Engineering Commons^™

Development Of A Homogenized Material Model For Carbon Fiber–Aluminum Transition Joints Using Fea And Optimization, Nicholas M. Couch

All Theses

The integration of metals and composites in automotive structures improves manufacturability and overall structural performance. The proposed Ultrasonic Additive Manufacturing (UAM) joint provides a promising solution for joining aluminum and carbon fiber; however, modeling its behavior across an entire vehicle can be computationally expensive. To address this challenge, a homogenized material card is developed to efficiently capture the joint’s mechanical response while maintaining computational efficiency. A novel characterization method is implemented, employing implicit simulations and optimization techniques to determine the effective material properties of the UAM transition joint. This approach enables rapid iteration of material parameters, facilitating the efficient evaluation …

Evaluating (Bio)Degradation Of Carbon Tetrachloride In Fe(Iii)-Reducing Environments, Adam Rogers

All Theses

Understanding degradation of carbon tetrachloride in-situ is vital for many remediation projects across the world, yet conclusive evidence of its feasibility is lacking in previous studies.

The main objective of this research is to assess the potential for carbon tetrachloride attenuation by biological, abiotic, and combined processes in a Fe(III)-reducing aquifer. In doing so, it assesses the effect of pH and stoichiometric ratio on abiotic degradation of carbon tetrachloride using various reducing agents, evaluates iron-mediated versus direct biotic degradation of carbon tetrachloride using pure cultures under resting and growth conditions, and characterizes the effects of culture strain, electron acceptors and …

Bike/Ped Data Collection And Model Calibration, Eirini Stavropoulou, Dionysios Tzamakos, Nikiforos Stamatiadis, Reginald Souleyrette, Teng Wang

Kentucky Transportation Center Research Report

Motivated by an uptick in pedestrian and bicycle traffic, as well as the inclusion of pedestrian and bicyclist weights in the Strategic Highway Investment Formula For Tomorrow, the Kentucky Transportation Cabinet (KYTC) has made significant investments in transportation facilities for nonmotorized users. Despite an intensified focus on the needs of nonmotorized users, KYTC has not yet established a formal program to track the number of people walking, biking, skateboarding, and using micromobility devices statewide. Based on a review of methods and technologies for counting nonmotorized users; analysis of counting programs established by local, state, and regional transportation agencies; and a …

Congestion And Travel Time Reliability Performance Measures For Shift 2026, Mei Chen, Eugene Antwi, Xu Zhang

Kentucky Transportation Center Research Report

Researchers obtained and processed probe speed data from HERE Technologies and integrated them with the Kentucky Transportation Cabinet’s highway inventory to develop congestion and travel time reliability performance metrics. This report summarizes analyses conducted using HERE speed data for 2022 – 2023. HERE data were processed using an established methodology, after which they were aligned with Kentucky’s highway inventory network. Analysis found that 2022 – 2023 HERE data offer significant improvements in coverage and quality over previous years. For locations that lacked sufficient data, researchers used HERE’s speed model to estimate hourly speeds. Data were used to calculate congestion and …

Traffic Prediction For Research And Education Networks: Anomaly-Aware Deep Learning And Benchmarking, Mohammad Arafath Uddin Shariff

School of Computing: Dissertations, Theses, and Student Research

Research and Education Networks (RENs) and High-Performance Computing (HPC) environments are critical infrastructures for modern scientific discovery, demanding sustained high-throughput and low-latency data transfers. Unlike commercial networks, RENs exhibit unique traffic characteristics, including predominant “elephant flows,” inherent burstiness, and complex temporal-spatial dynamics often decoupled from human-driven cycles. Traditional traffic forecasting methods, tailored for commercial Wide Area Networks (WANs), consistently fail to capture these distinct REN dynamics, leading to inefficient resource management and potential impediments to scientific progress.

This thesis addresses this critical gap by developing and validating a robust, scalable, and anomaly-aware traffic forecasting framework specifically tailored for REN/HPC networks. …

Hardware And Software Design For A Portable Surgical Training Simulator, Victoria Nelson

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

More than 51 million surgeries are performed on patients annually in the United States. That number grows to 310 million surgeries performed globally each year. Most surgeons go through a minimum of five years of residency – where they train and hone their surgical skills. It is important during this time, and throughout their careers, that they get plenty of practice. Surgical training is time intensive, expensive, and frequently under-resourced. There are finite amounts of surgical training modules for students to share at their facilities. The problem of getting adequate surgical training time continues to exist after surgeons begin their …

Owl Solar-Powered Link: Duck Radio Mesh For Autonomous Monitoring, Jaden Tran, Shane Williams

Electrical Engineering

The Solar Duck Sensor Node transforms a standard DuckLink into a fully self-sustaining environmental monitor. A compact solar panel / power bank module plugs into the power ports of both the DuckLink and the Raspberry Pi Zero 2 W, keeping them charged through day-night cycles. The Pi Zero 2 W will perform local processing of sensor data. Sensor output will come from the Raspberry Pi AI Camera and its object detection capabilities. This output will be distilled into metadata and advertised over BLE. The DuckLink captures these packets, encapsulates them into LoRa payloads, and forwards them across the ClusterDuck mesh …

Designing A User-Centered Bias System To Enhance Media Literacy And Factual Accuracy, Anjali Majan

Theses and Dissertations

In an era of rapid news consumption, readers often struggle to detect bias and misinformation. This study examined whether interface design can support more critical engagement with news. We developed a progressive disclosure interface that encouraged users to reflect as they read by gradually revealing bias and factual cues. Participants were assigned to either Progressive Disclosure or Ground News. The experiment involved two phases. In the intervention phase, participants used an interface with support features. In the assessment phase, they completed tasks without the tool. We evaluated their performance using five measures: bias recognition accuracy, bias shift, factuality judgment, overlap …

Controlling Electroless Deposition On Polymer Interfaces Towards Discrete Functional Particle Synthesis, Grecia Pierina Alvarado Munoz

Graduate Theses and Dissertations

Electroless deposition is a process that facilitates the formation of metal layers on surfaces through the reduction of metal ions onto a surface in the presence of a sacrificial reducing agent. This process can be applied to synthesize conductive metal layers on insulators such as glass or polymers. The kinetics of heterogeneous deposition depend on the interfacial surface chemistry, including the presence of added catalyst materials, as well as the bulk chemical environment, such as the concentration of metal ions and sacrificial reductants. Furthermore, the homogeneous formation of metal nanoparticles may compete with the deposition reaction, adversely affecting the control …

Simulation Of Photochemical Effects On Air Quality, Grace Li

Chemical Engineering Undergraduate Honors Theses

Nitrogen dioxide (NO₂) and ozone (O₃) are both EPA criteria air pollutants in the troposphere, largely generated by combustion and therefore present in significant concentrations in urban areas. Sunlight facilitates chemical reactions between pollutants and ambient air. Aerosols modulate the amount of available energy required to drive such photochemical reactions, ultimately impacting air quality. Simulating photolysis rates with FastJX software is a resource-efficient strategy to study how these aerosols can affect air quality.

A Machine Learning Approach To Detect Pores In Laser Powder Bed Fusion Additive Manufacturing, Jose Galarza, Jose Barron Jr., Luis Jimenez, Tamer Oraby, Jianzhi Li, Farid Ahmed

Manufacturing & Industrial Engineering Faculty Publications

Real-time detection of pores in the Laser Powder Bed Fusion (LPBF) metal Additive Manufacturing (AM) process is proposed in this study and can be utilized for in-situ process monitoring and quality control. The average light emission data from the process captured by an optical tomography camera can be integrated into a defect detection module to characterize defects after the deposition of a layer. The light emission contains information on the process zone which could be extracted with the appropriate data techniques. In this paper, we proposed a machine-learning approach that utilizes the mean light intensity data from the melt-pool monitoring …

Navigating Transportation Barriers: Older Adults’ Familiarity With New Mobility Options And Perceptions Toward Autonomous Vehicles In Arkansas, Arna Nishita Nithila, Suman Kumar Mitra, Michelle Gray, Alishia Juanelle Ferguson, Jennifer D. Webb

Civil Engineering Faculty Publications and Presentations

The objective of this study is to analyze older adults’ familiarity with new transportation options (ride-hailing services, bike-share services, and shared e-scooter services) and their perception towards autonomous vehicles (fully autonomous cars), as well as how transportation barriers influence their familiarity and perceptions, in Arkansas, a predominantly rural state. Data from 775 older adults aged 60 years or older were collected between October 2021 and October 2022. To fulfill the study objective, the study used Latent Class Cluster Analysis to segment older adults into classes based on their familiarity with new transportation options and their perceptions of autonomous vehicles. The …

Growth And Characterization Of Thin Film Gase On Si(111) And Sio2/Si(001) Substrates By Molecular Beam Epitaxy, Christopher John Hocevar

Graduate Theses and Dissertations

Gallium selenide (GaSe) is a thin-film semiconducting material with promising optoelectronic properties, including a tunable bandgap, high photosensitivity, and atomic-layer scalability. These characteristics make it suitable for devices such as photodiodes, FETs, MOSFETs, Hall effect sensors, and p–n diodes. In this study, GaSe thin films were grown on SiO2 and Si(111)-7×7 substrates using molecular beam epitaxy (MBE) to compare growth behavior across different substrates. The films were characterized using Raman spectroscopy, X-ray diffraction (XRD), atomic force microscopy (AFM), photoluminescence (PL) spectroscopy, and reflection high-energy electron diffraction (RHEED). RHEED confirmed the 7×7 reconstruction of the Si(111) surface and the amorphous nature …

Design And Validation Of A High-Frequency Multi-Output Dc-Dc Converter For Radar Power Applications, Tory Sutton

Graduate Theses and Dissertations

Modern radar systems and advanced electronics demand compact, efficient, and reliable power solutions capable of delivering multiple tightly regulated voltage rails under strict size, weight, power, and reliability (SWaP-R) constraints. This thesis presents the design, implementation, and validation of a high-frequency (460 kHz – 1 MHz), multi-output DC-DC converter for a mission?critical radar platform, addressing both integration and performance requirements. The first implementation, an isolated modular converter (IMC), utilizes isolated silicon?based DC-DC modules to deliver twelve isolated voltage outputs from a single input. This approach provided robust electrical isolation, simplified system integration, and minimized design risk, making it well-suited for …

Modification Of Tini Alloy By Fast Pulse Laser Heat Treatment, Yitao Chen, Mohammad Masud Parvez, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In this study, the effects of local heat treatment with fast pulse laser on thin TiNi shape memory alloy strip materials were investigated. Various materials characterization methods including optical microscope, scanning electron microscope, atomic force microscope, X-ray diffraction, differential scanning calorimetry, and Vickers hardness were used to identify the differences of microstructure, mechanical properties, and functional properties between regions inside and outside the laser-scanned region. The tensile test was also conducted for both the non-laser-scanned specimen and the laser-scanned specimen. The area covered by laser scanning shows great differences by possessing a more homogeneous austenite phase without shear bands and …

Digital Twins, Ai, And Cybersecurity In Additive Manufacturing: A Comprehensive Review Of Current Trends And Challenges, Md Sazol Ahmmed, Laraib Khan, Muhammad Arif Mahmood, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The development of Industry 4.0 has accelerated the adoption of sophisticated technologies, including Digital Twins (DTs), Artificial Intelligence (AI), and cybersecurity, within Additive Manufacturing (AM). Enabling real-time monitoring, process optimization, predictive maintenance, and secure data management can redefine conventional manufacturing paradigms. Although their individual importance is increasing, a consistent understanding of how these technologies interact and collectively improve AM procedures is lacking. Focusing on the integration of digital twins (DTs), modular AI, and cybersecurity in AM, this review presents a comprehensive analysis of over 137 research publications from Scopus, Web of Science, Google Scholar, and ResearchGate. The publications are categorized …

Technology-Enabled Foreign Object (Fo) Prevention, Christopher Lee Colaw

Open Access Theses & Dissertations

The aviation industry incurs $14 billion per year in cost due to Foreign Object (FO) damage and the prevention and resolution techniques associated with foreign object debris. While aircraft loss, material scrap and rework contribute to that cost impact, a traditional approach to aircraft design and manufacturing which is based on human performance is also a significant driver. Failure modes and effects analysis of human based aircraft manufacturing reveals that two of the largest risks are associated with unknown potential for FO creation and the inability to recall or objectively provide evidence of FO conformity for cases of inquiry, learning, …

Elucidation Of Nano-Mechanical Property Evolution Of 3d-Printed Zirconia, Diana Hazel Leyva Marquez

Open Access Theses & Dissertations

This dissertation presents an in-depth look at the mechanical behavior, size changes, and process improvement of ceramic and polymer materials made with additive manufacturing (AM). The work consists of four separate but related studies, each tackling important challenges in fabrication, characterization, and predictive modeling. Chapter 1 examines the nano-mechanical property changes of 3D-printed zirconia made using digital light processing (DLP). By employing nanoindentation and scanning electron microscopy (SEM), the effects of print orientation and sintering on hardness, elastic modulus, and microstructure are revealed. The results indicate that 0°-oriented sintered samples have up to 140% higher hardness compared to preconditioned samples, …

Effective Transformer Networks For Undersampled Magnetic Resonance Image Reconstruction, Tahsin Rahman

Open Access Theses & Dissertations

The proliferation of data-driven tools for solving problems in every possible domain, coupled with rapid advances in computing technology, has led to an arms race of AI development and application research in industry and academia. One field of research that stands to gain immeasurably from this revolution is medical imaging. It is a critical part of modern diagnostics, and advancements in this area can directly benefit the average person by making healthcare more accessible, accurate, and affordable. Breakthroughs in mainstream image processing and computer vision have long fueled development in medical imaging, and it is now common to see cutting …

Visceral, Neural, And Immunotoxicity Of Per- And Polyfluoroalkyl Substances: A Mini Review, Pietro Martano, Samira Mahdi, Tong Zhou, Yasmin Barazandegan, Rebecca Iha, Hannah Do, Joel Burken, Paul Ki-Souk Nam, Qingbo Yang, Ruipu Mu

Chemistry Faculty Research & Creative Works

Per- and polyfluoroalkyl substances (PFASs) have gained significant attention due to their widespread distribution in the environment and potential adverse health effects. While ingestion, especially through contaminated drinking water, is considered the primary route of human exposure, recent research suggests that other pathways, such as inhalation and dermal absorption, also play a significant role. This review provides a concise overview of the toxicological impacts of both legacy and emerging PFASs, such as GenX and perfluoro butane sulfonic acid (PFBS), with a particular focus on their effects on the liver, kidneys, and immune and nervous systems, based on findings from recent …

Low Energy Ion Irradiation Effects In Electronic Devices And Materials, David C. Mccall

All Dissertations

The physics and engineering of ion-solid interactions are governed by the ion beam characteristics (flux, charge, energy) and target(s) in question. Here I present work on two projects related to the extraction of a high flux of low charge state Argon ions from a commercial plasma source and the irradiation of an engineered target, a transistor, with high charge state Argon ions.

An end-Hall ion source that produces a a high current plasma of ions and electrons in a rough vacuum environment is characterized. Using a Langmuir probe and multiple pressure measurements, the ion and electron content of the source …

Human Comfort Modeling, Measurement, And Improvement In Human–Robot Collaboration, Yuchen Yan

All Dissertations

A dissertation is proposed to explore human comfort in human-robot collaboration (HRC) through modeling, prediction, and enhancement methodologies. Human comfort is a crucial yet underexplored factor in HRC, directly influencing task efficiency, trust, and overall collaboration effectiveness. Understanding the influential factors, developing computational models, and refining methods to improve human comfort in HRC are essential steps toward advancing the field of collaborative robotics. To address these challenges, multiple studies have been conducted. A series of experimental studies were performed to investigate how robot motion-based parameters affect human comfort in HRC. These studies examined both analytical comfort modeling approaches and physiological …

Experimental Evaluation And Comparison Of Football-Related Head Impacts Among Ovine, Human, And Hybrid Iii Headforms, Madysn D. Cardinal

All Dissertations

Concussions and traumatic brain injury (TBI) remains a significant public health concern, especially in American football, where repeated head impacts pose long-term risks to athlete health. While current helmet testing standards rely heavily on the Hybrid III surrogate headform to evaluate protective performance, these surrogate models lack anatomical accuracy and exclude the presence of a brain component, limiting their ability to capture the true mechanics of concussion. To address this limitation, this research developed and validated a novel inverted impact testing method that allows the impact testing of a Hybrid III headform and a cadaveric specimen. Additionally, this fixture preserves …

Robustness Investigation, Detection, And Defense Of Deep Learning Models Against False Data Injection, Amirhossein Nazeri

All Dissertations

This dissertation addresses the critical challenge of adversarial robustness in deep learning systems, focusing on two fundamental domains: time-series prediction and object detection. As these AI systems become increasingly deployed in safety-critical applications from power grid management to autonomous vehicles their vulnerability to adversarial attacks poses significant risks to infrastructure and human safety.

The first contribution introduces a novel stealthy black-box False Data Injection (FDI) attack specifically designed for quasi-periodic time-series data. Unlike existing attacks that produce easily detectable anomalies, our method generates adversarial perturbations that preserve the underlying periodicity and statistical properties of the data, effectively bypassing traditional anomaly …

Robust Adaptive Rigid Body State And Mass Property Estimation Via Unscented Kalman Filter On Tse(3) With Process Noise Estimation, Herman Gunter

Doctoral Dissertations and Master's Theses

Mass property estimation, including mass, center of mass, and moment of inertia, is a crucial yet challenging problem in spacecraft autonomy and astrodynamics. Knowledge of mass properties of a spacecraft is essential for future astronautical missions, as changes in the mass properties of a spacecraft due to a shift in cargo distribution often require a careful and costly recalculation to ensure applied control inputs produce the desired results. As spacecraft missions grow in both duration and number, meeting the need for precise and accurate measurements becomes increasingly complex. Stochastic effects, such as angle and velocity random walks, along with persistent …

Real-Time Fiducial Marker Based Localization For Autonomous Unmanned Aerial Vehicle Navigation, Sourav Raxit

LSU New Orleans Theses and Dissertations

By harnessing fiducial markers as visual landmarks in the environment, Unmanned Aerial Vehicles (UAVs) can rapidly build precise maps and navigate spaces safely and efficiently, unlocking their potential for fluent collaboration and coexistence with humans. Existing fiducial marker methods rely on handcrafted feature extraction, which sacrifices accuracy. On the other hand, some deep learning pipelines for marker detection fail to meet real-time runtime constraints crucial for navigation applications. In this work, I propose YoloTag- a real-time fiducial marker-based localization system. YoloTag uses a lightweight YOLO v8 object detector to accurately detect fiducial markers in images while meeting the runtime constraints …

Discovery Of High-Performance Cathode Materials For Protonic Ceramic Fuel Cells, Liang Han

All Dissertations

Environmental pollution and rapid energy consumption have become common problems in global development and will continue to grow with the world population. PCFCs use proton-conducting ceramics as electrolytes, with low activation energy and high ionic conductivity at intermediate temperatures, enabling them to operate at intermediate-temperature conditions, which can effectively solve the problems of poor stability and high cost of exotic materials of traditional solid oxide fuel cells. However, as the operating temperature decreases, the electrocatalytic activity of the cathode decreases significantly, seriously affecting PCFC’s performance. Therefore, developing high-performance cathode material suitable for working under intermediate-temperature conditions has become the key …

Secure Control And Trust Evaluation Framework For Autonomous Transportation Systems, Grace Muriithi

All Dissertations

This dissertation advances the cybersecurity of hybrid tracked vehicles (HTVs) and ship power systems (SPSs) by developing innovative cyber-attack models and corresponding defence frameworks. First, we formulate stealthy false-data-injection attacks (FDIAs) on HTV energy-management systems as a partially observable Markov decision process (POMDP) solved via deep reinforcement learning. A novel sniffing-based reward function guides the attacker to covertly degrade battery capacity and energy efficiency, which we evaluate using custom stealth–impact metrics and a sliding-window anomaly detector (Isolation Forest with Dynamic Time Warping). Additionally, we model sophisticated control-layer attacks in HTVs, including reinforcement-learning-optimised replay attacks and denial-of-service (DoS) attacks targeting generator-speed …

Understanding The Elements Of Sterile Processing Workflow: Or, Sterilization And Personnel, Sayed Rezwanul Islam

All Dissertations

The Sterile Processing Department (SPD), also known as the Central Sterile Services Department (CSSD), is an essential part of hospitals and healthcare facilities and is responsible for ensuring the cleanliness, sterility, and proper functioning of medical instruments. Sterile processing departments (SPDs) are key drivers of productivity, effectiveness, safety, and infection control in hospitals. A well-designed SPD workflow can enhance patient safety, reduce operating room (OR) delays, and improve productivity. To understand the flow of sterile processing and interactions between the OR and SPD, process maps and task analyses were developed through direct observations of the basic SPD functions: decontamination, assembly, …

Advancing Lithium-Ion Batteries Through Exploration Of Novel Physico-Chemical Phenomena, Peshal Karki

All Dissertations

Lithium-ion batteries (LIBs) power a wide range of modern devices, from smartphones to electric vehicles. This dissertation integrates materials characterization and electrochemical testing to develop novel Si-based electrode materials, investigate separator effects, and improve electrochemical impedance spectroscopy (EIS) modeling. First, I synthesized Si@CC composites using bio-based carbon sources and discovered a novel in situ disorder reduction in the amorphous carbon cloud during cycling, attributed to Si volume fluctuations and mesoporous carbon structure, which enhanced capacity retention. A binder-free electrode (Si@CC@BP) using bucky paper further improved gravimetric and areal capacities while reducing weight and manufacturing complexity.

Next, I investigated how separator …