Engineering Commons^™

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 …

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 …

Propeller Noise Prediction Of An Urban Air Mobility Vehicle In Urban Environment, Jie Hua

Doctoral Dissertations and Master's Theses

Urban Air Mobility (UAM) vehicles operate in complex, unsteady aerodynamic environments where wake interactions, gust and turbulence significantly affect both performance and noise generation. Understanding these mechanisms is critical for developing quieter and more efficient eVTOL systems that meet future community noise and certification requirements. This dissertation focuses on the high-fidelity numerical investigation of propeller noise in three representative unsteady loading scenarios: (i) transition (tilt) flight, (ii) edgewise inflow, and (iii) wake–propeller interaction. Each case emphasizes different physical mechanisms that dominate noise generation in UAM operations. Hybrid turbulence-resolving approaches—Detached Eddy Simulation (DES) and Delayed Detached Eddy Simulation (DDES)—are coupled with …

Solar Powered Conservation: The Effects Of Solar Photovoltaic Facilities On Avian Community Composition, Michael Christopher Ferrara

Graduate Theses and Dissertations

The expansion of solar photovoltaic energy infrastructure is transforming landscapes worldwide. Increasingly, facilities are planted with native vegetation, yet how vegetation characteristics and landscape variables shape wildlife communities in solar facilities remains poorly understood. Because avian populations have been in decline and are sensitive to habitat changes, understanding how solar facilities influence avian communities is important. In Chapter 1, we used autonomous recording units, local vegetation measurements, and land use and land cover data to quantify how avian community occupancy is influenced by solar cover in solar facilities and comparable reference sites. We used a Bayesian multi-species occupancy model to …

Advanced Membrane Methods For Treatment Of Toxic Contaminants And Education Of Early-Career Researchers, Thomas Mckean Iii

Graduate Theses and Dissertations

Membrane technologies are attractive as they are linearly scalable and often require lower operating costs compared to other technologies. One area where they are particularly effective is the treatment of water contaminated with toxic substances. The simplicity of this removal mechanism provides reliable performance capable of meeting stringent removal requirements. However, membrane fouling is a major challenge that often limits their commercial viability. This research sought to investigate novel approaches to pretreatment and membrane modification to overcome fouling and high operating pressures. In addition, membrane separation processes can often be developed into simple yet educational experiments that are ideal for …

Extending Touch: Investigating Sensorimotor Integration, Cognitive Workload, And Presence With Neuro-Haptic Feedback In Virtual Reality, Aliyah Khadijah Shell

Graduate Theses and Dissertations

Sensory feedback from the hand is fundamental for the coordination of fine motor skills and overall sensorimotor function. Impaired somatosensation during task execution has been associated with the development of inaccurate motor plans, which can hinder motor learning. Virtual Reality (VR) has emerged as a promising tool for motor rehabilitation; however, most VR-based interventions overlook the critical role of tactile feedback in motor control. The absence of touch feedback, which is integral to conventional rehabilitation and training, may limit the full therapeutic potential of VR. Integrating functionally relevant neurostimulation based haptic feedback (neuro-haptic feedback) into VR-based interventions may enhance functional …

Development Of A Handy Tool For The Selection Of Urban Stormwater Best Management Practices, Aaron T. Kenny

Civil & Environmental Engineering Theses & Dissertations

The City of Norfolk, Virginia faces substantial stormwater management challenges due to shallow groundwater, tidal influence, dense urban development, and limited right-of-way. These constraints limit the applicability of many Best Management Practices (BMPs) and require the early identification of feasible practices before detailed hydrologic modeling. This thesis introduces a decision-support tool that quickly and systematically identifies and prioritizes BMPs that are both feasible and well-suited to Norfolk’s Municipal Separate Storm Sewer System (MS4) program, streamlining early-stage selection and saving time and resources.

The tool implements a two-stage methodology. First, feasibility gates are applied using catalog attributes derived from the Virginia …

On The Scalability Of Anisotropic Mesh Adaptation On Distributed And Shared Memory Architectures For Numerical Approximations, Kevin Mark Garner Jr.

Computer Science Theses & Dissertations

Mesh generation is a critical component in numerical approximations of Partial Differential Equations (PDEs). One such example includes Computational Fluid Dynamics (CFD), as CFD simulations in turn are crucial for applications in many industries, such as personalized healthcare and the design of aerospace vehicles. Generating high quality meshes for large-scale CFD problems presents a significant bottleneck in the CFD workflow. This dissertation proposes “fast,” parallel 3D mesh generation methodologies that are designed to leverage the concurrency offered by emerging High-Performance Computing (HPC) architectures. First, a distributed memory method is presented that integrates a sequential state-of-the-art isotropic, advancing front local reconnection-based …

Machine Learning For Anomaly Detection In Neural Network Security And Srf Cavities, Hal Ferguson

Electrical & Computer Engineering Theses & Dissertations

This dissertation explores the development and deployment of machine learning approaches to address critical challenges in anomaly detection across two distinct domains: neural network security in federated learning settings and cavity behavior analysis in particle accelerator operations at Jefferson Lab in Newport News, Virginia. Anomaly detection identifies deviations from expected patterns, safeguarding systems in cybersecurity, industry, and research against malicious activities and failures. This dissertation demonstrates how our machine learning approaches enhance detection accuracy and efficiency in both neural network security and industrial applications.

First, we investigate vulnerabilities in deep neural networks deployed in federated learning. Although federated learning preserves …

Design And Assessment Of A Single-Blade Rotary Wing For Use In Vertical Takeoff And Landing (Vtol) Aircraft, William C. Mcmasters

Mechanical & Aerospace Engineering Theses & Dissertations

A single-bladed propeller was designed to determine its efficacy in increasing efficiency of quadplane aircraft in the cruise configuration while still providing sufficient vertical lift for the vertical takeoff portion of flight. Aerodynamic theory predicts higher efficiency for single-blade propellers, resulting in a lower power requirement. A counter-weighted single-blade was modeled after a 10x5 model aircraft propeller used in small unmanned vehicles with a steel counterweight to balance centrifugal forces. The propeller was tested in the ODU wind tunnel to determine performance at various Advance Ratios (J). The research suggests that single-blade propellers show comparable performance compared to two-bladed propellers …

Comparative Analysis Of Emergent Behaviors Of Three Drone Swarm System Models For Targeting Using Agent-Based Modeling And Simulation, Arsenio T. Gumahad Ii

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation introduces a novel computational simulation framework for evaluating the emergent behaviors of three swarm drone models using Agent-Based Modeling and Simulation (ABMS). The three swarm models are a Leader-Follower swarm model based on Bruckstein's antline theory, a Flocking model based on a simplified Reynolds 'Boids’ model, and a Stigmergic model with pheromone-based coordination. The primary objective of the simulation is to evaluate the performance of these models in delivering a user-defined number of drones of each type to a target area of interest in four separate scenarios, resulting in 50,000 separate simulation trials. Each scenario was structured to …

Thermal Management Of Power Electronic Converters In Electric Motor Drives Using Active Thermal Control And Active Cooling, S M Imrat Rahman

All Dissertations

The application of power electronic converters (PEC) in electric vehicles (EVs) has significantly increased due to their enhanced controllability and flexibility. Additionally, Permanent Magnet Synchronous Machines (PMSMs) are favored in EVs for their higher torque, efficiency, performance, and heat dissipation capabilities compared to asynchronous machines. The reliable operation of power converters in PMSM drives is crucial for EV operation, and this is driving interest in developing innovative and sustainable technologies that ensure the safe and reliable functioning of PECs. One of the main challenges in achieving reliable PECs is designing effective thermal management systems to control junction temperature and reduce …

Machine Learning-Enabled Safety-Critical Model Predictive Control For Uncertain Dynamical Systems, Hossein Nejatbakhsh Esfahani

All Dissertations

This dissertation explores the interactions between Model Predictive Control (MPC), Safety-critical Control, and Artificial Intelligence (AI)/Machine Learning (ML) methods, with a particular focus on Reinforcement Learning (RL) and Bayesian Optimization (BO). We then leverage AI/ML to address several challenges in the control design and safe operation of uncertain dynamical systems. In many applications, ranging from autonomous vehicles and robotics to energy systems and industrial processes, ensuring safety is as essential as satisfying control objectives. The use of Control Barrier Functions (CBFs) within the MPC framework recently has emerged as a powerful tool to guarantee safety by enforcing constraints in optimal …

Reverse (Bio)Engineering: A Machine Learning Approach To Optimize Baseball Pitcher Health And Performance, Robert C. Moore

All Dissertations

Ball tracking systems are becoming ubiquitous in sport, creating an unprecedented opportunity for big data applications to optimize human health and performance. These applications are especially common in baseball, a sport known for analyzing ball flight data to quantify performance. Analysts routinely use ball flight data to identify the attributes of top performing pitchers, finding that the best pitchers throw with optimal combinations of release speed and spin to precise locations. However, for certain pitchers, the throwing motion required to produce optimal ball flight places exceedingly high biomechanical load on the elbow, and consequently injury rates continue to rise. This …

Hybrid Learning For Rough Terrain Navigation Of Actively Articulated Wheeled Vehicles, Dhruv Mehta

All Dissertations

Conventional wheeled ground vehicles have been used for rough terrain navigation in the recent years. They consist of a chassis connected to wheels through passive, semi-active, or active suspension systems. However, their fixed configurations limit mobility and maneuverability, constraining their ability to autonomously navigate diverse and rough terrains. Autonomous Ground Vehicles (AGVs) face significant challenges in this regard, including varying terrain roughness, soil hardness, and obstacle crossing.

To address these limitations, Actively Articulated Wheeled Vehicle (AAWV) architectures have recently emerged, offering real-time geometric adaptability. AAWVs have chassis and wheels connected via articulated serial or parallel linkages. However, increased articulation introduces …

Data-Driven Discovery Of Finite-Dimensional Koopman Operator For Modeling And Control Of Uncrewed Ground Vehicles, Ajinkya Joglekar

All Dissertations

This dissertation advances data-driven modeling and adaptive control techniques for Uncrewed Ground Vehicles (UGVs), with a focus on autonomy in mission-critical and safety sensitive environments. UGVs are deployed across a wide spectrum of domains, from structured manufacturing shop floors to unstructured off-road terrains, including planetary exploration, precision agriculture, and disaster response. These platforms, operating in dull, dirty, and dangerous conditions, demand autonomy that is both adaptable and robust. While traditional model-based control methods offer interpretability and robustness, they struggle with unmodeled dynamics, parameter variations, and integration of high-dimensional sensing. Conversely, modern machine learning approaches can directly exploit sensory data but …

Integrating Dft And Machine Learning To Predict Structural Properties In High Entropy Alloys, Nathan Linton

All Dissertations

In the past decade, a paradigm shift in the design of metal alloys has been observed. These new alloys are commonly referred to as high entropy alloys (HEAs), multi-principal element alloys (MPEAs), or complex, concentrated alloys (CCAs). In contrast to conventional alloys, which consist of one main element (for example 80%) with other elements in small amounts, HEAs are made of four or more main elements ranging from 5 to 35% each element. Due to the large presence of multiple elements, HEAs have shown substantial material property improvements over conventional alloys such as steel. For example, they have high ductility …

Particle Migration In Non-Newtonian Fluid Flows Through Curved Microchannels, Sanskruti Ramesh Raut

All Dissertations

Innovations in microfabrication over the past three decades have enabled the development of microfluidic devices with intricate channel geometry. Microfluidic platforms offer controlled manipulation of fluids and particles by leveraging the internally induced and/or externally imposed force field(s). The demand for compact microchannel geometry has turned the attention toward curved microchannels with significantly reduced footprints. However, most of the previous studies in curved microchannels have been limited to particle migration in Newtonian fluids. The influence of fluid rheology has remained largely unexplored.

In the first part of this dissertation, we present a systematic experimental study on the influences of fluid …

Accident Data Analytics And Ai-Based Auditory Enhancement For Highway Construction Safety, Thinh Nguyen

All Dissertations

This research develops data-driven and AI-enhanced approaches to improve worker safety in highway construction environments. The study integrates advanced analytics and auditory signal enhancement to identify high-risk worker behaviors and improve real-time safety warnings. The work consists of three core studies. The first study applies Sequential Pattern Mining and Social Network Analysis to more than 1,000 construction accident reports to identify high-risk worker actions and their hidden sequential relationships with accident types and consequences. These insights reveal sector-specific risk patterns, supporting the creation of targeted, data-informed safety interventions. The second study introduces an AI-based auditory enhancement model built on a …

Universal Systems Simulation Via Constraint Hypergraphs With Applications To Digital Twins, John Morris

All Dissertations

The characterization of systems encompasses a variety of modeling frameworks designed to capture specific behaviors and components of various system domains. Whatever the framework, the core elements of a system representation are the information of the system and a description of how that information is related. The relations in deterministic systems are functions, which, when composed to form executable processes, can be used to simulate system data. A declarative modeling framework is one that encodes mechanisms for preparing these simulations within the model structure, allowing an external agent to form the execution processes required for a given context. To date, …

Purifying Circular Rna Therapeutics, Karen Guillen-Cuevas

All Dissertations

Circular RNA (circRNA) has emerged as a promising therapeutic modality due to its enhanced stability and resistance to exonuclease degradation compared with linear mRNA. However, its stability and functionality depend strongly on achieving high purity, and current methods such as size-exclusion chromatography suffer from peak overlap, low yields, and poor scalability. This dissertation addresses these limitations by developing ultrafiltration-based strategies to purify circRNA directly from in vitro transcription (IVT) and self-splicing (circularization) reactions. First, the feasibility of ultrafiltration was demonstrated using polyethersulfone membranes, where sieving coefficients and critical flux values of circRNA, precursor RNA, and nicked RNA were measured to …

End-To-End Direct Current For Standalone Power Network, Eyad Ahmad Aldarsi

All Dissertations

The primary issue that faces the humanity is climate change and because of that greenhouse gases (GHGs) emissions are rising. The consequences of this issue have emphasized the necessity for replacing the dominant method of electricity generation, which mostly utilizes fossil fuels, to be centered on access to all, green, low-cost, and renewable sources of energy. Currently, photovoltaics (PV) and wind turbines are the two technologies so far that can convert the source of renewable energy, which is produced by sun irradiance and wind respectively, into large-scale electric power that can be distributed into the electricity grid. The work in …