Engineering Commons^™

Numerical Studies Of Semiclassical Light Storage Using The Coherent Atomic Transfer Function, Zachary T. Johnson

Theses and Dissertations

Quantum communication through photons relies on photonic storage to preserve quantum states. However, when photons interact with matter, quantum information becomes distorted. A recently developed semi-classical analytical model predicts output light pulses from an electromagnetically induced transparency (EIT) system. Using the predictions, the model known as the Coherent Atomic Transfer (CAT) Function, is capable of predicting the stored pulse or reconstructing the original pulse. Using numerical convolution and deconvolution with the CAT function as an analog of the point spread function of Fourier optics can provide insights on the effects of EIT storage on the retrieved pulse. Blind deconvolution is …

Transfer Efficiencies Of Surface-To-Surface Transport Of Micron-Sized Actinide Surrogate Particles, Austin R. Powell

Theses and Dissertations

Particle effluent of varying sizes is released during routine activities within laboratory environments and these particles can come in contact with a wide range of surfaces. Particles of micron size or smaller can be especially pervasive and can transfer between multiple subsequent surfaces, leading to the progressive contamination of a laboratory. Understanding the transport dynamics of micron sized particles will help inform facility personnel of the possibility of contamination by these potentially hazardous materials of interest. In this research, the transfer efficiency of micron sized surrogate actinide particles (Europium-doped Gadolinium Oxysulfide (EGOS)) is measured for multiple materials, between two particle …

Heterogeneous Boid Swarm Performance Under Environmental And Neighbor Communication Link Variability, Jonathan C. Oxborrow

Theses and Dissertations

Artificial swarms are of growing interest in numerous fields and use cases. As their utilization increases drones and robots with different capabilities will be required to coordinate for task completion thus creating heterogeneous swarms. Swarm individuals generally communicate with all neighbors inside their sensor range generating a significant amount of message traffic. Previous research of a heterogeneous group in a non-physical environment has shown that restricting communication to only one neighbor of each different capability maintained performance. This work applies that finding to a heterogeneous boid swarm with the addition of varied environmental conditions. The swarm is comprised of three …

Analysis Of Nuclear Security And Safety Integration Using Survey Responses And Pairwise Comparison Methods, Sheila V. Gbormittah, Theodore A. Thomas, Jason Timothy Harris

International Journal of Nuclear Security

Integrating nuclear security and safety is important for implementing and sustaining nuclear technology because it promises improved and effective management. This integration is an ongoing effort to ensure that both work together with minimal conflicts. This research aimed to determine the preferred level at which nuclear security and nuclear safety integrate by using the pairwise comparison methods of decision-making. This methodology used survey responses from women nuclear professionals to identify the most-desired criteria at three levels: strategic, operational, and cultural. The strategic level includes actions that government officials and regulators can take. The operational level encompasses actions that deliver the …

Wright State University's Celebration Of Student Research, Scholarship & Creative Activities From Thursday, March 13, 2025, Wright State University

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Abstract Books

The student abstract booklet is a compilation of abstracts from students' oral and poster presentations at Wright State University's Celebration of Student Research, Scholarship & Creative Activities on March 13, 2025.

Refining Chlorosulfonation Methods For The Synthesis Of A Perfluoroalkyl Arylsulfonimide (Pfsi) Monomer, Ainsley P. Foster, Ben Varney, Hua Mei

SPARK Symposium Presentations

Proton-exchange membrane (PEM) fuel cells are sources of energy that are clean, quiet, and highly responsive to changes in power needs, making them promising for use in automobiles and other portable power devices. The electrolyte of a PEM cell–the layer responsible for conductivity–is a polymer membrane, commonly consisting of perfluoroalkyl sulfonic acid (PFSA) polymers. In place of the PFSA polymers, perfluoroalkyl arylsulfonimide (PFSI) polymers are expected to improve the efficiency of PEM fuel cells with better stability and proton conductivity. The trifluovinylether (TFVE) aryl perfluorosulfonamide monomer is a new PFSI monomer proposed to fulfill these benefits once polymerized. The previous …

Practical Estimation Of Action-Generation Mechanisms In Repeated Games, Vladimer Kellachow Iii

Theses and Dissertations

The goal of this research is to gain insight into how players of a game learn their strategy during the course of repeated play. The study employs the Experience Weighted Attraction (EWA) model, developed by Dr. Colin F. Camerer and Dr. Teck-Hua Ho, as the foundational behavioral framework. Using historic observed strategy decisions, the parameter values that define an opponent’s learning process are updated using various inference methods.

Atmospheric Water Generation: Experimental Observations And Assembly Of An Artificial Neural Network, Houston Hoss Anderson

Theses and Dissertations

This research investigated the performance of a Tsunami T50 Vapor Compression Cycle styled Atmospheric Water Generation (AWG) machine operated under ambient conditions in Dayton, Ohio. Water yield from the device was measured volumetrically and these values are paired with respective weather data, collected from a local monitoring station, to build an Artificial Neural Network in MATLAB and JMP software. Water yield varied over the course of this study but averaged 1.2L and maxed at 5L for 4-hour operating periods. This work is part of a 3-year project; future data is needed to enhance both training and validation of the model …

Improving Smartphone Gnss Jammer Localization With Cloud-Based Environmental Occlusion Modeling, Glenn H. Jones

Theses and Dissertations

The advancement of Global Navigation Satellite System (GNSS) technology in modern smartphones has made these devices pervasive in both civilian and military applications. Although smartphone GNSS chipsets are more susceptible to jamming and spoofing than military grade hardware, smartphone networks offer an underutilized opportunity to detect and mitigate threats to position, navigation, and timing (PNT) services essential to the Department of Defense (DoD) and civilian first responders. Traditional methods for geolocating ground-based jamming sources using smartphone GNSS often fail in environments with dense vegetation or significant occlusions, resulting in substantial localization errors.

A Multi-Objective Reinforcement Learning Framework For Title Autonomous On-Orbit Inspections, Austin C. Reynolds

Theses and Dissertations

The rapidly evolving landscape of space operations necessitates dynamic and autonomous systems to address complex challenges such as Resident Space Object (RSO) inspections. This research explores the application of a Multi-Objective Reinforcement Learning (MORL) framework to rendezvous and proximity operations (RPO), enabling agents to balance conflicting objectives like time efficiency, fuel conservation, and information gain. Unlike traditional reinforcement learning, MORL allows dynamic reweighting of objectives without retraining, offering adaptability and efficiency in multi-objective environments. The study demonstrates MORL's capabilities through custom 2D and 3D simulations of Hill-Clohessy-Wiltshire (HCW) environments and comparing its performance to traditional RL in RPO scenarios. Tasks …

Lethality And Survivability Of Autonomous Self-Sensing Uavs, Jeffrey T. Wilson

Theses and Dissertations

Unmanned Aerial Vehicles (UAVs) have seen increased usage over the past two decades during the Global War on Terrorism (GWOT), operating in low-risk environments against dispersed enemies with minimal counter-drone capabilities. However, as the U.S. military shifts focus to Multi-Domain Operations (MDO) and Large Scale Combat Operations (LSCO), UAVs face significantly higher risks, including frequent and successful attacks, as well as the exploitation of their technology. Battle damage assessment (BDA) is not new; however, autonomous self-assessment by UAVs represents a novel advancement. Currently, UAV BDA relies on manual inspection, requiring approximately eight hours per drone. By adopting self-sensing technology, UAVs …

Molecular Scale Investigations Of Interactions Between Pfas And Concrete, Eric E. Keeler

Theses and Dissertations

Per- and polyfluoroalkyl substances (PFAS), widely referred to as “forever chemicals,” exhibit high environmental persistence and potential health risks due to their robust carbon-fluorine bonds. These substances are prevalent in aqueous film-forming foams (AFFF), used in industrial and military applications, and are known to contaminate environmental surfaces, including concrete. This study aims to characterize the molecular-level interaction energies of six PFAS species—PFOA, PFOS, PFHxS, PFHxA, 6:2 FTS, and PFBS—with calcium silicate, a key component of concrete, using density functional theory (DFT) calculations. Change in Gibbs free energy (ΔG) was determined for each of the interactions, revealing negative ΔG values for …

On The Exploration Of Crystallographic Anisotropy And Defects In Shock Loading Using Molecular Dynamics, Benjamin P. Helman

Theses and Dissertations

The impact of crystallographic orientation, grain boundaries, and vacancies on the shock behavior of aluminum was investigated using molecular dynamics simulations. Shock loading in the [001], [011], and [111] directions was explored, revealing anisotropic behavior in shock speed, melting, dislocation density, and unique phase changes. The Hugoniot elastic limit in the [100], [110], and [111] directions was calculated as 23.2 GPa, 24 GPa, and 18.4 GPa respectively. These results were found to be an order of magnitude larger than the compressive yield strength computed at equilibrium. Additionally, metastable melting in the [011] and [111] directions occurred roughly 1000 K below …

Improving Zero Shot Learning By Linking Multi-Label Cnns With Llms, Michael A. Wegner

Theses and Dissertations

Classifying previously unseen objects poses a significant challenge for traditional computer vision algorithms, which rely on extensive labeled training data. Zero-shot reasoning offers a way to overcome this limitation. This research explores a novel method for image recognition using the Animals with Attributes 2 (AWA2) dataset as a proof of concept. A multi-label ResNet50 model predicts core attributes like color, ear shape, or number of limbs. Those attributes then feed into ChatGPT which leverages its extensive knowledge base to classify the animal based on the provided attributes. This novel approach skips the need to train on every possible class. Instead, …

Jamming-Tolerant Low-Rate Wireless Personal Area Network For Detection Sensor Networks, Michael A. Eddy

Theses and Dissertations

This research evaluates the impact of electronic warfare, particularly jamming, on an audio-based drone detection wireless sensor network (WSN) using Monte Carlo simulations. A six-node IEEE 802.15.4 network, with five edge nodes and a central sink, is tested against jamming probabilities ranging from 0-100% in 5% increments across 30 iterations per configuration. Results show that packet delivery ratio (PDR) degrades linearly at approximately 20% per jammed node, while detection performance often exceeds PDR. Even at 80% jamming, detection success rates remain above 57%, highlighting resilience despite network degradation. The study reveals that jamming effectiveness depends on node placement relative to …

Performing Requirements Specification And Analysis Through Open Generative Pre-Trained Transformers, Harvey J. Hurst

Theses and Dissertations

Every acquisition program begins with a requirement, and for those programs to succeed, robust requirements engineering (RE) must be implemented. RE encompasses eliciting, analyzing, specifying, and validating requirements—a critical process throughout a program's lifecycle. Despite its importance, RE faces challenges such as scope creep, ambiguity, redundancy, and inadequate automation support, often exacerbated by reliance on historical data. To address these issues, this thesis leverages advancements in Generative Technology, particularly large language models (LLMs) such as Generative Pre-Trained Transformers (GPTs). This research developed two GPT-based tools: the Single Requirement Analysis Tool and the Set of Requirements Analysis Tool. These tools were …

Early-Phase Cost Estimation For Department Of Defense Construction Projects Via Artificial Neural Networks: Implications And Policy Recommendations For Artificial Intelligence Integration, Kobe T. Thompson

Theses and Dissertations

The Department of Defense lost over 500 million dollars between 2016 and 2024, partially due to poor early cost estimates resulting in cost overruns. practice for cost estimation relied on parametric techniques that incorporate historical data, subject matter experts in cost estimating, and predictive software applications. The main motivation for this study was to assess the viability of artificial neural networks as a means of providing a more accurate cost estimate in the early design phases of a construction project. The dataset initially contained approximately 48,000 data points from a database of various Air Force projects, including maintenance, repair, minor …

Material Classification With Spectropolarimetric Lidar, Alexander J. Watson

Theses and Dissertations

A method for characterizing unknown targets using a hyperspectral polarimetric light detection and ranging (LiDAR) system is presented. Light reflected from manmade objects tends to be more polarized than light reflected from objects in the natural world. As such, polarization measurements can be used in remote sensing applications to differentiate artificial and natural objects. Previous works have attempted to characterize objects through passive polarimetric imagery. Methods developed by Cain and Lemaster and Cunningham facilitate reconstruction of the Stokes Vector from returning light. Martin used multispectral polarimetry to classify targets when the angle of incidence (AOI) is close to 0º. Here, …

Symbology Detection And Numerical Recognition For T-38 Heads-Up Display Recordings, Ben T. Hepner

Theses and Dissertations

The extraction of symbology and numerical data from the T-38 Heads-Up Display (HUD) enhances post-flight analysis and supports real-time decision-making. This research develops a deep learning pipeline using YOLO-based object detection and Optical Character Recognition (OCR) to analyze HUD video data. Model evaluations showed mAP0.5:0.95 ranging from 0.422 (YOLOv11m, hard test set) to 0.696 (YOLOv8m, medium test set), demonstrating robust symbology detection. Numeric detection performed well (mAP_0.5:0.95 = 0.764), but OCR struggled with glare and resolution limitations, achieving a recognition accuracy of 17.35%. These results validate deep learning for HUD data extraction but highlight the need for improved robustness …

Proximal Policy Optimization Applied To The Beyond Visual Range Air Combat Maneuvering Problem, Daniel B. Joseph

Theses and Dissertations

Artificial intelligence (AI) grows ever-more important in warfighting. Emerging technologies allow for the use of AI to control aircraft and weapons systems. This research investigates the application of reinforcement learning (RL) through the Proximal Policy Optimization (PPO) algorithm to a two-versus-two (2v2) beyond-visual-range (BVR) air combat maneuvering problem (ACMP). Implemented in the Advanced Framework for Simulation, Integration, and Modeling (AFSIM), the methodology frames the engagement as a Markov decision process, wherein an autonomous RL agent learns continuous control decisions—throttle, pitch, roll, and yaw—under a cooperative communication scheme. A multi-phase curriculum-learning approach facilitates the progressive acquisition of flight stability, weapon deployment, …

Analyzing Lf/Vlf Lightning Waveforms To Estimate D-Region Electron Density Profiles: Process, Application, And Comparison, William R. Smith

Theses and Dissertations

Lightning waveforms in the low frequency (LF; 30-300 kHz) and the very low frequency (VLF; 3-30 kHz) can be exploited to produce data-driven ionospheric Dregion electron density profile (EDP) estimates with significantly higher spatial and temporal coverage than previously available. The lightning waveforms used in this paper are signals detected in the LF/VLF of negative cloud-to-ground lightning by the Earth Networks Total Lightning Detection Network. Each waveform contains a ground wave and a time-delayed ionospheric reflection. The time delay between the ground wave and ionospheric reflection has previously been used to estimate a single specular reflection altitude, where LF/VLF emissions …

Choosing Robust Leadership: Encompassing The Best-Of-N Model And Swarm Intelligence Optimization For Heterogeneous Multiple Autonomous Unmanned Aerial Vehicle Systems, Kudamuhandiramlage Harith Kolitha Warnakulasooriya

Shelby Hall Graduate Research Forum Presentations

Presentation slides for a presentation given at the 1st annual Shelby Hall Graduate Research Forum at the University of South Alabama.

Thermal Stability Analysis Of Aqueous Ionic Amines For Sustainable Co2 Capture, Li Hua Zang, Keegan Everitt, Kevin West, Brooks D. Rabideau, Breanna Dobyns, James Davis

Shelby Hall Graduate Research Forum Posters

In closed air cabin atmospheres such as those of spacecraft, CO₂ accumulation jeopardizes crew respiratory function and may gradually affect sensitive equipment, making effective air revitalization critical. Traditional CO₂ capture methods like monoethanolamine (MEA) efficiently capture CO₂ but suffer from high volatility, leading to solvent loss and unpleasant odor, as well as corrosion and degradation, requiring frequent replacement. These flaws demand eco-friendly, durable alternatives. This study addresses these limitations by exploring a series of aqueous ionic amines (AIAs), salts similar to MEA in CO₂ capture efficiency but with improved thermal stability—crucial for preventing degradation under high regeneration temperatures and prolonged …

Effect Of Pre-Adsorbed Species On High-Pressure Adsorption Of Methane In Zeolite 5a Using Grand Canonical Monte Carlo (Gcmc) Simulations, Kanhamardi Lao, Brooks D. Rabideau

Shelby Hall Graduate Research Forum Posters

Natural gas upgrading, which removes impurities from methane (CH4), is essential for industrial applications, including liquefied natural gas (LNG) production and power generation, as well as for residential use. Removing non-hydrocarbon impurities such as carbon dioxide (CO2), nitrogen (N2), and water vapor (H2O), among others, along with separating heavier hydrocarbon gases from raw natural gas, is required to achieve high- purity methane and prevent pipeline corrosion. Zeolite 5A is a microporous aluminosilicate material with a pore size of approximately 5 Å, containing sodium and calcium cations that balance the framework’s negative charge. Its structure offers high thermal stability and a …

Modelled Flooding Impacts On Lower Fish River Watershed, Sebastian Loschner

Shelby Hall Graduate Research Forum Posters

This study investigates the impacts of compound flooding in the Lower Fish River watershed, Baldwin County, Alabama, with a focus on the potential effects of sea level rise due to climate change. Coastal flooding, particularly in smaller watersheds, is a growing concern as it results from the interaction of multiple factors, including rainfall, tidal changes, and extreme weather events. Compound flooding, which involves multiple flood drivers, is expected to worsen with climate change, as increased precipitation and rising sea levels create heightened flood risks. However, existing research on compound flooding predominantly focuses on large-scale watersheds, leaving a knowledge gap in …

Treating Ground Water For Agricultural And Individual Consumption, Gabby Miller, Bronson Scott, Michael Clawson

Biomedical Engineering

This project, conducted in collaboration with Cal Poly seniors and Da Vinci High School students, aims to develop a solar-powered groundwater purification system. This system is designed to provide clean water for agricultural use and individual consumption, addressing the growing concerns of groundwater contamination and accessibility needs. The final prototype integrates a gravity filtration system combined with chemical purification, utilizing aluminum sulfate and chlorine to remove particulates, bacteria, and organic compounds.

The research phase involved an extensive review of groundwater contamination issues, existing filtration technologies, and market analysis. Key design constraints included cost-effectiveness, ease of maintenance, and minimal energy consumption, …

Smart Highway Construction Site Monitoring Using Artificial Intelligence, Mehran Mazari, Yahaira Nava-Gonzalez, Ly Jacky N. Nhiayi, Mohamad H. Saleh

Mineta Transportation Institute

Construction is a large sector of the economy and plays a significant role in creating economic growth and national development,and construction of transportation infrastructure is critical. This project developed a method to detect, classify, monitor, and track objects during the construction, maintenance, and rehabilitation of transportation infrastructure by using artificial intelligence and a deep learning approach. This study evaluated the performance of AI and deep learning algorithms to compare their performance in detecting and classifying the equipment in various construction scenes. Our goal was to find the optimized balance between the model capabilities in object detection and memory processing requirements. …

Metal Nitrides As Cathode Hosts For Lithium-Sulfur Batteries, Hai-Ji Xiong, Cheng-Wei Zhu, Ding-Rong Deng, Qi-Hui Wu

Journal of Electrochemistry

Lithium-sulfur batteries are considered as one of the potential solutions as integrating renewable energy systems for large-scale energy storage because of their high theoretical energy density (2600 Wh·kg^–1) and specific capacity (1675 mAh·g^–1). Currently, various strategies have been proposed to overcome the technical barriers, e.g., “shuttle effect”, capacity decay and volumetric change, which impede the successful commercialization of lithium-sulfur batteries. This paper reviews the applications of metal nitrides as the cathode hosts for high-performance lithium-sulfur batteries, summarizes the design strategies of different host materials, and discusses the relationship between the properties of metal nitrides and their …

Enhancing Cycle Life Of Graphite ‖ Lifepo4 Batteries Via Copper Substituted Li2Ni1-XCuXO2 Cathode Prelithiation Additive, Jian-Ming Zheng, Jing-Wen Zhang, Tian-Peng Jiao

Journal of Electrochemistry

Lithium nickel oxide (Li₂NiO₂), as a sacrificial cathode prelithiation additive, has been used to compensate for the lithium loss for improving the lifespan of lithium-ion batteries (LIBs). However, high-cost Li₂NiO₂ suffers from inferior delithiation kinetics during the first cycle. Herein, we investigate the effects of the cost-effective Cu substitution of Li₂Ni_1-xCu_xO₂ (x = 0, 0.2, 0.3, 0.5, 0.7) synthesized by high-temperature solid-phase method on the structure, morphology, electrochemical performance of graphite‖LiFePO₄ battery. The X-ray Diffraction (XRD) refinement result demonstrates that Cu substitution strategy is favorable …

Sno2 Particles Embedded Into Carbon Coated Mesoporous SioX Rod As High Volumetric Capacity Anode For Lithium-Ion Batteries, Jia-Lin Guo, Ni-Ni Li, Peng Zheng

Journal of Electrochemistry

Due to the high capacity and moderate volume expansion of silicon protoxide SiO_x (160%) compared with that of Si (300%), reducing silicon dioxide SiO₂ into SiO_x while maintaining its special nano-morphology makes it attractive as an anode of Li-ion batteries. Herein, through a one-pot facile high-temperature annealing route, using SBA15 as the silicon source, and embedding tin dioxide SnO₂ particles into carbon coated SiO_x, the mesoporous SiO_x-SnO₂@C rod composite was prepared and tested as the anode material. The results revealed that the SnO₂ particles were distributed uniformly in the …