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Articles 91 - 120 of 40764

Full-Text Articles in Physical Sciences and Mathematics

Synchrotron X-Ray Diffraction Method For Continuous Strain Analysis Across Heterogenous Material Interface Layers, Sierra Damon Aug 2026

Synchrotron X-Ray Diffraction Method For Continuous Strain Analysis Across Heterogenous Material Interface Layers, Sierra Damon

Discovery Day - Daytona Beach

Synchrotron X-ray diffraction method for continuous strain analysis across heterogenous material interface layers   The transfer of strain across a material interface is a relevant concept to quantify for numerous aerospace applications that involve coatings applied to substrates of different materials, particularly in the field of high temperature materials. X-ray diffraction (XRD) is a metrology technique capable of resolving strain within an arbitrary material by quantifying the shifts of Bragg peaks with respect to an unstrained sample and has seen increased use due to the capability of XRD to perform in-situ measurements on materials in extreme environments. Since different materials have …

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Eliminating Range Constraints For Optical Tracking Of Sub-10 Cm Orbital Debris, James Kirk Aug 2026

Eliminating Range Constraints For Optical Tracking Of Sub-10 Cm Orbital Debris, James Kirk

Discovery Day - Daytona Beach

The growing population of orbital debris, including a significant amount of debris ranging from 1 to 10 cm, has substantially increased the risk to satellites. Due to the sheer number and high velocities, debris ranging from 1 to 10 cm still has the ability to cause mission-ending damage while remaining undetectable by ground-based detection facilities. This study utilizes the NASA Standard Satellite Breakup Model (NASA SSBM), combined with MATLAB, to propagate debris clouds over extended durations, enabling the identification of high-detection zones and debris rings. Using the modeled spacecraft environment, a satellite was positioned below the debris ring altitudes. Lowering …

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Classification Of Sequential Factors In Aviation Accident Cause Prediction, Sophia Nasca, Addyson Wolfe Aug 2026

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. …

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Low-Complexity Polynomial Ring Learning For Quantum Space Assets, Lola Torres Aug 2026

Low-Complexity Polynomial Ring Learning For Quantum Space Assets, Lola Torres

Discovery Day - Daytona Beach

Secure communication for space-based systems requires cryptographic methods that remain both reliable and efficient under strict computational constraints. This work investigates a low-complexity polynomial ring learning algorithm designed for quantum space assets, including satellite–ground communication systems. The project focuses on post-quantum cryptographic principles, where encryption and decryption rely heavily on repeated polynomial operations; this can be computationally expensive with constrained platforms. This is addressed with reformulating polynomial multiplication as a structured linear transformation on coefficient vectors. By representing these operations as matrices with a cyclic structure, the structure allows the use of the discrete Fourier transform (DFT); this will simplify …

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M.O.D.U.S. Modular Optical Design Using Specular Film, Mario Gutierrez, Robert Thibodeau, Emma Show, Desiree Robinson, Lingyuan Meng, Sean Martin, Conner Beeson Aug 2026

M.O.D.U.S. Modular Optical Design Using Specular Film, Mario Gutierrez, Robert Thibodeau, Emma Show, Desiree Robinson, Lingyuan Meng, Sean Martin, Conner Beeson

Discovery Day - Daytona Beach

High-quality parabolic mirrors, which are vital components in reflecting telescopes, are typically bulky, costly, and highly fragile. This experiment explores the feasibility of using specular Class B Mylar as an unconventional, lightweight, and cost-effective alternative. This approach could enable new telescope designs by greatly reducing weight and manufacturing expenses, while also opening options for potential adaptability.   This approach involves using Mylar, a flexible, reflective style of plastic. The mylar is formed into a concave mirror by stretching a sheet over a chamber and depressurizing one side to force the sheet into the necessary curved shape. Multiple designs are being created …

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Small Uas Detection: Threat Intelligence & Risk Management Project, Tyler Johnson Aug 2026

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 …

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Stability Through Chaos: Atmospheric Impact And Control Strategies For Laser Communication, Om Acharya, Mykailla Harper, Mark Vanberschot, Aldir Moreira Aug 2026

Stability Through Chaos: Atmospheric Impact And Control Strategies For Laser Communication, Om Acharya, Mykailla Harper, Mark Vanberschot, Aldir Moreira

Discovery Day - Daytona Beach

Study of Atmospheric Effects and Mitigation Strategies in Free-Space Optical Communication Systems examines the fundamental limitations imposed by atmospheric disturbances on point-to-point laser communication links and evaluates methods to improve link reliability and performance. Free-space optical communication offers high data rates and reduced spectral congestion compared to radiofrequency systems, but its effectiveness is constrained by atmospheric effects including turbulence-induced scintillation, beam wander, absorption, and scattering. These phenomena introduce fluctuations in signal intensity and pointing errors, leading to degraded link stability and increased bit error rates. The work analyzes these atmospheric effects and investigates mitigation strategies that enhance optical link robustness …

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High Tempo Air Operations, Joseph Lipson, Brennan Flanagan, Trevor Sterbens, Brandon Godfrey, Jeremiah Sepich Aug 2026

High Tempo Air Operations, Joseph Lipson, Brennan Flanagan, Trevor Sterbens, Brandon Godfrey, Jeremiah Sepich

Discovery Day - Daytona Beach

Aircraft carrier flight decks are one of the most dangerous work environments in the world, where dozens of aircraft must be moved, fueled, and armed within strict time limits. Currently, Flight Deck Handling Officers track aircraft positions using a physical board with wooden pucks that can be knocked out of place or become outdated during fast-moving operations. This study looks at whether using AI tools helps people design a better digital version of this tracking system. Participants with little design experience were randomly selected and then randomly assigned to one of two groups — one that could use AI tools …

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Humans Vs. Ai: Comparing Approaches To Disaster Response Interface Design, Kelly Nguyen, Olivia Hartmann, Kailey Hrbek, Madeline Nees, Gabrielle Roth, Emily Silliman Aug 2026

Humans Vs. Ai: Comparing Approaches To Disaster Response Interface Design, Kelly Nguyen, Olivia Hartmann, Kailey Hrbek, Madeline Nees, Gabrielle Roth, Emily Silliman

Discovery Day - Daytona Beach

Amphibious emergency support operations involve rapidly changing information, high stress, and significant cognitive demands, which can make decision-making and situation awareness more difficult for operators. When interfaces are poorly designed, they can contribute to issues such as alarm flooding, confusion from incomplete information, and delayed responses, all of which increase operational risk during time-critical disaster situations. This study explores whether using generative AI to assist with interface design will improve performance (output quality and effort) and usability compared to a manual sketch mock-up. Participants were asked to design a dashboard interface to support disaster relief operations following a Category 5 …

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Ai-Driven Scheduling Algorithms For Private Aviation, Tayan Benson, Jessica Buskey, Gabriel Camacho, Caitlyn A. Gabrinowitz Aug 2026

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 …

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From Code To Cube: Interactive Fluid Simulation With Real Time Motion Control, Dominic Ziccardi, Carter Groezinger Aug 2026

From Code To Cube: Interactive Fluid Simulation With Real Time Motion Control, Dominic Ziccardi, Carter Groezinger

Discovery Day - Daytona Beach

This research project explores the use of FluidX3D, an open-source lattice Boltzmann method (LBM) solver, to simulate fluid behavior within a three-dimensional cube container. The system supports both standard water models and rheoscopic fluid visualization, allowing detailed observation of complex flow dynamics in real time. The simulation accurately represents fluid motion, gravity-driven behavior, and rotational response within a bounded cubic domain. The longterm objective is to extend this digital simulation into a physical installation consisting of six synchronized square displays arranged to form a cube. This configuration will create a volumetric illusion of fluid occupying a tangible, handheld structure. An …

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Predicting Passenger Demand On National Flights Departing From Hartsfield-Jackson Atlanta International Airport (Atl) In 2024, Brooklyn Gossett, Ana Yu Wen Aug 2026

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 …

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Navigating Enhanced Exploration Assistance (Nexa), Azhari Abbas, Caleb Fakunle, Ryan Powell, Donovan Livingston Aug 2026

Navigating Enhanced Exploration Assistance (Nexa), Azhari Abbas, Caleb Fakunle, Ryan Powell, Donovan Livingston

Discovery Day - Daytona Beach

NEXA is an artificial intelligence software platform developed to enhance residential security and property monitoring through seamless integration with autonomous drone systems. This research application of advanced AI in surveillance aims to create a standalone solution capable of real-time threat detection and intelligent alert management. By processing visual and sensory data, NEXA facilitates autonomous drone operation with minimal human intervention. Secure communication channels ensure that instant alerts are delivered to property owners and, potentially, law enforcement, improving response times in security incidents, search-and-rescue operations, and perimeter surveillance. Additionally, NEXA is capable of interfacing with commercially available drone platforms and presents …

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An Evaluation Of Machine Learning Models' Efficacy In Determining Uav Spoofing Attacks, Nicolas Machado, Jaxon Selzer Aug 2026

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, …

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String-Of-Pearls Measurements Of Supersonic Plasma Jets Using Magnetospheric Multiscale Satellites, Amelia Koth Aug 2026

String-Of-Pearls Measurements Of Supersonic Plasma Jets Using Magnetospheric Multiscale Satellites, Amelia Koth

Discovery Day - Daytona Beach

High-energy supersonic plasma jets form when the solar wind, which is a flow of charged particles from the Sun, slows down as it encounters Earth’s magnetic shield. Occasionally, the solar wind remains at supersonic speeds as it enters this region. This forms plasma jets that propagate toward Earth; these jets can carry strong magnetic fields, drive magnetic reconnection, and potentially initiate substorms that lead to auroral activity.   Previously studied plasma jets occurred when the interplanetary magnetic field (IMF) points southward. In contrast, this study focuses on northward IMF conditions, which are less understood, yet still capable of producing supersonic jets. …

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Helio: Heliophysics Enhanced Learning For Intelligent Orbits, Kylie Nager, James Kirk Aug 2026

Helio: Heliophysics Enhanced Learning For Intelligent Orbits, Kylie Nager, James Kirk

Discovery Day - Daytona Beach

HELIO: Heliophysics Enhanced Learning for Intelligent Orbits   Satellite constellations operating in near-Earth space are increasingly vulnerable to space weather disturbances, such as solar flares, coronal mass ejections (CMEs), and high-speed solar wind streams, which degrade communications, destabilize attitude control, and accelerate orbital decay. These disturbances directly threaten mission continuity, constellation availability, and space asset survivability. Current protective approaches rely primarily on ground-based alerts and lack integration with broader space domain awareness, which results in programmed reactive protocols that are often initiated too late to prevent performance degradation and asset loss. The HELIO project addresses this gap by turning space-weather forecasts …

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Interplanetary Trajectory Optimization With Reinforcement Learning, Shiloh Cuffe Aug 2026

Interplanetary Trajectory Optimization With Reinforcement Learning, Shiloh Cuffe

Discovery Day - Daytona Beach

This project investigates the application of reinforcement learning (RL) to optimize low-thrust interplanetary trajectory design, focusing on the Earth-Venus transfer leg of the BepiColombo mission. Traditional trajectory optimization methods, such as patched conics and genetic algorithms, often require simplifying assumptions or complex optimization schemes. This work formulates the trajectory design problem as an optimal control problem (OCP) within a Markov Decision Process (MDP) framework, enabling an RL agent to learn efficient transfer strategies under realistic spacecraft constraints. The objective is to develop an autonomous guidance approach capable of replicating or improving upon established mission designs. The spacecraft is modeled as …

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Generalized Cloud-Based Compressible Aerodynamics Calculator And Simulation Web App, Massimo Mansueto, Liam Griesacker, Andres Torres-Figueroa Aug 2026

Generalized Cloud-Based Compressible Aerodynamics Calculator And Simulation Web App, Massimo Mansueto, Liam Griesacker, Andres Torres-Figueroa

Discovery Day - Daytona Beach

The Generalized Cloud-Based Compressible Aerodynamics Calculator and Simulation Web App focuses on the development of a tool to support the analysis, visualization, and teaching of compressible aerodynamics. In the case of most undergraduate aerospace engineering courses, students rely on static equations, charts, and manual calculations, which can make it difficult to conceptualize complex flow phenomena such as shock waves, expansion fans, and nozzle flow. The purpose of this project is to create an accessible platform that integrates a compressible flow calculator, nozzle sizing tool, and interactive simulations into a single educational resource. The application is implemented using modern web development …

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Extending The Essentially Entropic Lattice Boltzmann Method To Three-Dimensional Turbulent Flows, Michael Derderian Aug 2026

Extending The Essentially Entropic Lattice Boltzmann Method To Three-Dimensional Turbulent Flows, Michael Derderian

Discovery Day - Daytona Beach

The Entropic Lattice Boltzmann Method (EELBM) has demonstrated strong numerical stability and accuracy for two-dimensional simulations, particularly at higher resolutions where the entropic formulation introduces only minimal stabilizing turbulent viscosity and eventually converges to the Lattice Bhatnagar–Gross–Krook (LBGK) formulation. This built-in stabilization can be interpreted as an implicit large-eddy simulation (LES) model, allowing EELBM to capture complex turbulent behavior without requiring explicit subgrid-scale closures. While these advantages have been thoroughly validated in 2D, understanding how the entropic constraint regulates dissipation in three dimensions is essential for assessing EELBM’s suitability for practical, turbulence-dominated applications. This work focuses on the development and …

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Feasibility Of High-Throughput Onboard Ai For Mars Rovers Under Solar Constraints, Aashman Gupta Aug 2026

Feasibility Of High-Throughput Onboard Ai For Mars Rovers Under Solar Constraints, Aashman Gupta

Discovery Day - Daytona Beach

This project evaluates the feasibility of sustained onboard AI autonomy for a solar-powered Mars rover by directly linking solar energy availability to achievable compute performance. While Mars solar irradiance and edge computing performance have been studied independently, no unified framework currently couples surface power generation to autonomy throughput in an experimentally validated manner. The project will begin with a simulation of solar power generation for a 1 m² rover-mounted array across a Martian sol, accounting for seasonal variation, dust opacity, and array configuration (fixed versus sun-tracking). The resulting power profile will then be coupled to representative compute platforms running autonomy …

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An Energy-Aware Meta-Learning Framework For Real-Time Lunar Rover Localization Via Adaptive Algorithm Selection, Jose Demedeiros, Garrett Seyler Aug 2026

An Energy-Aware Meta-Learning Framework For Real-Time Lunar Rover Localization Via Adaptive Algorithm Selection, Jose Demedeiros, Garrett Seyler

Discovery Day - Daytona Beach

This work proposes an energy-aware meta-learning framework that selects the single most suitable localization algorithm for a lunar rover, per scene, using only monocular imagery and orbital maps. The goal is to achieve sub-meter accuracy while minimizing onboard compute and energy consumption. We assemble a suite of seven lunar-relevant algorithms spanning relative and absolute localization, including monocular ORB-SLAM3, LuVo homography-based visual odometry, Censible cross-view matching with orbital imagery, crater-based methods (LunarNav and ShadowNav), monocular horizon navigation with a DEM, and DROID-SLAM. Relative methods provide incremental motion updates, while absolute methods deliver global pose fixes; an Extended Kalman Filter fuses these …

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A System Safety Approach To Assuring Artificial Intelligence Enabled Functions In Civil Aviation, Evan Bear, Quinn Galen Aug 2026

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 …

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A Hybrid Llm-Srgm Framework For Ai-Enabled Reliability Assessment In Safety-Critical Software Systems, Caleb Stone, Shrenik Jadhav Aug 2026

A Hybrid Llm-Srgm Framework For Ai-Enabled Reliability Assessment In Safety-Critical Software Systems, Caleb Stone, Shrenik Jadhav

Discovery Day - Daytona Beach

Ensuring the reliability of software intensive and safety critical systems is a persistent challenge across aerospace, defense, transportation, and other mis- sion focused domains. Traditional software relia- bility growth models (SRGM) provide useful quanti- tative insight into defect discovery trends, but they rely mostly only on numerical failure data and do not use the rich contextual information contained in test logs, anomaly reports, and engineering notes. This paper presents a hybrid framework that com- bines semantic features extracted by a large lan- guage model (LLM) with a non-homogeneous Pois- son process (NHPP) based software reliability growth model. The LLM analyzes …

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Cars Imass - Comparing Llm Vs Human Operator Effectiveness In Multi-Agent Swarm Coordination, Gatlin Nelson Aug 2026

Cars Imass - Comparing Llm Vs Human Operator Effectiveness In Multi-Agent Swarm Coordination, Gatlin Nelson

Discovery Day - Daytona Beach

Title: Dual-Perspective Risk Analysis for Human-LLM Decision Comparison in UAV Swarm Navigation   Unmanned aerial vehicle (UAV) swarms operating in low-altitude wireless network environments encounter localized disruptions that degrade positioning and navigation metrics. These disruptions are modeled as geographic failure zones with defined boundaries. A UAV discovers a zone by entering it and observing degraded performance on its onboard systems. This work assumes that affected UAVs can autonomously retreat to safety using onboard sensors and focuses on the subsequent rerouting decision. Once recovered, the system generates candidate repositioning points surrounding the vehicle, each scored using Conditional Value-at-Risk (CVaR). A human operator …

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Multi-Dimensional Particle-In-Cell With Monte Carlo Collisions (Pic-Mcc) Simulation For Visualizing Plasma Flow And Secondary Ionization In Constricted-Anode Geometries, Parth Thakar Aug 2026

Multi-Dimensional Particle-In-Cell With Monte Carlo Collisions (Pic-Mcc) Simulation For Visualizing Plasma Flow And Secondary Ionization In Constricted-Anode Geometries, Parth Thakar

Discovery Day - Daytona Beach

Constricted-anode plasma sources generate locally intensified electric fields that enhance ionization near the anode, making them valuable in propulsion and laboratory plasma systems. However, the narrow geometry produces complex charge accumulation and secondary ionization effects that remain difficult to measure experimentally. To address this challenge, our research develops and applies a multi-dimensional Particle-in-Cell with Monte Carlo Collisions (PIC-MCC) simulation of a DC discharge in 1-D, 2-D, and 3-D configurations that model a constricted-anode device. PIC-MCC is a first-principles method that tracks electrons and ions individually while computing self-consistent electric fields and incorporating energy-dependent collision processes. This approach enables direct visualization …

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Phaëthon System, Brady Roudabush, Lauren Gallo, Emelia Thompson, Jacob Woods Aug 2026

Phaëthon System, Brady Roudabush, Lauren Gallo, Emelia Thompson, Jacob Woods

Discovery Day - Daytona Beach

Phaëthon System is the project name for the Search and Rescue Drone Initiative. This initiative will improve the current search and rescue drone industry by introducing new techniques to get through dense forest canopies and other places where an overhead view is not useful. The Phaëthon System uses a swarm of drones that can penetrate under the tree canopy to map and search with the utmost efficiency and safety for rescuers. A command drone is launched to survey the overall search area, and set up a communications and data link. The next component is then released, which is a swarm …

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Real-Time Fused Sensor System For Early Onboard Detection Of Weather Phenomena, Sanjana Singh Aug 2026

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 …

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Reimagining Wind Based Sea Travel With Vertical Axis Wind Turbines, Julian Goins Aug 2026

Reimagining Wind Based Sea Travel With Vertical Axis Wind Turbines, Julian Goins

Discovery Day - Daytona Beach

In the realm of Nautical vehicles, aside from the occasional outliers like rarely used coal steamboats, experimental solar powered ships, or the military grade nuclear vessels, the vast majority of ships run off diesel-powered engines. The unsustainability of such methods will need to be addressed for the security of our planet’s future due to the limited and destructive nature of fossil fuels, much like it already is in many other fields. To that end, this project gains inspiration from the past and looks toward harnessing the power of the wind. In recent times, most sail boats are equipped with some …

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Investigating The Spatial Scales Of Ionospheric Irregularities Using Wavelet Analysis, Nash Mcleod Aug 2026

Investigating The Spatial Scales Of Ionospheric Irregularities Using Wavelet Analysis, Nash Mcleod

Discovery Day - Daytona Beach

Investigating the Spatial Scales of Ionospheric Irregularities Using Wavelet Analysis:   Ionospheric radio wave scintillation arises from plasma density irregularities in Earth’s ionosphere. Consequently, rapid fluctuations occur in the phase and amplitude of Global Navigation Satellite System (GNSS) signals and can impact communication and navigation systems. These irregularities span from a wide range of spatial and temporal scales and evolve dynamically under the influence of magnetosphere-ionosphere (MI) processes. We investigate phase and amplitude scintillation events using Continuous Wavelet Transform (CWT) to study the spatial evolution of ionospheric irregularities. These irregularities are thought to be formed via different plasma mechanisms such as …

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Effect Of Anode Size On The Properties Of Constricted Hollow Anode Pulsed Plasma Source, Nirav Patel, Garret Seckinger Aug 2026

Effect Of Anode Size On The Properties Of Constricted Hollow Anode Pulsed Plasma Source, Nirav Patel, Garret Seckinger

Discovery Day - Daytona Beach

With the advent of ion thrusters, burns requiring large velocity changes can be performed with a fraction of the propellant required by traditional chemical rocket engines. However, current ion thrusters produce thrust in the order of millinewtons and thus cannot be viable for launching vehicles or burns requiring velocity changes in a small amount of time. Furthermore, current ion thrusters experience grid and component erosion, where the two grids at the termination of the nozzle slowly erode due to particle impact, and the hot electrodes degrade due to high thermal load. This limits the life of ion engines, which require …

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