Digital Commons Network^™

Temperature Compensation In Loop And Patch Fss Strain Sensors: Analysis And Experimental Validation, Swathi Muthyala Ramesh, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Frequency selective surfaces (FSSs) are arrays of conductive elements or apertures that exhibit frequency-dependent reflection and transmission properties. Their electromagnetic response is influenced by geometry and environmental conditions, making them attractive for wireless strain-sensing applications. However, temperature variations can produce frequency shifts similar to those caused by strain, reducing measurement accuracy. This work investigates the effects of intrinsic temperature compensation on two common FSS unit cell geometries—loop and patch—through comprehensive simulation analysis. The results show that loop-based cells offer superior thermal stability, while patch-based cells provide greater strain sensitivity, illustrating the trade-off between thermal robustness and mechanical responsiveness. A patch-type …

Safety Aware Continual Reinforcement Learning-Based Output Tracking Control Of Nonlinear Continuous-Time Systems, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

An output feedback (OF)-based control scheme utilizing both a scalable multilayer neural network (MNN) observer and actor–critic MNN via integral reinforcement learning (IRL)/adaptive dynamics programming (ADP) approach for a class of nonlinear systems with output constraints is introduced. The proposed observer, critic, and actor MNN weight updates are derived using a singular value decomposition (SVD) of MNN activation function gradient along with output error, Bellman and control input errors, respectively. Next, the approach incorporates continual learning (CL), utilizing a penalty function in the weight update laws for both actor–critic MNNs to consolidate knowledge from previous tasks and enhance learning in …

Corrections To: Enhancing Measurement Accuracy: The Impact Of Missing Data On Parameter Estimation In Mass-Spring-Damper Systems (Ieee Transactions On Instrumentation And Measurement (2026) 75 (1–12) Doi: 10.1109/Tim.2026.3676091), Michkath Omanda Bouraima, Steven Thompson, Maciej J. Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

In the above article [1], a wording ambiguity appears in Proposition 4 regarding the description of the missing at random (MAR) mechanism. The published sentence states that the probability of observing the kth sample depends on the realized measurement value. This wording may be interpreted as dependence on the current unobserved value y[tk], which could suggest a missing not at random (MNAR) mechanism. The intended MAR mechanism is that the observation probability for the kth sample depends only on previously observed measurement information, such as y[tk-1], and not on the current unobserved value y[tk]. Therefore, the corrected wording clarifies that …

Increasing Actuation Authority And Bandwidth For Aeromechanics Testing: A Piezoelectric-Based Approach, Sydney A. Giannuzzi

Graduate Studies Theses and Dissertations 2026

Flutter in turbomachinery poses significant risks to aerospace systems, requiring accurate identification of flutter boundaries to ensure operational safety. Traditional binary “flutter / no flutter” testing methods provide limited data without error margins. Aeromechanical Identification Methodology (AIM) offers a safer alternative by mapping aeromechanical damping across operational conditions using non-contact excitation. However, current AIM actuators are constrained to excitation frequencies below 500 Hz, limiting their effectiveness and applicability. To bridge this gap, this research analyzed and validated performance of a novel piezoelectric-based oscillatory flow injection valve (NOVA) designed to deliver high-bandwidth, high-authority actuation for expanded flutter boundary mapping.

NOVA was …

Experimental Validation Of Optical Wireless Communication And Power Transfer For Uav Applications, Fnu Dhruv

UNF Graduate Theses and Dissertations

Unmanned Aerial Vehicles (UAVs) have revolutionized emergency response, disaster assessment, and search-and-rescue operations. However, their operational efficacy is fundamentally constrained by limited battery endurance and the susceptibility of traditional radio-frequency communication to disruption in adverse weather. To address these limitations, this thesis proposes and experimentally validates a novel architecture integrating Free-Space Optical (FSO) communication with Simultaneous Lightweight Information and Power Transfer (SLIPT). This system utilizes a split-beam configuration to concurrently enable high-bandwidth data transmission and optical energy harvesting to replenish the UAV's battery pack. The research was conducted in three progressive phases. Initially, system feasibility was established through rigorous optical …

Thermomechanical Modeling Of Transpiration Surfaces For Hypersonic Propulsion, Spencer D. Smith

Graduate Studies Theses and Dissertations 2026

Hypersonic flight vehicles are a promising form of high speed passenger transport and efficient space access architectures. However, they are fundamentally a thermally limited technology. High heat fluxes exceeding 10 MW/m2 and gas temperatures between 3000-4000K can be found both within the engine, and on the outer surface. Current conventional engineering materials are non-viable at these conditions. In order to make these materials viable, active cooling strategies could be utilized. One particularly promising type is transpiration cooling, where a coolant is diffused through a porous surface. Although researched heavily in the 1960s, adoption is still minimal. Part of the reason …

Experimental Characterization Of Obstacle-Driven Ddt And The Performance Of Relief Dump Tanks In Detonation Systems, Bryan Suarez

Graduate Studies Theses and Dissertations 2026

This study investigates the lifecycle of a detonation event in a modular detonation
tube facility. It focuses on the mechanisms of deflagration-to-detonation transition
(DDT) and the effectiveness of a pressure relief system. With a stoichiometric
hydrogen-oxygen mixture, the research aims to characterize the effect of
interchangeable turbulator obstacles on the DDT process. By varying blockage
ratios and obstacle geometries in the pre-detonation section. This study identifies
how physical characteristics influence transition efficiency. The experimental data
collected includes pressure spikes and wave speed which were then used to
validate against the Chapman-Jouguet (CJ) theory at initial pressures of 350 Torr
and …

Watch Your Step, Mind The Crowd: Socially Compliant Navigation In Unstructured Environments, Jack Vice

Graduate Studies Theses and Dissertations 2026

Autonomous mobile robots increasingly operate in complex real-world environments characterized by uneven terrain, dynamic obstacles, and human presence. This dissertation addresses the fundamental challenge of developing adaptive navigation strategies that enable robots to safely and effectively traverse unstructured outdoor environments including construction sites, agricultural fields, and disaster areas while maintaining social compliance around people. We advance this capability through five complementary contributions that collectively target dynamic, unstructured, human-occupied environments. First, we demonstrate evolutionary optimization of legged mobility for uneven terrain. Second, we propose using a spatiotemporal autoencoder to learn the temporal dynamics of moving people and objects. Third, we introduce …

Pseudo-Boiling Of Supercritical Co2 In A Parallel-Flow Microchannel And A Micro-Jets Impingement Device And Single-Phase And Two-Phase Heat Transfer Of Subcritical Co2 Jets, Pranzal Ahmed

Graduate Studies Theses and Dissertations 2026

Carbon dioxide (CO2) is gaining attention as a low-toxicity, zero-ozone-depletion refrigerant with a global warming potential of 1, making it an attractive alternative to synthetic HFCs/HFOs. Near its critical point, CO2's thermophysical properties change sharply with small shifts in temperature and pressure — a behavior that can be exploited to enhance heat transfer in trans-critical power cycles and electronics cooling. This dissertation experimentally investigates heat transfer during the pseudo-boiling of supercritical CO2 in a parallel-flow microchannel and a micro-jet impingement device, alongside CO2 flow boiling and single-phase water heat transfer in micro-jet impingement. Using microfluidic devices instrumented with embedded resistance …

Design, Fabrication Modeling, And Optical Metrology Of Mwir Silicon Metalenses, Weiyu Chen

Graduate Studies Theses and Dissertations 2026

Mid-wave infrared (MWIR) optical systems require compact, broadband, manufacturable components whose performance can be predicted and measured reliably. Silicon metalenses are attractive because silicon combines high refractive index, MWIR transparency, and semiconductor-compatible fabrication. This dissertation develops a scale-bridging design–fabrication-modeling–metrology framework for MWIR silicon metalenses.

A shared full-aperture framework connects meta-atom libraries, physical layout generation, angular-spectrum propagation, point-spread-function calculation, and focal-plane energy metrics. Building on this foundation, the Dispersive Sweatt Model (DSM) incorporates meta-atom dispersion into conventional ray-tracing software, enabling broadband co-optimization of metasurfaces and refractive elements. A process-aware design framework then incorporates scanning electron microscopy (SEM)-measured height–radius relationships produced by …

Integrated Optical Probes For Confocal Scanning Imaging And Adjustable Coherent-Gated Dynamic Sensing, Yonglin Huang

Graduate Studies Theses and Dissertations 2026

Optics and photonics have been one of the most important sciences and technologies that impact modern human life in a big way. For example, fiber-optics for communications and artificial intelligence. Optical probes are critical components for optical imaging and optical sensing technologies that have been actively researched and developed in the past decades. Advanced fiber-optic sensor probes with smaller size, better performance, lower noise, higher photon efficiency, rapid sensing time, and lower cost are needed in many applications, such as nanoscale material science, chemistry, and biomedical fields, etc.  In this project, new fiber-optic sensor probe technologies and integrated micro-optic devices …

Integrated Corridor Management Framework For Severe Freeway Incidents, Sanjida Afroz Iqra

Graduate Studies Theses and Dissertations 2026

Traffic incidents are a major source of non-recurrent congestion on urban freeways, generating substantial mobility, safety, and economic impacts. Severe incidents that block multiple or all travel lanes are particularly disruptive because they degrade freeway operations and propagate congestion onto surrounding arterials. Effective Integrated Corridor Management (ICM) requires the ability to identify severe incidents, estimate their network-wide impacts, and anticipate the traffic conditions and driver behaviors that contribute to instability. This dissertation develops a data-driven ICM framework to address these challenges using real-world incident, crash, detector, and connected vehicle data from major Central Florida corridors, including I-4 and SR-417. The …

Securing The Energy Transition: Cyber-Physical Security And Resilience In Next-Generation Power Systems, Airin Rahman

Graduate Studies Theses and Dissertations 2026

Modern power systems are rapidly evolving into renewable-dominated and digitally interconnected cyber-physical infrastructures due to the increasing deployment of distributed energy resources (DERs), inverter-based technologies, and advanced control platforms. Maintaining reliability under high renewable penetration requires flexible resources capable of shifting energy across extended time horizons. Long-duration energy storage (LDES), particularly hydrogen-based energy systems, has therefore emerged as an important enabler of renewable integration, grid flexibility, and resilience. However, the growing dependence on communication, sensing, and distributed control also expands the cyber-physical attack surface of modern power systems, creating security and resilience challenges that conventional operational paradigms were not designed …

Advancing Cyber-Physical Security And Resilience Of Modern Power Systems: Intelligent Monitoring, Secure Operation, And Resilient Recovery, Md Moshiur Rahman

Graduate Studies Theses and Dissertations 2026

Modern power distribution systems are rapidly evolving into cyber-physical, DER-rich, and data-driven networks that rely on extensive sensing, communication, automation, grid-edge intelligence, and operator decision support. While this transformation improves flexibility, observability and controllability, it also expands the cyber-attack surface and increases the risk that cyber intrusions can propagate into physical disturbances, compromised DER operation, degraded situational awareness, and interrupted service continuity. This dissertation advances the cyber-physical security and resilience of modern distribution systems by developing a high-fidelity real-time cyber-physical hardware-in-the-loop testbed using OPAL-RT, EXata CPS, industrial relays, SCADA/RTAC, HMI, and grid-edge devices to emulate realistic DER-integrated distribution grid operation. …

Evaluating The Brain-Muscle Connectivity Of Cyclic Ankle Pedaling Movement In A Clinical Setting, Matthew K. Shanosky

Graduate Studies Theses and Dissertations 2026

Clinical neurorehabilitation requires objective biomarkers to accurately detect and monitor neuromotor impairments. While traditional metrics are favored for their efficiency and minimal equipment demands, they typically rely on subjective observation and lack physiological resolution. High-resolution electrophysiological technologies, such as electroencephalography (EEG) and electromyography (EMG), offer objective insights into nervous system dynamics; however, prolonged data acquisition times have hindered their translation into frontline clinics. To bridge this translational gap, this study developed a time-efficient experimental paradigm designed for rapid clinical deployment. Healthy participants completed two initial resting baseline trials before performing an externally paced, dynamic, cyclic ankle movement task utilizing simulation …

Integrated Design And Trade Study Of A Sub-Ambient Ammonia Fuel Storage And Delivery System For Narrow-Body Commercial Aircraft, Ethan Taylor

Graduate Studies Theses and Dissertations 2026

This study develops an integrated design framework for a sub-ambient anhydrous-ammonia fuel storage and delivery system for narrow-body commercial aircraft, using the Boeing 737 MAX 8 as the baseline platform. Ammonia was selected because it contains no carbon in its molecular structure, benefits from an established global production and distribution infrastructure, and offers more practical storage conditions than several alternative carbon-free energy carriers. However, its relatively low energy density, toxicity, material-compatibility requirements, and combustion hazards require substantial modifications to power conventional commercial aircraft fuel storage and delivery systems.

The study proposes an integrated design and initial analysis of a sub-ambient …

Investigation On Selective Catalytic Reduction For Retrofit Of Commercial Aviation Aircraft Engines, Connor M. Wall

Graduate Studies Theses and Dissertations 2026

As the aviation industry continues to grow, the ever-increase of emissions from the sector becomes a growing concern. While the International Civil Aviation Organization (ICAO) set a goal of net-zero carbon emissions by 2050, there are other emissions like contrails and NOx that must still be addressed. Selective Catalytic Reduction (SCR) has been used in the transportation and power generation industry for over two decades and has been an effective solution for NOx reduction. Even with the success SCR has had in other industries, its capabilities in the aviation industry have been trivially investigated. Aircraft engines pose an unique challenge …

A Framework For Optimizing Creep Model Parameters From Conventional And Accelerated Creep Tests, William D. Day

Graduate Studies Theses and Dissertations 2026

The demand for efficiency in power generation and propulsion requires higher firing temperatures and reduced cooling air consumption which raises metal temperatures. This makes simplistic creep evaluations, such as Larson-Miller and Orr-Sherby-Dorn parameters, inadequate. Finite element analysis (FEA) must simulate primary and secondary creep, predict failure, and provide design guidance. Gas turbine components, expected to last over 100,000 hours, often require extrapolation of limited test data for new materials. It is essential that robust creep simulations be developed efficiently, accurately, and effectively use limited test data.

This dissertation describes an optimized framework for efficient creep testing and rapid construction of …

A Reconstruction Method For The Anisotropic Electrical Conductivity In A Hybrid Planar Inverse Problem, Athanasios Dimitriadis

Graduate Studies Theses and Dissertations 2026

Some single-physics medical imaging methods fail to reliably discriminate benign from malignant biological tissue. In partial response, a new class of inverse problems employ multi-physics phenomena, coupling methods of high resolution with methods of high contrast. In this thesis we are concerned with one such problem in which an anisotropic electrical conductivity is to be recovered from some internal knowledge of the current density field generated by maintaining a fixed boundary voltage. This internal data is obtained by the method of Current Density Impedance Imaging (CDII), which combines Maxwell's equations with Magnetic Resonance Imaging (MRI) measurements. The anisotropy class is …

Computational Regolith Mechanics And Instrumentation Development For Lunar Exploration And Resource Utilization, Jared M. Long-Fox

Graduate Studies Theses and Dissertations 2026

Sustained exploration of the Moon requires quantitative understanding of lunar regolith properties to support scientific investigation, in situ resource utilization, excavation, and infrastructure development. This dissertation examines the mechanical interaction between robotic excavation systems and lunar regolith, emphasizing how regolith behavior both enables and constrains exploration-focused and exploration-enabled science. Computational excavation models were compared to laboratory data to evaluate prediction of excavation forces and to develop metrics of excavation efficiency. Laboratory experiments using high-fidelity lunar regolith simulants were conducted to characterize pressure-sinkage behavior, shear strength, and angle of repose across a range of material states. Common analytical excavation and terramechanics …

Deceptive Design And Disability: How Dark Patterns Affect Users With Visual Impairments, Konstantin Metz

Graduate Studies Theses and Dissertations 2026

Dark patterns are deceptive interface designs that steer users toward unintended actions, often at financial or privacy cost. This thesis examines how those that are vision impaired are at greater risk of these dark patterns given their visual acuity deficit. We conducted semi structured interviews with nine participants across common contexts including e-commerce checkout, subscription and cancellation flows, software download pages, and mobile permission prompts. The data show recurring exposure to dark patterns such as hidden or de-emphasized fees, pre-selected add-ons, deceptive advertising and fake download buttons along with unequal consent paths, repeated permission nagging, and cancellation friction. Participants reported …

Revolution In The Age Of Social Media: A Mathematical Model For Information, Dissent, And Stability, Killian Muollo

Graduate Studies Theses and Dissertations 2026

Revolutions, defined by Skocpol as rapid transformations in class, state, and/or social structures, are important world events that can cause civil wars, spark international trends, and result in transitions toward democratic and autocratic regimes alike. They are characterized largely by the mechanism of mass mobilization, which is increasingly facilitated by online networks and digital communication. In this dissertation, we investigate such means and outcomes of revolutions as dynamical systems. We construct three models describing separate but complementary aspects of revolution, beginning at the smallest unit of analysis and then moving outward in scope. First, we construct a graph-based model to …

Shm For Incipient Buckling Detection In Overloaded Structures Using Nonlinear System Identification Algorithms On Redundant Data Sets, Padmanabh Shridhar Desai

Dissertations, Master's Theses and Master's Reports

Structural health monitoring (SHM) detects and characterizes damage to predict failure, but failures such as buckling, which are not predicated on traditional damage modalities, are harder to detect. Direct load measurements are costly and difficult to implement (especially for dead loads) as they require copious numbers of sensors, which must be installed before loading is present. Vibration-based detection is a good alternative because it can infer global structural characteristics with relatively few sensors. This dissertation presents an SHM approach for detecting incipient buckling in structures under excessive loads based on non-linear models fit from measurements of small lateral vibrations due …

Development And Calibration Of A 2-D Diesel Oxidation Catalyst Filter (Docf) Model With Spatially Varying Washcoats Using Spacims And Engine Loading Data, Thomas K. Price

Dissertations, Master's Theses and Master's Reports

Diesel engine exhaust contains regulated species, including carbon monoxide, hydrocarbons, nitrogen oxides, and particulate matter (PM). Meeting increasingly stringent emission standards typically requires multiple aftertreatment components, motivating the development of multifunctional devices that reduce system size, cost, and catalyst usage. Computational models are essential for guiding this design process; however, existing models primarily focus on single-function devices and rarely capture the behavior of multifunctional systems with multiple catalyst washcoats. This work presents a physics-based model of a wall-flow diesel oxidation catalyst filter (DOCF), a multifunctional device that integrates the roles of a diesel oxidation catalyst and a diesel particulate filter …

On The Vibrational Dynamics Of Wind Turbine Blades: The Oscillatory Response To Gust Pulses, And The Physical Mechanisms Behind Them, North A. Yates

Dissertations, Master's Theses and Master's Reports

An easily noticed trend in the utility-scale wind turbine industry is that the size of the machines has continued to increase over time. While this may have benefits in terms of increasing the power generation for a single turbine, a major drawback is the rate with which the weight of the turbine blades grow. To ensure these larger machines can be utilized, efforts are being put forth to create lighter blades. This may fix the weight issue, but brings on a new one; these lighter blades can also be more flexible than previously studied ones. It is, therefore, vitally important …

Computational And Ai Frameworks For Identifying Key Regulatory Genes And Their Target Genes In Plants And Humans, Md Khairul Islam

Dissertations, Master's Theses and Master's Reports

This dissertation presents computational and AI-driven frameworks for identifying key regulatory genes and their downstream targets across plant and human biological systems. Three studies address distinct challenges in genomic regulation using advanced machine learning and bioinformatics approaches.

The first study introduces DyGAF (Dynamic Gene Attention Focus), a dual-attention transformer framework that identifies and ranks disease-relevant biomarker genes by simultaneously modeling independent molecular responses and interdependent regulatory network behavior. Two attention models provide complementary perspectives on gene importance and are fused through a novel combination metric. Applied to COVID-19 nasopharyngeal swab profiles, the attention-weighted representations achieved 94.23% classification accuracy, high sensitivity, …

Machine Learning And Multi-Scale Optimization For Control And Energy Management In Connected And Automated Vehicle Propulsion Systems, Joshua D. Orlando

Dissertations, Master's Theses and Master's Reports

This dissertation presents a multi-scale optimization framework leveraging machine learning (ML) to enhance energy efficiency in connected and automated vehicle (CAV) propulsion systems. As transportation transitions toward hybridization and automation, the integration of vehicle-to-everything (V2X) connectivity and advanced control algorithms offers unprecedented opportunities for energy reduction. This research addresses three critical scales of vehicle energy management: multiple vehicle-level coordination, component-level powertrain dynamics, and real-time vehicle parameter estimation.

First, the research investigates the energy consumption characteristics of heterogeneous propulsion systems—ranging from internal combustion engines to battery electric vehicles across light- and heavy-duty sectors—on arterial roadways. Utilizing Particle Swarm Optimization (PSO) and …

Robust State Estimation And Scene Understanding For Autonomous Ground Vehicles In Challenging Environments, Nader J. Abu-Alrub

Dissertations, Master's Theses and Master's Reports

Autonomous ground vehicles require reliable state estimation and scene understanding to operate safely in challenging environments. Poor illumination, adverse weather, degraded visibility, snow-covered roads, and sensor noise can reduce the reliability of conventional localization and perception pipelines. Addressing these challenges requires sensing and algorithmic strategies that exploit the complementary strengths of different modalities. Radar is particularly attractive because of its resilience to lighting and weather variations, while inertial, camera, and lidar measurements provide additional motion, appearance, and geometric information. This dissertation investigates compact radar-based and sensor-fusion approaches for improving autonomous ground-vehicle state estimation and scene understanding under degraded sensing conditions. …

Antenna-Based Sensors For Dielectric Characterization Of Materials, Hilary Scott Nkimbeng Cho

Dissertations, Master's Theses and Master's Reports

This research introduces antenna-based sensors for dielectric characterization aimed at overcoming the limitations of conventional microwave sensors. Although traditional microwave sensors are widely used for their noncontact operation, high sensitivity, and ability to penetrate various materials, they often face challenges such as large size and high-power consumption. To address these issues, antenna-based sensors are explored for their compactness, ease of fabrication, and flexible design adaptability across diverse sensing applications. An in-depth analysis of multiple antenna sensor configurations is conducted, followed by the design and development of high-performance sensing structures. A saw-tooth slot antenna sensor is developed for highly sensitive liquid …

Using Automotive Lidar To Reduce The Energy Consumption Of An Ego Autonomous Vehicle, Logan P. Schexnaydre

Dissertations, Master's Theses and Master's Reports

There is significant potential to reduce the energy consumption of the transportation sector through autonomous vehicles. Prior work on autonomous vehicle energy efficiency focuses on the whole system or the control subsystem. Yet, the sensing and processing components, which have direct and indirect effects on net energy use, are less explored. This dissertation fills this gap by modeling and evaluating these effects for lidar sensors, which provide high-resolution spatial data at the cost of high power and processing demands. I apply lidar to the energy-saving tasks of automated vehicle following and road surface profiling. For automated vehicle following, I model …