Interview Study, Mary Bender
Discovery Day - Daytona Beach
Introduction. Today's pilots learn to fly on aircraft with sophisticated automated systems, such as the G1000. Although automation can reduce workload, over-relying on this technology can lead to decreased situational awareness, complacency, and a loss in manual flying skills (Parasuraman, 2000; Parasuraman et al., 2000; Parasuraman & Wickens, 2017; Taylor et al., 2020). Instructor pilots, in turn, are faced with the challenge of teaching students how to leverage a system that can affect their performance, both positively and negatively. The purpose of this study was to explore the strategies and challenges that instructor pilots face when training students on automation. …
High-Level Trajectory Learning For Non-Prehensile Object Manipulation With Hierarchical Reinforcement Learning, Gulsum Tuba Cibuk Girgin
High-Level Trajectory Learning For Non-Prehensile Object Manipulation With Hierarchical Reinforcement Learning, Gulsum Tuba Cibuk Girgin
Discovery Day - Daytona Beach
Site exploration requires in-situ resource utilization when the physical properties of resources are unknown. Therefore, a generalizable object manipulation method is crucial for extraterrestrial environments. Existing studies develop reinforcement learning policies that enable interaction with objects, in which quadruped robots learn to reach commanded goals with one foot while balancing with the remaining legs. However, in these studies, goal-oriented task execution relies on high-level trajectories provided by human experts, which limits autonomous robotic operations. In this study, we propose a hierarchical DRL in which a high-level pedipulation policy outputs commands for a low-level reach policy, enabling autonomous, smooth and affordable …
Quantitative Assessment Of Cybersecurity Risk Variability Across Transportation Modes, Paulo Carreon
Quantitative Assessment Of Cybersecurity Risk Variability Across Transportation Modes, Paulo Carreon
Discovery Day - Daytona Beach
Quantitative Assessment of Cybersecurity Risk Variability Across Transportation Modes examines how cybersecurity risks differ across major transportation sectors and addresses the lack of a structured, cross modal analysis in existing transportation cybersecurity research. As transportation systems increasingly rely on digital infrastructure, communication networks, operational technologies, and interconnected platforms, they become more exposed to cyber threats that can affect safety, mobility, operations, and public trust. Despite the growing importance of this issue, there is still limited research that quantitatively compares how cyber risks vary across transportation modes such as road and intelligent transportation systems, aviation, rail and transit, and maritime systems. …
Small Unmanned Aerial Systems-Assisted Airport Obstruction And Perimeter Inspections, Christopher Candler, Christopher M. Saylor, Marcus Thompson, Tejash Zala
Small Unmanned Aerial Systems-Assisted Airport Obstruction And Perimeter Inspections, Christopher Candler, Christopher M. Saylor, Marcus Thompson, Tejash Zala
Discovery Day - Daytona Beach
Airports are required to maintain obstruction-free airspace surfaces under 14 CFR Part 77; however, vegetation and perimeter obstruction management is often conducted through periodic ground inspections and contractor-led surveys that provide only snapshot conditions. These approaches may delay detection of encroachments into approach, transitional, horizontal, or primary surfaces, increasing the risk of operational impacts and reactive mitigation. This study proposes an FAA-aligned framework integrating small unmanned aircraft systems (sUAS) into obstruction monitoring workflows through recurring, repeatable perimeter inspections. High-resolution optical and LiDAR sensors, combined with RTK/PPK-enabled GNSS correction, generate centimeter-level geospatial datasets that are processed into canopy height models. These …
Advancing Runway Incursion Severity Prediction Through Tabular-To-Image Deep Learning, Bill Deng Pan, Yupeng Yang
Advancing Runway Incursion Severity Prediction Through Tabular-To-Image Deep Learning, Bill Deng Pan, Yupeng Yang
Discovery Day - Daytona Beach
Runway incursions remain one of the most persistent safety challenges in modern aviation operations, often resulting from complex interactions among human, environmental, and operational factors. While existing Safety Management System (SMS) frameworks emphasize monitoring the frequency of incursions, they provide limited predictive capability regarding event severity. This ongoing study seeks to address that gap by applying a novel tabular-to-image deep-learning approach to improve the accuracy and interpretability of runway-incursion severity prediction models. Data for this study will be drawn from the Federal Aviation Administration (FAA) Runway Safety Statistics and National Transportation Safety Board (NTSB) accident databases. The methodology will involve …
Assessing Safety Culture Among Airport Operators Through Stakeholder Perceptions, Bill Deng Pan
Assessing Safety Culture Among Airport Operators Through Stakeholder Perceptions, Bill Deng Pan
Discovery Day - Daytona Beach
The effective implementation of Safety Management Systems (SMS) at airports depends not only on compliance with regulatory requirements but also on the presence of a strong and measurable safety culture. While the Federal Aviation Administration (FAA)’s increasing emphasis on SMS has accelerated adoption across certificated airports, many airport operators, often coming from operational, engineering, or business backgrounds, lack practical methods to assess safety culture in a structured and actionable manner. Existing guidance highlights the importance of safety culture and safety climate. However, limited research exists on how airport stakeholders perceive and experience safety culture within the airport operating environment. This …
Sequential Causal Architecture For Multimodal Aviation Accident Prediction, Kaitlyn Cavanaugh, Isaac Morrison
Sequential Causal Architecture For Multimodal Aviation Accident Prediction, Kaitlyn Cavanaugh, Isaac Morrison
Discovery Day - Daytona Beach
Aviation accidents are rarely the result of a single failure but rather from a complex causal chain of latent failures. While traditional data mining models often predict incident occurrence, they frequently overlook the sequential mechanics defined by known accident causation theoretical frameworks like the Swiss Cheese Model and the FAA's HFACS. This project addresses the need for interpretable, reliable, multi-stage forecasting by proposing a Sequential Causal Architecture that transforms theoretical causation models into a structured Directed Acyclic Graph (DAG) for multimodal accident causation chain prediction. Data from the NTSB and DOT is used and connected together in a meaningful way …
Heuristic Trafficability Assessment For Autonomous Lunar Surface Operations Using Orbital Data Products, Leia Spaniak
Heuristic Trafficability Assessment For Autonomous Lunar Surface Operations Using Orbital Data Products, Leia Spaniak
Discovery Day - Daytona Beach
This study seeks to map the surface of the Moon by developing a new orbital dataset composed of layers that inform trafficability. The project supports the objectives of the Artemis Program by focusing operations on the Lunar South Pole, where terrain conditions remain difficult to assess over broad areas. With future validation anticipated through cone penetrometer testing, the study examines what orbital data layers can reveal about bearing capacity through estimated internal friction angle, density, and cohesion. The research evaluates the feasibility of this methodology by comparing the mapping strategy to data obtained during the Apollo 15, 16, and 17 …
Assured Learning For Intelligent Dynamic Systems: A Metacognitive Framework, Rocio Jado Puente, Michael Budihartono, Eduar Cabrera Gaspar
Assured Learning For Intelligent Dynamic Systems: A Metacognitive Framework, Rocio Jado Puente, Michael Budihartono, Eduar Cabrera Gaspar
Discovery Day - Daytona Beach
Assured Learning for Intelligent Dynamic Systems: A Metacognitive Framework Advanced Air Mobility systems, including electric vertical takeoff and landing (eVTOL) aircraft and autonomous drone platforms, require increasingly high levels of autonomy and safety. Meeting these demands calls for intelligent systems that can adapt in real time to uncertainty and changing environmental conditions. However, traditional certification methods are not well suited to rigorously measure or quantitatively verify the performance of online learning components because of their non-deterministic behavior. This work introduces a novel runtime safety assurance method based on a metacognitive architecture (MCA) that supervises and regulates learning-enabled components. The approach …
Modeling Aircraft Collision Risk Using Machine Learning And Traffic Density Data Ac, Jadia Renee Ewing, Alexander Van Baelan, Conrad Prisby, Rafal P. Smietana
Modeling Aircraft Collision Risk Using Machine Learning And Traffic Density Data Ac, Jadia Renee Ewing, Alexander Van Baelan, Conrad Prisby, Rafal P. Smietana
Discovery Day - Daytona Beach
Air traffic congestion is an increasingly important factor in aviation safety as global flight activity continues to grow. This project investigates whether higher traffic density is associated with an increased risk of aviation incidents and identifies key contributing factors. Using publicly available flight (ADS-B) and incident (NTSB) data, we apply several machine learning models to analyze traffic patterns and predict risk. We begin with logistic regression to evaluate the relationship between density and incident probability, followed by decision trees to extract interpretable rules describing high-risk conditions. K-nearest neighbors (KNN) is used to examine similarity in traffic patterns among incident flights, …
Impact Of Stress & Fatigue On Cardiovascular Function In Young Pilots: A Thematic Review, Swarna Manoj
Impact Of Stress & Fatigue On Cardiovascular Function In Young Pilots: A Thematic Review, Swarna Manoj
Discovery Day - Daytona Beach
Impact of Stress & Fatigue on Cardiovascular Function in Young Pilots: A Thematic Review Authors: Swarna Manoj, Scott Ferguson Keywords: pilot, stress, fatigue, heart rate variability (HRV), cardiovascular disease (CVD) Aviation is expanding globally and young pilots are the major workforce, yet FAA protocols require mandatory ECG only from age 35, with annual cardiac screening after age 40. Over the past five years, a pattern of sudden cardiac arrests in pilots particularly aged 30-40 has urged safety concerns. Despite the existing literature examining fatigue, burnout, stress, sleep hygiene and circadian disruption, only few studies systematically examine how these factors impact …
A Sustainability Index For Airlines: A Kpi-Based Framework For Benchmarking Environmental Performance, Craig Dedrick
A Sustainability Index For Airlines: A Kpi-Based Framework For Benchmarking Environmental Performance, Craig Dedrick
Discovery Day - Daytona Beach
The aviation industry faces increasing pressure to reduce its environmental impact, yet standardized methods for evaluating airline sustainability performance remain limited. This study proposes a structured sustainability index designed to benchmark airline environmental strategies using fourteen key performance indicators (KPIs) derived from publicly disclosed corporate sustainability and annual reports. To improve analytical clarity, the KPIs are organized into seven conceptual clusters capturing distinct dimensions of environmental performance: strategic governance and commitment, operational and fleet efficiency, the sustainable aviation fuel (SAF) ecosystem, emissions reduction and climate mitigation outcomes, carbon management and neutralization, energy transition and electrification, and environmental pollution and resource …
Agar-Natural Polymer Composites For Packaging Applications, Alaa Alnatsheh
Agar-Natural Polymer Composites For Packaging Applications, Alaa Alnatsheh
Discovery Day - Daytona Beach
Global plastic production reached 359 million metric tons in 2018, with packaging accounting for about 31% of total use and expected to continue increasing toward 2060. Recycling remains limited, with approximately 66% of recyclable packaging in the United States not being recycled. These challenges have increased interest in biodegradable materials derived from renewable sources. Agar, a polysaccharide extracted from red seaweed, has strong film-forming ability but shows limitations such as low mechanical strength and high water sensitivity. This study investigates agar-based bioplastic films using three formulation approaches: agar-starch (binary), agar-starch-chitosan (ternary), and agar with nanocellulose (nano-enhanced). Films were prepared using …
The Regeneratively Cooled Engine Development (R.E.D.) Project, Joseph Traverso, Sharjeel Malik, Ford Catlin
The Regeneratively Cooled Engine Development (R.E.D.) Project, Joseph Traverso, Sharjeel Malik, Ford Catlin
Discovery Day - Daytona Beach
The Experimental Rocket Propulsion Lab (ERPL) is a student-run organization dedicated to designing, building, and testing experimental rocket engines. With ERPL transitioning toward flight vehicles, developing engines with longer burn times is critical to future club success. One limitation to burn time is an engine’s ability to withstand extreme combustion temperatures, typically in excess of 5000 F. ERPL engines have found success with passive cooling techniques such as ablative, heatsink, and film cooling, but these techniques aren’t suitable for extended burn times. Therefore, ERPL has created the Regeneratively cooled Engine Development (R.E.D) project, with the objective to design, analyze, and …
Is Lane Splitting/Lane Filtering Safe Or Dangerous?, Anastacio Doucas Nolas, Sierra Juliano, Shawn De La Osa, Kimberly R. Williamson
Is Lane Splitting/Lane Filtering Safe Or Dangerous?, Anastacio Doucas Nolas, Sierra Juliano, Shawn De La Osa, Kimberly R. Williamson
Discovery Day - Daytona Beach
This course-based research project examines whether lane splitting and lane filtering are inherently dangerous or whether their safety depends on human factors and traffic conditions. Using published crash, behavioral, and policy literature, the project compares how these motorcycle maneuvers affect riders and other road users across different roadway environments. The analysis distinguishes lane splitting, which occurs between moving lanes of traffic, from lane filtering, which typically occurs at low speeds in stopped or slow traffic queues. Findings suggest that safety cannot be explained by the maneuver alone. Instead, outcomes are shaped by speed differential, driver perception failures, rider workload, intersection …
Advancing Aircraft Maintenance - Smart Mechanic Glasses Proposal, Diego Cordero-Rios, Ilan Soler, Ryan Mercer, Addison Groce, Ruipeng Zhao, Zimo Yang
Advancing Aircraft Maintenance - Smart Mechanic Glasses Proposal, Diego Cordero-Rios, Ilan Soler, Ryan Mercer, Addison Groce, Ruipeng Zhao, Zimo Yang
Discovery Day - Daytona Beach
Commercial aircraft maintenance is increasingly challenged by aging fleets, expanding use of composite materials, labor shortages, and rising expectations for reliability, safety, and cost-effectiveness. Modern aircraft systems demand that maintenance technicians interpret large amounts of technical data to detect complex and hidden defects while navigating limited visibility, distractions, outdated manuals, and inconsistent flows between teams. Traditionally, technicians rely on printed manuals, tablets, or laptops, which increase cognitive load and interrupt task execution, ultimately decreasing productivity, especially in confined physical spaces. Meanwhile, the use of advanced materials, such as composites, creates inspection and repair demands that are more labor-intensive and time-consuming; …
3d Printing In Construction: Technology And Digital Innovation, Zachary Braunstein, Tyler Fritsch, Leah Oberkehr, Ethan Arvidson
3d Printing In Construction: Technology And Digital Innovation, Zachary Braunstein, Tyler Fritsch, Leah Oberkehr, Ethan Arvidson
Discovery Day - Daytona Beach
The study of 3D Printing in Construction: Technology and Digital Innovation examines the growing role of additive manufacturing in transforming traditional construction practices. This literature review explores the evolution of construction 3D printing from early conceptual research on contour crafting to modern automated construction systems that integrate robotics with digital design technologies such as Building Information Modeling. The review highlights practical applications including the design and testing of a 3D printed concrete pedestrian bridge and the increasing use of 3D concrete printing in residential construction to reduce labor demands and project timelines. It also discusses advancements in printable materials, including …
Vibration And Thermal-Vacuum Feasibility For Micro Carbon Fiber Filled Nylon Filament Lunar Applications, Andrew Murphy, Shannon O'Sullivan, Daniel Lopez
Vibration And Thermal-Vacuum Feasibility For Micro Carbon Fiber Filled Nylon Filament Lunar Applications, Andrew Murphy, Shannon O'Sullivan, Daniel Lopez
Discovery Day - Daytona Beach
The proposed work seeks to improve the fundamental understanding of the properties concerning 3-D printing filaments that have potential to be used for lunar applications. The associated properties in focus for the proposed study, vibration and thermal-vacuum-resistance, are fundamental aspects of spaceflight and are critical to mission success for objectives associated with the environmental factors in space. The successful outcome of the proposed work will answer questions relating to the feasibility of micro carbon fiber filled nylon 3-D printing filaments such as Markforged’s Onyx® for application for projects in the Space Technologies Laboratory, including for the development of structures relating …
A Comparative Classical And Data-Driven Facial Analysis Of Wide-Field-Of-View Lens Captures, Andrew Murphy, Giovanni C. Decapua, Anthony M. Cafiso, Max E. Raabe, Kaden E. Van Leuven
A Comparative Classical And Data-Driven Facial Analysis Of Wide-Field-Of-View Lens Captures, Andrew Murphy, Giovanni C. Decapua, Anthony M. Cafiso, Max E. Raabe, Kaden E. Van Leuven
Discovery Day - Daytona Beach
WFOV lenses are becoming popular in facial recognition due to the fact that they enhance subject coverage and improve the chances of detecting target faces. However, wide-angle optics introduce nonlinear distortion around the image periphery, which degrades the performance of recognition pipelines. In this poster presentation, we use WFOV lens captures to analyze facial recognition using classical low-complexity algorithms based on the discrete Fourier transform (DFT), discrete cosine transform (DCT), principal component analysis (PCA), and data-driven learning with convolutional neural networks. Finally, we present computational efficiency, compression, accuracy, and precision of recognizing distorted images with qualitative and quantitative measures.
Advancements In Spacecraft Trajectory Generation Through Matrix Decomposition Techniques, David Stoev, Oshani Jayawardane, Kaitlyn Cavanaugh, Kristiyan Stefanov, Andrew Murphy
Advancements In Spacecraft Trajectory Generation Through Matrix Decomposition Techniques, David Stoev, Oshani Jayawardane, Kaitlyn Cavanaugh, Kristiyan Stefanov, Andrew Murphy
Discovery Day - Daytona Beach
The Circular Restricted Three-Body Problem (CR3BP) is renowned for its intricate and chaotic dynamics, leaving it without a closed-form solution. In this poster, we introduce an innovative approach to determine spacecraft trajectories within the CR3BP framework using matrix factorization techniques. We formulate a matrix equation where the right-hand side vector is constructed from the spacecraft's position and velocity data, while the coefficient matrix is derived from the spacecraft's temporal data. Subsequently, we apply several matrix decomposition techniques, including modified Gram-Schmidt, the Householder technique, and Givens Rotation, to analyze the coefficient matrix and derive the spacecraft trajectories. Finally, we evaluate the …
Hydroquad - A Drone Quadruped Hybrid, Haitish Gandhi, Dheer Chhabria
Hydroquad - A Drone Quadruped Hybrid, Haitish Gandhi, Dheer Chhabria
Discovery Day - Daytona Beach
The HyDroQuad is a hybrid robotic system designed to navigate environments where traditional robots face limitations. By combining a quadrupedal walking mechanism with an aerial drone, the platform is able to walk efficiently on stable terrain and transition to flight when encountering obstacles such as rocks, gaps, or steep slopes. This adaptability makes it a strong candidate for future planetary exploration, where terrain is often uneven and unpredictable. This work focuses on developing and evaluating a functional prototype of the system. A fully integrated platform, HDQ-MK1, was designed and constructed by combining a lightweight multirotor drone with a compact quadruped …
A Myoelectric Prosthesis Utilizing A Convolutional Neural Network And Signal Processing, Hope Lea, Katherine Clark, Francis Genco, Carolyn Ascha Richardson, Tobiah Rosser
A Myoelectric Prosthesis Utilizing A Convolutional Neural Network And Signal Processing, Hope Lea, Katherine Clark, Francis Genco, Carolyn Ascha Richardson, Tobiah Rosser
Discovery Day - Daytona Beach
A Myoelectric Prosthesis Utilizing A Convolutional Neural Network and Signal Processing Commercially available myoelectric prostheses for transradial amputees utilize electromyography (EMG) sensors to observe electrical signals from superficial muscle contractions and control robotic fingers, yet often have flaws regarding adaptability and dexterity. These devices require users to learn awkward muscle patterns, as the EMG placement and gesture recognition does not consider how humans would normally think about moving their hand. Additionally, the number of available gestures is more limited, as the devices are threshold-based and do not sample enough muscles. This work seeks to address these issues by creating a …
Earthquake-Resistant Design And Base Isolation Techniques, Christian George, Jacob Sweeten, Gabriela Cotto, Savion Stewart
Earthquake-Resistant Design And Base Isolation Techniques, Christian George, Jacob Sweeten, Gabriela Cotto, Savion Stewart
Discovery Day - Daytona Beach
Earthquake-resistant design has become a critical feature in construction near active fault lines, where seismic activity is most frequent and potentially destructive. In recent years, technological advancements have significantly improved methods for protecting buildings from earthquake damage. Among these innovations, base isolation systems have appeared as one of the most effective solutions. By decoupling a building from ground motion, base isolators reduce the transmission of seismic forces, helping to prevent structural damage and support building stability during earthquakes. In addition to improving safety, base isolation systems can also reduce long-term costs associated with earthquake-related repairs and maintenance. Base-isolated structures are …
Hurricane-Resilient Construction Practices In The Southeastern United States, Eleanor Hopkins, Jonathan Gildersleeve, Kieran Hemminger, Remingtin Rodriguez
Hurricane-Resilient Construction Practices In The Southeastern United States, Eleanor Hopkins, Jonathan Gildersleeve, Kieran Hemminger, Remingtin Rodriguez
Discovery Day - Daytona Beach
Hurricanes pose a significant threat to infrastructure and communities across the southeastern United States, causing billions of dollars in structural damage each year. High wind speeds, storm surge, and wind-driven rain frequently lead to roof failures, structural collapse, and severe interior water damage. As coastal populations continue to grow, improving the resilience of buildings in hurricane-prone regions has become a critical engineering and planning challenge. This literature review examines hurricane-resilient construction practices and evaluates strategies that improve structural performance during extreme weather events. Key areas of focus include continuous load path structural systems, reinforced roof-to-wall connections, elevated foundations to mitigate …
Plastic Roads And Waste Utilization In Pavements: Recycling Plastic Waste Into Durable Road Construction, Hunter Smith, Caden Hoffer, Robert Kincart, Winston De Feria Weber
Plastic Roads And Waste Utilization In Pavements: Recycling Plastic Waste Into Durable Road Construction, Hunter Smith, Caden Hoffer, Robert Kincart, Winston De Feria Weber
Discovery Day - Daytona Beach
Plastic waste production continues to increase worldwide, creating significant environmental and waste management challenges. With over 350 million tons of plastic waste generated annually, researchers and engineers are exploring innovative methods to reuse materials in sustainable construction practices. To reduce construction waste and make productive use of recycled materials, engineers are investigating utilization applications for plastic waste in pavement systems. This project examines the use of recycled plastic as a modifier in asphalt pavement mixtures to improve road performance while addressing environmental concerns. The objective of this work is to evaluate how incorporating recycled plastics into asphalt mixtures can enhance …
Characterization Of An Ambe Tagged Neutron Source For A 30-Ton Wbls Detector, Rylee Grover
Characterization Of An Ambe Tagged Neutron Source For A 30-Ton Wbls Detector, Rylee Grover
Discovery Day - Daytona Beach
Understanding the detection capabilities of water-based liquid scintillator (WbLS) is critical for its deployment in next-generation neutrino detectors such as THEIA and Phase II of the Deep Underground Neutrino Experiment (DUNE). This study focuses on the characterization and alignment testing of an Americium-Beryllium (AmBe) radioactive neutron source. We plan to dope the 30-ton WbLS detector at Brookhaven National Laboratory (BNL) with Gadolinium (Gd) to improve neutron detection capabilities. This will be tested by the implementation of an AmBe source as a calibration metric. The AmBe source emits neutrons coincident with a 4.4 MeV gamma ray, making it possible to perform …
Catalyst: A Unified Framework For Orbital Debris Risk, Conjunction Analysis, And Space Policy, Tyler Barr
Catalyst: A Unified Framework For Orbital Debris Risk, Conjunction Analysis, And Space Policy, Tyler Barr
Discovery Day - Daytona Beach
Catalyst is an analyst grade mission console and offline simulation service that operationalizes the Embry Riddle MIT Orbital Capacity Assessment Toolbox Monte Carlo (E-MOCAT-MC) for Space Situational Awareness (SSA) aligned assessment, connecting scenario assumptions to time tagged events, quantitative stability indicators, and evidence preserving exports. E-MOCAT-MC serves as the authoritative generator of seeded scenario runs under explicit configuration control, ingesting locally served Two Line Element sets (TLEs) and persisting each run as a structured record containing configuration data, stochastic seeds, event logs, derived metrics, and replayable artifacts for deterministic analysis. Unlike systems that primarily visualize TLEs and object tracks, Catalyst …