Digital Commons Network^™

Porous Triboelectric Nanogenerator For Load Sensing Of Total Knee Replacement, Elham Mahmoudi, Adam Garry Redgrift, Emre Salman, Milutin Stanacevic, Ryan Willing, Shahrzad Towfighian

Mechanical Engineering Faculty Scholarship

This study addresses the critical need for self-powered, durable pressure sensors in Total Knee Replacement (TKR) implants to enable the collection of post-operative information. The scope of this research encompasses the design, development, and testing of a triboelectric nanogenerator (TENG) integrated into an instrumented knee implant for energy harvesting and pressure sensing. The authors’ unique approach involves utilizing a porous silicone rubber as a dielectric material. This allows the TENG to withstand forces up to 2000 N and generate a maximum power output of 18 μW. Theoretical modeling combined with experimental validation provides deeper insight into the fundamental operating principles. …

Bridging Cybersecurity Practice And Law: A Hands-On, Scenario-Based Curriculum Using The Nice Framework To Foster Skill Development, Colman Mcguan, Aadithyan Vijaya Raghavan, Komala M. Mandapati, Chansu Yu, Brian Ray, Debbie Jackson, Sathish Kumar

Electrical and Computer Engineering Faculty Publications

In an increasingly interconnected world, cybersecurity professionals play a pivotal role in safeguarding organizations from cyber threats. To secure their cyberspace, organizations are forced to adopt a cybersecurity framework such as the NIST National Initiative for Cybersecurity Education Workforce Framework for Cybersecurity (NICE Framework). Although these frameworks are a good starting point for businesses and offer critical information to identify, prevent, and respond to cyber incidents, they can be difficult to navigate and implement, particularly for small-medium businesses (SMBs). To help overcome this issue, this paper identifies the most frequent attack vectors to SMBs (Objective 1) and proposes a practical …

Multi-Modal Data-Efficient Learning For 3d Machine Vision, Zhimin Chen

All Dissertations

The rapid progress of 3D computer vision has enabled a wide range of applications in autonomous driving, robotics, and augmented reality. Despite this growth, training robust 3D perception models remains challenging due to limited labeled data, the complexity of integrating multiple modalities, and the inherently imbalanced and long-tailed nature of 3D datasets. This dissertation addresses these challenges by proposing data-efficient, multi-modal learning frameworks that improve the accuracy, generalization, and scalability of 3D scene understanding.

In the semi-supervised setting, this work presents novel approaches that combine limited annotations with large amounts of unlabeled data to enhance 3D object classification and retrieval. …

Synthesis And Characterization Of Chemically Recyclable Polypropylene-Based Covalent Adaptable Networks, Andrii Tiiara

All Dissertations

Polyolefins (POs) are inexpensive engineering materials with excellent physical and mechanical properties, accounting for nearly 60% of all thermoplastics. However, large-scale recycling remains limited, with only ~15% undergoing mechanical recovery. This dissertation addresses this challenge by fragmenting and functionalizing polypropylene (PP) chains to generate macromonomers and employing them, along with industrial reactive PP macromonomers, to synthesize, depolymerize, and repolymerize chemically recyclable polypropylene-based polyolefins (CR-POs). These CR-POs incorporate ester linkages that form covalent adaptable networks (CANs), maintaining a gel fraction of ~70% while remaining melt-reprocessable via extrusion and compression molding.

First, the fragmentation of PP is investigated by microwave irradiation. Microwave …

Robust Data-Driven Predictive Control Of Nonlinear Systems Under Modeling Uncertainty, Pegah Ghafghanbari

All Dissertations

Data-driven predictive control enables designing controllers directly from data, making it attractive for complex systems with hard-to-model dynamics. However, practical deployment is challenged by modeling inaccuracies and changing operating conditions. This dissertation develops predictive control frameworks that incorporate robustness and adaptability to address these issues in uncertain nonlinear systems.

The first part employs the Linear Parameter-Varying (LPV) framework, which represents nonlinear dynamics through simple linear form representation. To characterize the plant-model-mismatch often caused by limited data and numerical calculations, Bayesian Neural Networks (BNNs) are used, and their uncertainty estimates are integrated into two robust control approaches. The first is a …

Surface Reaction And Transportation Of Radium-226 In Marine Systems, Jiusi Wang

All Dissertations

Historical uses of radium (Ra)-containing self-luminous paint, such as on gauges and dials in naval ships, have led to the potential for such paint, and thus Ra, to be released into the marine environment. Radium-226 (²²⁶Ra) behavior in marine systems is not fully described in the literature, presenting a knowledge gap in the process of evaluating potential ecological impact of Ra in marine systems. This study explores various mechanisms contributing to Ra environmental transport in marine systems on a laboratory scale, including leaching, sorption, and diffusion. ²²⁶Ra leaching from watch hand dials containing radioactive luminous paint is …

Advancing Life Cycle Assessment Of Mass Timber: Environmental Performance, Circular Design And End-Of-Life Strategies, Muzan Williams Ijeoma

All Dissertations

Mass timber has emerged as a leading candidate for low-carbon construction, offering the dual benefits of reduced embodied emissions and biogenic carbon storage. Yet, fully realizing its sustainability potential requires a comprehensive and context-specific understanding of its environmental performance across the entire life cycle, from raw material production to building operation and beyond end-of-life (EoL). This dissertation advances life cycle assessment (LCA) practices for mass timber by addressing critical challenges across multiple phases of its life cycle. This dissertation is comprised of three published papers, and two submitted manuscripts. First, I conducted a critical review and meta-analysis of mass …

Hydrodynamics Of Perforated Heave Plates, Muhammad Usman

All Dissertations

Ocean waves are a clean and renewable energy source that can help reduce dependence on fossil fuels and combat climate change. To capture this energy, researchers have developed devices known as wave energy converters (WECs). One common type, called a two-body point absorber WEC, uses a buoy floating on the ocean surface connected to a submerged reaction plate, known as the heave plate, which lies underwater. The relative up-and-down motion between the buoy and the heave plate, driven by ocean waves, generates usable power via a power take-off (PTO) system. Traditionally, these submerged heave plates are solid structures. However, this …

Opposed-Piston Two Stroke Engine As A High Power Density Solution In Heavy Duty Applications: An Experimental Evaluation With Diesel And Ethanol, Ankur Bhatt

All Dissertations

With an increasing demand to reduce greenhouse gas (GHG) emissions, the conventional powertrain technology is at a saturation point. There is reinvigorated research interest in alternative powertrain designs that offer potentially higher efficiencies and lower engine-out emissions compared to conventional powertrains. The opposed piston two-stroke (OP2S) engine is one such alternative engine architecture that has demonstrated a reduction in engine-out emissions and increased efficiency compared to conventional four-stroke diesel engines. Like any two-stroke engine, the scavenging process and the composition of the internal residuals are predominantly governed by the pressure differential between the intake and the exhaust ports. Without dedicated …

Strategic Enhancement Of Biofuel Production Using Bacillus Subtilis As A Model Organism: A Dual Approach Of Gene Essentiality Mapping And Optimization, Angela A. Zebede

Electronic Theses and Dissertations

With rising global demand for renewable energy, enhancing microbial platforms for biofuel production is vital. This study engineered Bacillus subtilis to improve resilience to solvent stress by targeting membrane lipid biosynthesis pathways essential for integrity. Growth curve analysis (OD₆₀₀) showed that phosphatidylserine (PS) and phosphatidylethanolamine (PE) knockout strains grew significantly slower than wild type (168), indicating the importance of these lipids under stress. Laurdan fluorescence spectroscopy was used to assess membrane properties. Generalized polarization (GP) analysis revealed a concentration-dependent reduction in membrane order upon 1%–2% 1-butanol exposure. GP values declined progressively from control to 2% treatment, reflecting increased membrane fluidity …

Towards Trustworthy Federated Learning, Alina Basharat

Theses and Dissertations

Federated learning is a collaborative training model in which multiple clients optimize aglobal model by transmitting updates to a coordinating server while keeping raw data on-device, thereby reducing direct data exposure and enabling iterative global improvement. However, the iterative communication process is vulnerable to malicious attackers that either deliberately destroy the model or curious to infer raw data. Moreover, learning from multiple agents may result in unfair results. To enhance trustworthiness within this setting, we employ two-sided norm-based screening (TNBS) that removes both abnormally large and abnormally small updates, pair it with a q-fair objective to emphasize high-loss (disadvantaged) clients, …

When Textures Trim Drag: Micro-Structures For Adaptive Drag Reduction And Flow Authority, Miguel Angel Olvera

Theses and Dissertations

Turbulent boundary layers are a major source of drag and performance loss. This thesis investigates Triangular Porous Texturing (TPT), apex-forward microstructures with optional bleed channels, as a passive concept for simultaneously reducing skin friction and strengthening boundary layer momentum near separation. Low-speed wind tunnel tests are conducted over tripped turbulent boundary layers on flat plates with three surfaces: a smooth baseline, a solid-crest TPT array isolating the knife-edge “slip-cut” effect, and a porous-bleed TPT array whose paired micro-channels vent a small fraction of the free stream. Time-resolved PIV provides wall-normal velocity fields; skin friction is inferred from near-wall shear, and …

Modeling Flood Risks For Small-Scale Coastal Watershed Across Shared Socioeconomic Pathway Scenarios, Sebastian Loschner

Graduate Theses and Dissertations (2019 - present)

Coastal flooding, driven by the mixture of natural processes and human activities such as precipitation, waves, sea level rise, and urbanization, remains a growing concern. While recent flood-risk studies use IPCC's Shared Socioeconomic Pathways with climate projections to assess future flood exposure, smaller coastal watersheds, < 120,000 acres, remain insufficiently studied. Projected sea level rise is expected to intensify these impacts in smaller systems, potentially causing more severe flooding than reported for larger watersheds. To address this gap, this study used the SRH-2D model integrated with Aquaveo's Surface-water Modeling System to simulate flooding in the lower Fish River basin, Alabama. A coastal watershed sensitive to both riverine and tidal influences. Simulations tested different sea levels based on SSP scenarios corresponding to low, moderate, and high emissions for the years 2050 and 2100. Results indicate that the midcentury scenarios remained even in inundation extent and volume, between 9.9-10.4% compared to the 2020 baseline, the latter scenarios had a wider range in results of between 25.9-50.3% compared to the same baseline. Across scenarios, the most vulnerable and inundated areas of the smaller coastal watershed were the narrow points where upstream flow convene with downstream backwater. These findings highlight the need for futuristic location-specific flood mitigation strategies.

Learning To Accelerate Tightening Of Convex Relaxations Of The Ac Optimal Power Flow Problem, Faith Cengil, Harsha Nagarajan, Russell Bent, Sandra Eksioglu, Burak Eksioglu

Industrial Engineering Faculty Publications and Presentations

We propose a novel machine learning (ML)-based approach to significantly reduce the run times of the optimality-based bound tightening (OBBT) algorithm for strengthening the convex relaxations of the non-convex Alternating Current Optimal Power Flow (AC-OPF) problem. While OBBT can yield near-global solutions via tight convex relaxations, its runtime remains a critical bottleneck on large-scale power grids. Our key contribution is a dynamic policy that selects smaller subsets of voltage magnitude and phase-angle difference variables for sequential bound tightening at every iteration of the OBBT algorithm. This ensures that the bound-tightening process remains adaptive, thereby circumventing the stalling in the optimality …

Realization Of Deterministic Quantum Circuits For Non-Deterministic Or Incompletely Specified Quantum State Machines, Manjith Kumar, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

In classical logic design, there are machine learning methods based on converting a set of input-output traces to non-deterministic automata that are then converted to deterministic automata and synthesized using logic gates. This approach has not yet been extended to quantum automata. In this paper, we present a method to convert a set of input-output traces to a non-deterministic automaton, which is then converted to an incompletely specified multi-output Boolean function. The existing logic synthesis approaches for designing quantum circuits are insufficient to handle incompletely specified functions. So, we present a novel algorithm to synthesize logic functions with don’t cares …

Experimental Measurement Demonstration Of Initial And Steady-State Heights Of A Co2 Vertical Jet Fountain In Still Air, Brock Mcrae

Chemical Engineering Undergraduate Honors Theses

Atmospheric releases of heavier-than-air gases pose acute near-field hazards in low wind, yet the near-source behavior of vertical dense-gas jets in still air is sparsely documented. This thesis demonstrates a repeatable laboratory method for measuring the initial and steady-state rise heights of a carbon dioxide (CO₂) jet issued vertically from a floor nozzle in the CHRC ultra-low-speed wind tunnel under still-air conditions. Controlled mixtures (pure CO₂, 50/50 CO₂-air, 25/75 CO₂-air) were released at four flow rates (75, 100, 125, 150 LPM) with five repeats per condition. A fixed camera and tape-measure scale enabled video extraction of jet height using Kinovea …

Calibration And Validation Of Cyclic Stretching Platform For Stiffness Testing Of Engineered Heart Tissue, Jillian Welsh

Chemical Engineering Undergraduate Honors Theses

Cardiac fibrosis (CF) is a major contributor to the high mortality rate of heart failure which affects over 23 million people worldwide. CF involves cardiac fibroblasts depositing extracellular matrix, made primarily of collagen type I, which stiffens the heart walls over time. As testing new drugs for CF is deterred by the high cost and time required for animal and clinical trials, this research helps to solve the problem by providing an in vitro platform to study fibrosis.

The work involved creating tissues containing human cardiac fibroblast (HCFB) cells. Spring testing was conducted to determine the force applied by the …

Short-Arc Angles-Only Initial Orbit Determination For Leo And Geo Objects Using A Genetic Algorithm, Joseph R. Piini

Master's Theses

An ever-growing interest in utilizing space for scientific, commercial, and defense applications has led to an exponential rise in orbital debris recent years. With this sharp increase in space objects comes a greatly increased risk of potential collisions, necessitating an increase in Space Situational Awareness. In order to best mitigate the risk of future collisions in an increasingly congested space environment, it is crucial to be able to accurately determine the orbits of these new objects for trajectory tracking. This process is initial orbit determination (IOD), and is especially difficult when only observation angles are available for short observation times. …

Dynamic Modeling And Simulation Of A Power Generation Steam Rankine Cycle For A Fluoride Salt-Cooled High-Temperature Reactor Nuclear Power Plant, William R. Ton

Master's Theses

Nuclear Fluoride Salt-Cooled High-Temperature Reactors (FHRs) have the potential to greatly improve nuclear technology in terms of safety and cost. By combining molten salt coolant technology from the Molten Salt Reactor (MSR) and TRISO fuel technology from the Very High Temperature Gas Reactor (VHTR), FHRs may operate at significantly lower pressures than Light Water Reactors (LWRs) and with a more robust fuel source that is excellent at containing fission products. However, as no FHR has been built, there are still many design questions to address. This thesis uses transient computer modeling and simulation to investigate how an FHR could potentially …

Real Time Markerless 3d Hand Tracking For Intuitive Robotic Arm Control, Dylan G. Featherson

Master's Theses

This thesis presents a real-time, markerless motion-capture system for intuitive control of a multi-degree-of-freedom robotic arm. Using two synchronized RGB cameras and stereo-vision triangulation, the system reconstructs the three-dimensional position of a user’s hand without the need for physical markers or wearable sensors. The reconstructed 3D coordinates are mapped directly to the end-effector position of the Quanser QArm, a four-degree-of-freedom educational manipulator. Developed entirely in Python, the system integrates stereo camera calibration, 3D hand tracking with MediaPipe, coordinate transformation, and inverse kinematics into a unified real-time control pipeline operating at approximately 200 Hz. Calibration is performed through a checkerboard-based stereo …

Analyzing Patterns In Hofstede’S Cultural Dimensions Towards Individual Ai Receptiveness For Affective Experiences, Maggie Yang

Master's Theses

The use of artificial intelligence (AI) has significantly advanced efficient decision-making, with trust in algorithmic decisions shown to vary by cultural upbringing [1]. As AI becomes increasingly embedded in everyday life, it is essential to examine how cultural values affect trust in AI in subjective contexts that extend beyond purely quantitative analysis, like the personal interpretation of art. This work utilizes Hofstede’s cultural dimensions to investigate potential patterns in receptiveness towards AI predictions during art interpretation, providing insight into individual susceptibility to bias in AI-assisted affective analysis.

The study leveraged a cultural dimension survey and a custom Java program connected …

Origami-Inspired Pneumatic Soft Robotic Gripper, Conor J. Schott

Master's Theses

This thesis presents the design and evaluation of a vacuum-actuated, origami-based soft robotic gripper. A custom Sea Urchin crease pattern forms a lightweight folding skeleton that collapses radially under vacuum. The system emphasizes low cost and accessibility through laser cutting, 3D printing, and silicone molding. The Sea Urchin geometry was selected after digital and physical screening of candidate crease patterns for smooth folding, low strain concentration, and uniform inward motion. The folding skeleton is laser cut from 4 mil drafting film and folded into a compliant core. Four membrane configurations were developed: an origami gripper with a 36-inch balloon (Design …

Per- And Poly-Fluoroalkyl Substances Fate Across California Wastewater Treatment Plants: A Meta-Analysis Of Formation, Distribution, And Persistence, Elizabeth Reineke

Master's Theses

Per- and poly-fluoroalkyl substances (PFAS) are persistent contaminants that move through municipal and industrial wastewater systems with limited attenuation. As a result, they are increasingly detected in drinking water supplies. Despite growing regulatory concern, a systems-level understanding of PFAS behavior across multiple treatment facilities and watershed settings remains incomplete. This study compiled influent, effluent, and biosolids datasets from more than one hundred California wastewater treatment plants to evaluate PFAS occurrence, transformation, and partitioning across diverse treatment configurations. Analytical steps included calculating removal efficiencies, assessing precursor-to-product oxidation, evaluating co-contaminant correlations, and grouping facilities by process design to quantify configuration-specific fate patterns. …

Hallucination Techniques For Self-Supervised Synthetic Datasets For Mobile Robots, Wyatt D. Colburn

Master's Theses

Classical techniques in autonomous navigation struggle in tightly constrained spaces. Machine learning has been shown to perform better in these difficult environments but most techniques require large amounts of navigation experience for training. Using a new machine learning paradigm learning from hallucination (LfH), training data can be collected in a safe environment and not require supervision. Data is collected in real time while an agent performs a random walk in free space, supervision is not required as there are no obstacles for the robot to run into. After a random walk a post processing pipeline will hallucinate a safety corridor …

Favorability Mapping For Hydrothermal Power Resource Assessments Of The Great Basin, Usa, Stanley P. Mordensky, Erick R. Burns, John Lipor, Jacob Deangelo

Electrical and Computer Engineering Faculty Publications and Presentations

Highlights

• • The new approach to predict hydrothermal resource favorability for the U.S. Great Basin is a synthesis of modern data-driven machine learning improvements from the last several years and predicts 85 % of power-producing systems with operating power plants in the most favorable 10 % of the total area with over half of the power-producing systems (10 of the 19 exposed power-producing systems and 5 of the 9 hidden power-producing systems) in the 99th percentile.
• • The new hydrothermal favorability map predicts both hidden and exposed power-producing hydrothermal systems equally well.
• • The new hydrothermal favorability map preferentially predicts …

Optimizing Pv Solar Array Design By Analysis Of The Industrial And Training Assessment Center (Itac) Database, Angel Samuel Fernandez

Theses and Dissertations

Since 2017, the Industrial Training and Assessment Center (ITAC) at UTRGV has included photovoltaic (PV) system evaluations in its industrial energy assessments. A review of these reports showed inconsistencies in PV system design, including variations in sizing methods, performance assumptions, and application of NEC requirements. To address these issues, this thesis develops a standardized and NEC-compliant methodology for designing PV systems, incorporating demand-based sizing, solar-geometry principles, and electrical calculations guided by NEC Articles 690 and 705.

This thesis focuses on demand-based PV system sizing and incorporates NEC-guided electrical design to ensure technical compliance and safety. System performance is evaluated using …

Performance Assessment Of Reconditioned Freight Rail Bearings Using Eddy Current Array For Enhanced Nondestructive Inspection, Eduardo Miranda

Theses and Dissertations

In North America, freight bearings removed from service must undergo a reconditioning process in accordance with Association of American Railroads recommended guidelines before reuse, with approximately 80% having been reconditioned at least once. This process includes bearing inspection, where repairable defects may be refurbished and returned to service with an extended performance range of 50,000 to 250,000 miles. Motivated by this extensive range in performance, researchers at the University Transportation Center for Railway Safety, in collaboration with MxV Rail, utilized a nondestructive evaluation method to enhance the reconditioning inspection process. An Eddy Current Array (ECA) was applied to bearing cup …

Establishing Procedures For Primary Human Myoblast Cell Culture, Erica Duffy

Biomedical Engineering

Peripheral Artery Disease (PAD) affects an estimated 200 million people worldwide and is the leading cause of amputation in the United States. PAD is characterized by atherosclerotic narrowing of arteries, resulting in ischemia from reduced blood flow to distal tissues. Although surgical and percutaneous interventions can restore perfusion, fewer than 50% of patients experience sustained benefit, highlighting the need for alternative therapeutic strategies. One promising approach is promoting arteriogenesis, the growth and outward remodeling of pre-existing collateral vessels that improve blood flow around the occluded arteries. Arteriogenesis is regulated by regenerative, M2-polarized macrophages, making macrophage polarization a key therapeutic target. …

A Human Factors Analysis And Classification System (Hfacs) Approach To Compare Cardiovascular, Orthopedics, Trauma Care, And Neurosurgery, Asfandyar Khan

Doctoral Dissertations and Master's Theses

Background: Despite significant progress in patient safety, human error continues to occur at high rates in procedural settings. Traditional safety models tend to focus on retrospective incident analysis, often overlooking the systemic conditions that allow errors to occur. The Human Factors Analysis and Classification System (HFACS) offers a proactive lens to understand how and where errors emerge and is useful for identifying active and latent failures.

Objective: To evaluate the utility and reliability of the Human Factors Analysis and Classification System (HFACS) in categorizing and comparing the pattern of frequencies (events) in cardiovascular, orthopedic, trauma care, and neurosurgical procedure.

Design, …

Thermal Management With Supercritical Carbon Dioxide Under Extreme Applications, Devon Hardy

Doctoral Dissertations and Master's Theses

A unique challenge in thermal system design is minimizing the power required to operate cooling systems while maintaining effective heat removal. Traditional cooling systems utilize single-phase fluids where the heat transfer mechanisms are well understood. To meet a variety of cooling demands, a range of technologies are available, including microchannel forced convection, jet impingement, porous media, nanofluids, pin fin arrays, and film cooling, each offering distinct advantages and limitations. While the performance of single- or two-phase cooling systems are generally predictable, in extreme thermal environments, new cooling solutions are needed to improve overall system efficiency and reliability.

Supercritical fluids, particularly …