Engineering Commons^™

Dual Parameter Fss-Based Sensing For Structural Health Monitoring Applications, Swathi Muthyala Ramesh, Doyle T. Motes, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

frequency selective surfaces (FSSs) are periodic arrays of conductive elements or apertures that reflect and/or transmit incident electromagnetic energy. Their response depends on parameters, such as element shape, unit cell dimensions, dielectric properties, and the local environment, making them suitable for structural health monitoring (SHM) applications. This article presents a dual-parameter FSS-based sensor design capable of measuring small-scale uni-directional longitudinal strain (0%–0.5%) and temperature (23 ◦C–223 ◦C). The sensor integrates two-unit cells: 1) a patch-based cell on a thin substrate for strain sensing, offering enhanced strain transfer and superior sensitivity (~16–18 MHz/0.1%) and 2) a loop-based cell with a temperature-sensitive …

Analytical Model Of The Ac-Ac Dab Converter In The Egam Framework, Arnold A. Fernandes, Kartikeya Jayadurga Prasad Veeramraju, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

This paper develops an analytical model of the bidirectional AC-AC Dual Active Bridge (DAB) converter. The passive components of the AC-AC DAB are subject to grid, switching, and sideband harmonics. Thus, it is impossible to model via the conventional Generalized Average Method (GAM). It has been numerically shown that Extended GAM (EGAM) can be used to model the AC-AC DAB converter. In this paper, an analytical sixteenth order EGAM-model has been developed that considers only grid harmonics at the filter components and only sideband harmonics for the transformer leakage inductor. A closed-form expression is developed for the 2D convolution product. …

Active Microwave-Thermographic Signal Reconstruction With Adaptive Polynomial Regression, Logan M. Wilcox, Alexander Hook, Emma T. Bohannon, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Active microwave thermography (AMT) is a coupled electromagnetic (EM) and thermographic nondestructive testing and evaluation (NDT&E) technique. AMT utilizes a radiating EM source (e.g., an antenna) that induces dielectric/magnetic heating on a specimen under test (SUT). The inspection surface of the SUT is imaged with an infrared (IR) camera over the inspection time. As the thermal excitation originates from a spatially varying radiated power density, a nonuniform thermal excitation results within (or on the surface of) the SUT that is directly related to this power density. This nonuniform heating causes uncertainty in defect detection and has the potential to lead …

Anti-Jamming Attack Mixed Strategy For Formation Tracking Control Via Game-Theoretical Reinforcement Learning, Lei Xue, Bei Ma, Yongbao Wu, Jian Liu, Chaoxu Mu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Communication plays a role in multi-UAV to perform formation tracking missions. In complex environments, UAV communication is often subject to jamming attacks, affecting the formation process. Therefore, studying the formation tracking control problem in jamming attacks is of great significance. Typically, the actions of the UAV consist of two fundamental modules: mobility strategy and communication strategy. In this paper, we design an anti-jamming attack mixed strategy for formation tracking control of the multi-UAV system. In practical scenarios, multi-UAV systems not only require the accomplishment of formation maneuvers but also necessitate effective mitigation of jamming attacks caused by other UAVs. Therefore, …

Multi-Dimensional Iot-Based Energy Management Approach For Smart Homes: A Unified Model For Comfort And Energy Efficiency, Muhammad Ans, Teodoro Montanaro, Ilaria Sergi, Ahmad Alsharoa, Miriam Pezzuto, Luigi Patrono

Electrical and Computer Engineering Faculty Research & Creative Works

As smart home technologies evolve, achieving energy-efficient indoor climate management while maintaining comfort and air quality is a growing priority. This paper introduces a novel optimization framework for smart buildings that minimizes energy costs and dynamically manages indoor environmental conditions, specifically temperature, CO₂ concentration, and illuminance. Unlike conventional systems, our model incorporates dynamic constraints that respond to day-night comfort requirements and leverage real-time variations in electricity prices and environmental conditions. By optimally controlling the power levels of air conditioning, air purification, and lighting systems, the framework ensures indoor comfort while significantly reducing operational costs.A nonlinear optimization approach with dynamic …

Aperiodically Intermittent Dynamic Event-Triggered Control For Predefined-Time Synchronization Of Stochastic Complex Networks, Lei Xue, Haoyu Zhou, Yongbao Wu, Jian Liu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the problem of practical predefined-time synchronization in mean square (PTSMS) of stochastic complex networks (SCNs) is investigated through dynamic event-triggered control (E-TC). Different from the existing literature, this paper considers the dynamic E-TC in an a periodically intermittent control framework and employs the average control rate, which makes it easier to satisfy the conditions of the theorem. In comparison to existing finite-time and fixed-time synchronization, by introducing the time-varying function, it can be guaranteed that all states of SCNs achieve the practical PTSMS within a preset time without calculating the convergence time. Combined with stochastic analysis theory, …

Discrimination Of Temperature And Strain By Characterizing Two Femtosecond Laser-Written Coincident Sapphire Fiber Bragg Gratings For Harsh Environment Applications, Farhan Mumtaz, Bohong Zhang, Koustav Dey, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In this study, two co-incident sapphire fiber Bragg gratings (SFBGs) were successfully inscribed utilizing a femtosecond (fs) laser to achieve a high fringe contrast interferogram. These two SFBGs employ a unique configuration, one parallel to the center axis, called p-SFBG, and the other forming an angle from the center-axis, called a-SFBG, allowing for simultaneous strain and temperature measurements with low crosstalk. As a proof of concept, p-SFBG and a-SFBG using line-by-line method are characterized, which are shorter in length (i.e., 1.5 mm), producing reflectivity of ~3dB. This effort demonstrates the use of two coincident SFBGs forming an angle of 2.29° …

Safe Optimal Control Of Quadrotor Formations Using Multilayer Neural Networks And Continual Learning, Ehsan Soleimani, Irfan Ahmad Ganie, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article presents an integral reinforcement learning-based optimal formation tracking scheme for multiple quadrotors unmanned aerial vehicles (QUAVs) experiencing nonlinear coupled dynamics and subject to constraints. We use multilayer neural networks (MNN) within an actor-critic framework where the MNN weights are tuned using singular value decomposition (SVD) of the activation function gradient to approximate optimal control policy via backstepping. Additionally, barrier Lyapunov functions (BLF) are introduced to ensure set invariance, thereby maintaining the quadrotors within a defined safety space due to constraints. A novel weight update law for each layer is derived using the HJB approximation error and control input …

Prescribed-Time Nash Equilibrium Seeking For Pursuit-Evasion Game Under Intermittent Control With Undirected/Directed Graph, Lei Xue, Jianfeng Ye, Yongbao Wu, Jian Liu, D. C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This paper studies the prescribed-time Nash equilibrium (PTNE) seeking problem of the pursuit-evasion game (PEG) with second-order dynamics under the intermittent control (IC) strategy. To achieve Nash equilibrium (NE) in a user-defined prescribed-time, a time-varying high-gain function is incorporated into the design. The core challenge lies in applying IC to NE seeking, which complicates the convergence analysis and control design. To address this sticking point, we construct an auxiliary function and propose a Lyapunov function considering second-order dynamics to solve the PTNE seeking problem of PEG. Building upon the results for undirected graphs, we further extend our findings to directed …

Active And Reactive Power Flow Control Of The Dual Active Bridge Converter, Lauryn Morris, Thomas W. Francois, Jonathan Saelens, Oroghene Oboreh-Snapps, Arnold Fernandes, Praneeth Uddarraju, Sophia A. Strathman, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

The Dual Active Bridge (DAB) is a reliable and efficient converter capable of providing bi-directional power transfer and galvanic isolation. An ac-ac DAB can control both active and reactive power flow. The present work introduces a combined feedback/feed-forward current control system, utilizing the calculated and measured converter currents translated into the dq reference frame, to control the output power. The system was simulated in PLECS to demonstrate the control algorithm's ability to track the dq currents and provide the necessary output power.

Fast-Sparse-Spanner: A Practical Algorithm For Constructing Low-Stretch Sparse Geometric Graphs, Fnu Shariful

UNF Graduate Theses and Dissertations

When constructing geometric graphs (vertices are points and edges are line segments connecting point pairs) on pointsets, stretch-factor (worst-case detour between any point pair) is often considered a quality metric. A low stretch-factor (a quantity that is usually > 1) guarantees short paths between all vertex pairs. A geometric graph having a stretch-factor of t is known as a t-spanner. Creating low stretch-factor geometric graphs for large pointsets with a low number of edges is an open problem in computational geometry.

In this work, we have designed and engineered a new simple and practical (fast and memory-efficient) algorithm named Fast-Sparse-Spanner algorithm …

Traffic Safety In Tacoma: A Dual Study On Community Perceptions Of Vision Zero And The Application Of The Safe System Framework, Janeroza W. Matyenyi

UNF Graduate Theses and Dissertations

The city of Tacoma adopted Vision Zero in 2020 and is planning to achieve zero traffic deaths and severe injuries by 2035. As part of its outreach plan to engage the local community, the city of Tacoma’s Vision Zero team surveyed the critical issues affecting traffic safety as perceived by road users. One of the Vision Zero strategies is to implement safer speeds across streets by reducing speed limits that are too high. This study aims to analyze the factors influencing the perceptions of speeding and high-speed limits as safety concerns, analyze narratives from respondents on issues affecting traffic safety, …

Analysis Of Port Traffic Growth For Optimization Of Traffic Flow: A Microscopic Traffic Simulation Study Of Jaxport's Blount Island Marine Terminal, Amy A. Aida

UNF Graduate Theses and Dissertations

To accommodate increasing cargo volumes and remain competitive, ports worldwide are facing growing pressure to expand and modernize their facilities. However, these expansions can place additional strain on land transportation networks, leading to congestion, delays and operational inefficiencies. This study used VISSIM, a microscopic traffic simulation tool, to model and analyze the complex traffic dynamics at the Blount Island Marine Terminal in Jacksonville, Florida, which is currently undergoing expansion.

To account for future traffic conditions, time series analysis was employed to project growth in traffic demand, taking into consideration anticipated expansions in tenant yard facilities, as well as increases in …

Design, Fabrication, & Laboratory Testing Of A Strain Gage Instrumentation System For Marine Applications, Salem C. Homrighausen

UNF Graduate Theses and Dissertations

A strain gage-based instrumentation system was designed and fabricated to measure the moment present at the base of a mock, diesel-engine snorkel for a submerged vehicle designed to operate in the surf zone. Afterwards, a lab experiment was designed and executed to determine the accuracy of the instrument and a 2-dimensional, matrix-vector equation was formulated to relate pairs of voltages, Vx and Vy, to moments, Mx and My for the experiment. Three versions of this model were built. The first model was created using traditional statics equations governing strain, stress, moment, force. The second and third models were built directly …

Précis Of The Edge Of Sentience: Risk And Precaution In Humans, Other Animals, And Ai, Jonathan Birch

Animal Sentience

We often face grave practical decisions that seem to hinge on whether a system is sentient. This family of cases includes invertebrate animals, people who are unresponsive after brain injury, fetuses, neural organoids, and now AI technologies. We must decide what to do despite ongoing disagreement about the nature of sentience. In our state of uncertainty, we should pragmatically transform the question from “Is it sentient?” to “Is it a sentience candidate, an investigation priority, or neither?”. When a system is a sentience candidate, it is negligent to fail to consider precautions. We should instead evaluate precautions for their proportionality …

Understanding Fare Capping In Public Transit: Socioeconomic Predictors And Ridership Outcomes, Maige Majuto

UNF Graduate Theses and Dissertations

Fare capping is a transit policy that limits how much a rider pays within a certain period, after which all rides are free for the rest of that period. Fare capping has become a potential strategy to reverse the trend of declining transit ridership, which has been caused by factors like fare increases, service reductions, and shifts in travel behavior. While demographic and socioeconomic characteristics are known to influence ridership, their role in fare capping adoption remains underexplored. This study examines how factors like age, income, race, education, and car ownership affect fare capping adoption at the neighborhood level and …

Assessment And Optimization Of Electric Vehicles Charging Infrastructure: Addressing Accessibility Disparities In Urban And Rural Areas, Dennis B. Bwire

UNF Graduate Theses and Dissertations

The widespread adoption of electric vehicles (EVs) is essential for advancing sustainable transportation systems; however, disparities in the spatial distribution of electric vehicle charging stations (EVCS) present significant challenges for equitable access. This thesis investigates both the inequities in EVCS accessibility and offers a data driven approach for optimizing the siting of future charging infrastructure.

The first part of the study investigates the accessibility of EVCS in rural and urban areas, focusing on how socio-demographic factors influence accessibility metrics. Using geographic information systems (GIS), network analysis, and binary logistic regression, spatial data on EVCS locations and socio-demographic attributes such as …

Investigating The Roles Of Intrinsic Point Defects And Transition Metal Doping In Monolayer And Bulk Tis2, Patrick J. Keeney

UNF Graduate Theses and Dissertations

Within this thesis, the magnetic and electronic properties of various 1T-TiS₂ systems are thoroughly examined using density functional theory (DFT) and scanning tunneling microscopy (STM). Formation energies and electronic implications of intrinsic point defects in bulk TiS₂ and monolayer TiS₂ are analyzed by approximating a computational monolayer of TiS₂ as the surface layer of a bulk sample. This approximation is validated given that intralayer covalent bonding dominates interlayer van der Waals interactions. We conclude that the most energetically favorable intrinsic defects are Ti atoms settling above the outermost S plane and S vacancies. In addition, the …

Rodcast Interaction: A Novel Technique For Dense Virtual Reality Environments, Nevzat U. Demirseren

UNF Graduate Theses and Dissertations

Virtual Reality (VR) technologies continue to grow in popularity and application versatility, yet effective interaction within complex dense environments remains as a critical challenge. In particular, users with low level of VR experience often face decreased accuracy and dissatisfaction selecting occluded objects. A variety of interaction techniques to select and manipulate objects exist, but there is a research gap in understanding what kinds of techniques support users in dense environments. This study evaluates the user performance and preference in such environments. Three interaction techniques are examined in this study: Go-Go Hand, Flower Cone, and a proposed technique called RodCast Interaction. …

Frustrated Quantum Magnetism: The Interplay Of Isotropic And Anisotropic Interactions With Application To Α-Rucl3, Evan M. Wilson

UNF Graduate Theses and Dissertations

We investigate how anisotropic spin interactions, including Dzyaloshinskii–Moriya and Kitaev terms, manifest across quantum spin systems ranging from a single S = 1/2 dimer to molecular spin clusters and layered magnetic materials. Beginning with an exact analysis of the spin dimer, we demonstrate how singlet–triplet mixing induced by Dzyaloshinskii–Moriya interaction directly influences both thermodynamic observables and inelastic neutron scattering spectra. These microscopic fingerprints are then extended to trimer, tetramer, and tetrahedron geometries, where field-induced phase transitions and heat capacity anomalies reveal the interplay between isotropic Heisenberg and anisotropic Kitaev exchanges. In the frustrated zigzag honeycomb lattice, we show that a …

Solar Energy Prediction Using Advanced Hybrid Machine Learning Models, Jelawi A. Alqhtani

UNF Graduate Theses and Dissertations

Accurate short-term forecasting of solar power generation is critical for the reliable and cost-effective operation of renewable-based microgrids, where sudden weather-induced variability can compromise grid stability, battery scheduling, and energy trading decisions. Traditional physical and statistical models struggle to capture the complex non-linear relationships and localized weather effects, while individual deep learning architectures often exhibit systematic biases such as chronic under-prediction of peak generation. This thesis proposes a novel Cross-Feedback Ensemble framework that combines the complementary strengths of Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and one-dimensional Convolutional Neural Network (1D-CNN) models through an iterative cross-feedback mechanism and a …

Continuing Development Of An Unmanned Vehicle For Conducting Scientific And Engineering Operations In The Littoral Zone, Peter S. Bohn

UNF Graduate Theses and Dissertations

The beach and near shore are among the most economically and environmentally important regions on earth, yet they remain poorly understood due to the challenges of surveying the surf zone and obtaining other important data during high-energy events. Traditional methods such as wading surveys, small watercraft, and specialized vehicles like the coastal research amphibious buggy (CRAB) are limited by safety risks, high mobilization costs, and restricted operating windows. The work conducted in this effort addresses these limitations by continuing development of a remotely operated vehicle (ROV) intended to be operational in harsh surf conditions to collect high-resolution bathymetric and hydrodynamic …

Assessment Of Wave Climate Conditions At An Important Historical And Ecological Site Along The Fort George River In Northeast Florida, Ally O. Kasuwi

UNF Graduate Theses and Dissertations

This study investigated wave climate conditions at the Timucuan Preserve in northeast Florida, addressing gaps in previous shoreline erosion research that largely attributed erosion to boat wakes without detailed wave data. Field data were collected using several do-it-yourself water wave gauges. Each data collection event was for approximately one week, with an emphasis on collecting data before, during, and after periods of expected peak wave activity (i.e., holiday weekends and large-scale storms). Data were analyzed in the frequency domain to establish the likely cause of waves. Results suggested that, counterintuitively, watercraft traffic may have produced higher dominant wave periods than …

Connecting Bicyclists And Transit: A Multimodal Routing Tool With Bicycle Facilities Scoring, Raphael Y. Mrema

UNF Graduate Theses and Dissertations

This research develops a comprehensive, data-driven framework for assessing multimodal bicycle accessibility using open-source technologies and real-time routing data. Traditional active transportation studies often depend on proprietary GIS tools and static network datasets, which limit scalability, reproducibility, and integration with live mobility systems. In contrast, this study introduces a Python-based approach that leverages GeoPandas, the Google Maps Directions API, and General Transit Feed Specification (GTFS) data to dynamically evaluate infrastructure quality, operational stress, and multimodal connectivity. The framework was applied to Duval County, Florida, to examine how roadway design, facility type, and transit availability jointly influence bicycle network performance and …

Computational Pangenomics And Machine Learning For Genotype-Phenotype Analysis, Tejaswi Vemuri

UNF Graduate Theses and Dissertations

Phenotypes are the observable characteristics of an individual organism. Predicting quantitative phenotypes from genomic variation remains challenging when causal signals span both local motifs and distal regulatory contexts. Building on Frequented Regions (FRs)—subsequences conserved across genomes and extracted from a pangenome graph generated from a large collection of closely related species—we compare several modeling strategies across 35 Saccharomyces cerevisiae growth phenotypes: Random Forest (RF) on FR counts (called RFCounts), RF on FR sequences, 1D convolutional neural networks (CNN) on FR sequences, Long Short-Term Memory (LSTM) networks on FR sequences, a Genomewide Association Study (GWAS) baseline, and a sequence-based transformer model, …

Development And Validation Of Novel Force Reconstruction Algorithm For Traction Force Microscopy, Samuel E. Haarman

Dissertations, Master's Theses and Master's Reports

Traction Force Microscopy (TFM) is a powerful technique for quantifying cellular traction forces, yet its accuracy is dependent on the force reconstruction algorithm used to recover traction forces from the input substrate deformations. As such, the use cases of TFM are dependent on the types of reconstruction algorithms available. To expand the usability of TFM onto micropatterned substrates, we introduce gFEM, a novel force reconstruction method that incorporates the specific grooved topography of the user’s experimental substrate into the solution process. Unlike other traditionally used models, which assume a flat and continuous substrate, gFEM aims to improve the fidelity of …

A Hybrid Data Processing, Computational Intelligence, And Complex Systems Modeling Approach For Describing And Predicting The Bitcoin Market, Oluwadamilare Akinpelu Omole

Doctoral Dissertations

"The Bitcoin market, like traditional financial markets, is a complex system with intricate interdependencies and nonlinear interactions among various market elements. This, coupled with the inherent uncertainty and high volatility present, makes predicting Bitcoin price movements difficult. The lack of understanding of the underlying market dynamics often results in significant losses for investors and traders. Existing studies have focused on the use of predictive models, which have not sufficiently captured the complexities of the market and cannot forecast extreme market events. This research endeavors to bridge this gap by combining data processing techniques, computational intelligence, and complex systems theory to …

Nmr Relaxometry Approach For The Detection Of Asphalt Binder Performance Properties, Rebecca Herndon

Doctoral Dissertations

"Asphalt is a necessary material for transportation infrastructure. Understanding the material properties of asphalt binders is critical for improving infrastructure and enhancing the lifetime of pavements. While the physical properties of asphalt binders are well-defined by standard procedures and parameters, the chemical environment lacks definition. Physical parameters like viscosity and stiffness are traditionally used to differentiate asphalt binders, describe aging, and indicate the impact of additives. However, these tests have limited insight into the material's chemical environment. Therefore, a nondestructive analytical technique, nuclear magnetic resonance (NMR) relaxometry, was employed to investigate the chemical environment of asphalt binders. Although NMR relaxometry …

Advancing Refuge Alternatives In Mine Emergencies Using Advanced Numerical Simulation, Kutay Emre Karadeniz

Doctoral Dissertations

"Incidents and emergencies within underground coal mines can result in severe injuries or even loss of life, particularly due to the hazardous nature of mine explosions. One of the options for the miners to protect themselves from these hazards is to be sheltered in a refuge alternative (RA). However, the literature lacks an analysis of survivability constraints and the structural integrity of RAs when exposed to geomechanical changes and the ability to withstand the impact of coal mine explosions. In this study, based on the utilization and survivability constraints, basic human requirements and the required physical specifications of RAs during …

Nano-Micro Engineering For Advanced Energy Devices, Tazdik Patwary Plateau

Doctoral Dissertations

The development of advanced materials and manufacturing techniques for energy storage devices is continuously growing. The research emphasizes micro-engineering, nano-engineering, and advanced materials science, with the goal of enhancing the performance and scalability of manufacturing methods of different materials processing with a view of achieving sustainability. In the micro-engineering domain, novel methods for fabricating thick electrodes with short diffusion paths are introduced, enabling higher mass loading and improved battery performance. Additionally, innovative strategies for optimizing the performance of carbon nanofibers (CNFs) as anode materials in LIBs are explored in the nano-engineering domain. These studies address key challenges such as inter-bonding …