Digital Commons Network^™

A Machine Learning Framework For Early-Stage Cost Estimation Of Transportation Projects, Pritom Paul

Electronic Theses and Dissertations

To address the limitations of traditional planning-level cost estimating methods, such as reliance on statewide averages, heavy reliance on engineering judgment, and high levels of inaccuracy, this study developed two data-driven frameworks and corresponding tools. The first framework focused on resurfacing projects and used treatment-specific simple linear regression based on lane miles and geographic location. The second addressed a broader group of construction projects and used multiple linear regression with project length, route type, and right-of-way cost as key predictors. In both frameworks, the final estimates are computed by aggregating multiple estimates produced by county-, region-, and state-level models. The …

Decomposition And Spectral Characterization Of Unsteady Loads In Pulse-Jet Propulsion Testing, Cesar Benitez

Theses and Dissertations

Pulsed jet propulsion systems produce inherently unsteady forces whose time-resolved characterization is essential for performance assessment, yet the measured load signal conflates aerodynamic forcing with the dynamic response of the measurement balance itself. This thesis develops a load centered framework for the dynamic characterization of a pulsed jet system, treating the measured load fluctuation as the primary physical observable rather than attempting full true-thrust reconstruction. A single-degree-of-freedom balance model identified through ringdown testing provides the structural reference scale, yielding a natural frequency of 8.5 Hz and damping ratio of 18%. Power spectral density, phase-averaging, and synchronous–residual decomposition is applied uniformly …

Detecting Sophisticated Cyberattacks On Public Water Infrastructure, Ayrton Purdy

Graduate Theses and Dissertations (2019 - present)

In recent years there has been an increasing number of cyberattacks on public water generation and distribution systems. Advanced persistent attackers could usurp sensors and control systems to contaminate public drinking water. In order to conceal their malicious activity, they can manipulate sensor data flows to give the appearance of normal activity. The compromised sensors would report normal chemical levels even though unsafe water is entering the distribution system. In response, this research proposes a multi-sensor, cross-comparison approach to anomaly detection. The proposed approach is designed to detect sophisticated cyberattacks which are not easily detectable using traditional cyber tools. The …

Developing A Framework For Microchip Design Recovery, Eric Diep

Graduate Theses and Dissertations (2019 - present)

Due to the increase in diverse chip production over the past decade, reverse engineering has become a difficult and daunting task. This research develops a methodology for microchip design recovery, seeking to validate and reproduce prior approaches to physical reverse engineering using low-cost tools and techniques. We used mechanical hardware abrasion tools and techniques to delayer and capture silicon integrated chip (IC) layout. We focused on the Mifare Classic EVl microchip, commonly implemented in public transit/transportation cards, to extract information for design recovery. The research explores limitations and advantages of mechanical abrasion and optical microscopy in context to modem chip …

Manufacturing Systems: Characteristics And Dynamics, Alan J. Fitzmorris

Graduate Theses and Dissertations (2019 - present)

This research answers three basic questions. First, what are the behaviors (dynamics) of a manufacturing system in the context of system performance? Are these dynamics best described as linear deterministic, periodic, nonlinear deterministic, or stochastic? Second, what are the complexity (chaotic) characteristics of a manufacturing system, namely the maximal Lyapunov exponent, correlation dimension, and Kolmogorov-Sinai entropy? Third, is there a relationship between complexity characteristics and manufacturing system performance? This research involves four high level steps: data analysis, system dynamics analysis, system complexity analysis, and correlation analysis. The data analyzed consists of concrete plant and shipbuilding shop time series performance data. …

Enhancing Food Security In Stann Creek, Belize Using Meat Rabbits: Engineering Perspective, Lindsey Garretson

Biological and Agricultural Engineering Undergraduate Honors Theses

The purpose of this paper is to discuss the engineering perspective within the overall project of using meat rabbits to enhance food security and nutrition within Stann Creek, Belize. From the engineering perspective, the overarching goals were like the overarching project goals including the construction and materials required guide within the manual, designing potential upgrades to the design including a solar and battery system and an automatic watering system, and to design the system to be “practically sustainable” where possible. The constraints for this project included cost, the size of land dedicated for the rabbitry, and the operational and environmental …

Cationic Polymer-Grafted Magnetic Nanoparticles For Enhanced Removal Of Anionic Dyes From Wastewater, Joia A. Traver

Chemical Engineering Undergraduate Honors Theses

Water scarcity and pollution are escalating global challenges, with textile industry wastewater often enriched with toxic dyes posing significant risks to environmental and human health. These contaminants increase turbidity, reduce dissolved oxygen levels, and ultimately impair aquatic ecosystems. This thesis focuses on the remediation of dye-contaminated water using nanoscale polymeric adsorbents. Methyl orange, a common anionic dye widely used in textile and leather industries, was selected as the model contaminant due to its terminal sulfonate group, which enables strong electrostatic and hydrogen-bonding interactions with cationic functional materials.

In this work, magnetic nanoparticles grafted with cationic polymers were synthesized and evaluated …

Demonstration Of The Relationship Between Irwin Spire Quantity And Boundary Layer Depth In The Chemical Hazards Research Center Wind Tunnel, Jace D. Beckwith

Chemical Engineering Undergraduate Honors Theses

Atmospheric Dispersion Models (ADMs) are computer-based simulations used to model gas releases for enforcing regulatory compliance, designing facilities, and responding to emergencies. Because ADMs rely on complex mathematical models, they require experimental validation to ensure accuracy. Wind tunnels offer a controlled, repeatable method for gathering validation data. The Chemical Hazards Research Center (CHRC) at the University of Arkansas operates an ultra-low speed wind tunnel for this purpose. A key feature of this tunnel is its simulated Atmospheric Boundary Layer (ABL). The simulated ABL is a turbulent layer in which wind speed increases logarithmically with height from near zero at the …

Ngc - Torch Test Ablation Stand Improvements And Upgrades, Sarah Nelson

Undergraduate Honors Capstone Projects

This capstone project is sponsored by Northrop Grumman (NGC). The goal of the project is to redesign an ablation torch testing system to improve usability, safety, and versatility. Northrop Grumman relies on their ablation torch testing system to conduct quantitative evaluations of materials and high stress and high temperature conditions. The system provides essential data that supports product development, safety validation, and compliance with performance standards. By improving usability, safety, and versatility, NGC will be able to streamline testing operations, increase accuracy of results, and reduce operator risk. The system must allow testing using both a bent and straight torch …

Additive Manufacturing Of Spatially Variant Actuating Structures From Shape Memory Polymers., Katia Lizbeth Delgado Ramos

Open Access Theses & Dissertations

This dissertation studies the structure-processing-function relationships of additively manufactured shape memory polymer blends, with emphasis on mechanical anisotropy. Chemical exposure, thermally activated recovery, self-healing behavior, and 4D printed functional response. Two polyester-based blends were studied: a binary blend composed of polycaprolactone and thermoplastic polyurethane (PCL/TPU) blend, and a ternary blend composed of polycaprolactone/thermoplastic polyurethane/ polylactic acid (PCL/TPU/PLA) blend. The materials were melt-compounded using a twin-extruder to produce filament for fused filament fabrication (FFF). Specimens were fabricated using four different raster orientations, 0°,90°, 0/90°, and 45°, to investigate the influence of processing architecture and composition on the mechanical performance, recovery behavior, …

Development Of A Simulation-Driven Evaluation System For Foreign Objects In Aircraft Structures, Daniela Garcia

Open Access Theses & Dissertations

This thesis investigates the use of simulation-driven methods to evaluate the behavior and potential impact of foreign objects within aircraft structures. Foreign Object Damage (FOD) remains a major concern in aerospace safety, as small components unintentionally left inside aircraft compartments can create uncertainty regarding their effect during flight. Although current inspection methods can detect the presence of foreign objects (FOs), they often cannot determine whether these objects pose a significant structural risk, leading to conservative maintenance decisions. To address this limitation, this work develops a simulation-based framework that integrates Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) to evaluate …

First-Principles Study Of Uranium Mononitride, Roy Noe Herrera Navarro

Open Access Theses & Dissertations

This thesis presents a first-principles investigation of uranium mononitride (UN), withemphasis on the connection between uranium 5f electron correlation and defect stability. Electronic-structure calculations were performed within density functional theory using the Vienna Ab initio Simulation Package. Exchange-correlation effects were treated within the generalized gradient approximation, and a Hubbard correction was applied to the uranium 5f manifold. The adopted Hubbard parameter was motivated by first-principles linear-response analysis and considered in the broader context of DFT+DMFT descriptions of correlated uranium systems, including recent interpretations of UN as a Hund-metal system. Bulk UN was studied in unit-cell and 2 x 2 x …

Bridging Industry And Academia In Engineering Leadership Education: Using Q Methodology To Identify The Viewpoints Of Engineering Professionals On Effective Engineering Leadership, Pamela Edith Campos Valles

Open Access Theses & Dissertations

Background: Engineering leadership has been recognized as a key professional skill by the U.S National Academy of Engineering, leading to increased attention and integration in engineering education research and development. The perception and recognition of leadership within the engineering field remains limited by the widespread definitions of leadership and limited characterization of engineering leaders. The Contextual Engineering Leadership Development framework is grounded on a discipline specific definition of engineering leadership and approaches to leadership development derived from engineering undergraduate programs. The use of this framework provides the opportunity to describe what engineering leaders prioritize, enabling the identification and characterization of …

Mitigating Inertial Measurement Unit Drift In Quadcopter Trajectory Tracking Using Kalman Filter Sensor Fusion With Global Positioning Measurements, Juan Sandro Caballero Aguilar

Graduate Theses and Dissertations

Unmanned Aerial Vehicles (UAVs) like quadcopters are widely used in civilian and military applications such as farming, photography, search and rescue missions, and autonomous navigation and motion. The performance and stability of these systems depend on accurate state estimation, which provides real-time information about the vehicle’s position, velocity, and orientation. However, achieving reliable state estimation is challenging due to sensor noise, measurement uncertainty, and inaccurate modeling. Common navigation sensors such as the Global Positioning System (GPS) and Inertial Measurement Units (IMUs) exhibit complementary characteristics. GPS provides absolute position measurements but suffers from noise, multipath effects, and low update rates, while …

From Reactive To Predictive: A Hybrid Trust-Mediated Adoption Framework For Data-Driven Maintenance In Distributed-Authority Aviation Environments, Dustin J. Foote

International Journal of Aviation, Aeronautics, and Aerospace

Modern aviation maintenance operates within increasingly data-intensive technological environments, yet the operational integration of predictive maintenance into routine decision-making remains inconsistent across sectors. Contemporary aircraft incorporate centralized maintenance computers and condition monitoring architectures capable of fault aggregation, exceedance capture, and trend-based data collection. Although prognostics and health management research continues to advance detection and prediction methods, implementation outcomes often depend on factors beyond analytical performance alone.

This paper examines predictive maintenance adoption in distributed-authority aviation environments and argues that constraints emerge less from sensing capability than from organizational structure, decision authority dispersion, and institutional trust dynamics. For purposes of analysis, …

An Investigation Of Data Granularity In Rag Pipelines For Personalized Medicine, Paritosh Pandey

Master's Theses

Generative AI, exemplified by large language models like the OpenAI GPT and Meta LLaMA families, can produce diverse content in response to prompts. This capability offers a promising solution to challenges in precision medicine, which seeks to tailor treatments to individual clinical profiles but often struggles with data collection, cost, and privacy concerns. By generating realistic, privacy-preserving patient data, generative AI has the potential to transform patient-centric healthcare. With such motivation, this research develops a comprehensive Generative AI pipeline emphasizing data granularity for accurate prediction of personalized treatments. The pipeline features a central Large Language Model interacting with a Machine …

A Webcam Eye Tracking Infrastructure For Software Engineering Tasks, Zachary M. Kozak

School of Computing: Dissertations, Theses, and Student Research

Performing eye tracking utilizing commodity webcams has been explored for over a decade, but limited camera quality and sensitivity to head movements have hindered its adoption in research settings. Recent advances in consumer-grade webcams and machine learning methods present an opportunity to improve the accuracy of webcam eye tracking and extend the feasibility of studies beyond controlled laboratory environments.

Current popular webcam eye tracking methods restrict implementations to the browser and rely on continuous user interactions for calibration, limiting the kinds of studies that can be conducted. This thesis presents a feature-based gaze prediction system that incorporates eye geometry and …

Leveraging Code Embeddings To Identify And Address Blind Spots In Benchmark Creation, Charles Moloney

School of Computing: Dissertations, Theses, and Student Research

Formal software verification remains critical for early vulnerability detection, yet benchmarking these tools is costly and often reliant on centralized datasets such as SV-COMP. While such repositories enable standardized evaluation, they introduce risks of overfitting and bias, particularly due to first-party benchmark contributions. To address these limitations, we extend ARG-V, our tool for generating SV-COMP-compatible benchmarks from real-world Java code, with a novel approach of using code embedding techniques to selectively sample from mined code. By leveraging Nomic Embed Code and a cosine-based Minimum Hyperspherical Energy (MHE) objective, we systematically select and transform benchmarks from scraped GitHub code that …

Design And Development Of A Passive Dust Protection System For Lunar Docking Operations, Simon Thengvall

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

Lunar docking systems face a unique set of environmental conditions that can create significant challenges for mechanical design. Among these, the abrasive nature of lunar regolith can impair the kinematic function of traditional terrestrial mechanisms as well as contaminate critical spacecraft components such as environmental seals, causing them to fail. For crew-rated docking systems, failure of these systems not only threatens mission success, but also crew safety, so dust protection is crucial for docking components. To address the concerns of regolith intrusion, the Simple External Attachment for Lunar Openings (SEALO) is developed as a key architecture for mechanism evaluation when …

Learning Global Context For Sparse Activity Recognition In Lengthy Recordings With Limited Dataset Size, Zeyu Tang

All Dissertations

This dissertation describes methods to analyze lengthy recordings of data in order to detect sparsely occurring activities. The narrative below describes the progression of research that led to the development of these methods and their generalization into a unified framework. My research started with designing models for dietary monitoring, including detecting meals from day-long recordings and detecting intake gestures from meal-length recordings. Both tasks share some common characteristics: (a) the target event takes only a small portion of data recordings, and (b) there is global context within full-length data recordings that can help a model make better decisions. After finishing …

Decision Making For Large-Scale Problems Under Uncertainty And Conflict, Benjamin J. Hamlin

All Dissertations

Large-scale decision-making problems appear in many areas including long-range forecasting such as energy generation forecasting. Many such problems are subject to conflicting objectives and uncertain data, and can be modeled as linear optimization problems. We study novel theoretical results and algorithms for large-scale linear decision problems under conflict and uncertainty. First, we propose a parametric Benders decomposition algorithm for solving large-scale linear optimization problems with multiple objectives or deterministically uncertain objectives. Second, we extend the parametric Benders decomposition to a multi-stage setting, developing a parametric stochastic dual dynamic programming algorithm, which enables decision-making when conflicts and uncertainty have planning impacts …

Development Of A Mixing-Controlled Combustion Model For 0d Engine Modeling: Using High-Order Models To Guide The Formulation Of Reduced-Order Models, James Gohn

All Dissertations

Vehicles are becoming increasingly complex to comply with the increasingly stringent regulations placed on all market sectors while still maintaining performance requirements. This increased complexity leads to increases in the cost and time it takes to develop and produce these next generation vehicles. To meet demand therefore, it becomes necessary to evaluate numerous design iterations using computer models. There are multiple levels of models that may be necessary for different purposes or use cases. All levels of modeling for virtual prototyping, however, require a level of validation and predictive ability to be useful. To this end, the following thesis presents …

Multiscale Architecture Governs Stability In Suction-Actuated Variable Stiffness Catheters, Sheridan Lee

McKelvey School of Engineering Graduate Student Theses & Dissertations

Endovascular procedures require devices with widely varying mechanical properties: flexibility for navigating tortuous vessels and rigidity for stable therapeutic delivery. Suction-actuated variable stiffness sheaths address this challenge by incorporating axial wire string arrays that mechanically couple under suction to increase flexural rigidity. However, prototype devices achieve stiffening ratios below theoretical predictions, suggesting that interlayer mechanics and string positioning play a critical role. This study investigates whether interweaving polytetrafluoroethylene (PTFE) tape within the string array enhances flexural rigidity modulation and curvature stability. Prototype devices with varying wrap configurations were fabricated and evaluated using flexural testing, curvature stability testing, and mathematical modeling. …

Computational Fluid Dynamics (Cfd)-Based Performance Prediction Of Transcatheter Microvascular Plugs In Single-Ventricle Patients, Zhuhuan Zou

McKelvey School of Engineering Graduate Student Theses & Dissertations

Transcatheter palliation using fenestrated Modified Micro Vascular Plugs (MVP) has emerged as a promising, minimally invasive alternative to surgical pulmonary artery banding (PAB) for high-risk neonates with single-ventricle physiology. However, clinical applications are currently limited by the difficulty in predicting the resulting pulmonary-to-systemic flow ratio () and the lack of a standardized approach for selecting the optimal fenestration size. This study utilizes patient-specific computational fluid dynamics (CFD) to quantitatively evaluate the impact of varying fenestration diameters on circulatory balance. Patient-specific 3D models of the pulmonary artery (PA) were reconstructed from imaging data for two clinical cases using SimVascular. Transient CFD …

Conditioning Hierarchical Diffusion Transformers On Rf Circuit Parameters, Ethan Morton

McKelvey School of Engineering Graduate Student Theses & Dissertations

As modern ML techniques have become increasingly advanced, they have begun to be integrated into wireless RF systems for classification, identification, and spectrum management. Deep Neural Networks (DNNs) enable RF system operators and designers to design more flexible systems with greater robustness to errors and attacks. However, neural networks require significant amounts of properly annotated data to train. Current data labeling methods lack the ability to obtain reliable true labels for circuit properties such as carrier frequency offset (CFO), power amplifier (PA) non-linearity, and in-phase/quadrature (IQ) imbalance. This thesis investigates the efficacy of a novel architecture, RF-Diffusion, for generating high-quality …

Machine Vision For In Situ Measurement And Control Of Wire Stickout In Lwded Process, Braden Mclain, Remy Mathenia, Todd Sparks, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This work presents a machine-vision–based measurement and control framework for laser wire directed energy deposition (LWDED) processes. A visible-light camera system is used to capture meltpool images, from which a novel vision algorithm extracts the wire–meltpool interface location. By utilizing a camera that is rigidly mounted to the deposition head, the vision algorithm provides a relative measurement of the distance between the nozzle tip and the workpiece, also referred to as wire stickout. A proportional-derivative (PD) control strategy is implemented using the measured stickout as feedback to adjust deposition feedrate. Results show that the control system successfully compensates for improper …

Integrated Geophysical, Geotechnical, And Mineralogical Characterization Of Expansive Weches Formation Soils In East Texas: Implications For Infrastructure Design, Samuel Annobil

Electronic Theses and Dissertations

This study investigates the geotechnical, geophysical, and mineralogical characteristics of soils derived from the Weches Formation in Nacogdoches County, East Texas, with emphasis on the relationships among electrical resistivity, moisture condition, compaction state, and mineralogical composition. The Weches Formation is well known for producing clay-rich, moisture-sensitive soils that pose challenges to subgrade performance because of their plasticity and swelling behavior. Representative soil samples were collected and subjected to laboratory testing, including particle size analysis, Atterberg limits, Standard Proctor compaction, free swell tests, electrical resistivity measurements, and X-ray diffraction (XRD) mineralogical analysis. The soils are predominantly fine-grained and clay-rich, with USCS …

Reward Representation Learning, Gregory M. Hyde

Dartmouth College Ph.D Dissertations

The \emph{Markov decision process} (MDP) has long served as the canonical model for sequential decision-making. However, it assumes that the reward function is Markov with respect to a given state representation---an assumption that often does not hold in practice. Instead, agents typically only perceive streams of observations and actions and must infer the latent structure according to which reward unfolds over time. From this perspective, reward prediction is initially non-Markov, reflecting a mismatch between the agent's current representation and the underlying structure of the environment.

In this thesis, we advance the view that reward is not simply a signal to …

Analysis Of Oscillating Flow Over A 2-D Airfoil With Flow Reversal, Colter Couillard-Rodak

McKelvey School of Engineering Graduate Student Theses & Dissertations

Finite-state models are useful tools in modeling the aerodynamics of rotorcraft in flight simulators. 2-D and 3-D finite-state models have been developed and compared to closed form solutions, however these models are currently unable to handle situations where the freestream changes directions and the rotor re-enters its own wake. A 2-D finite state model was previously developed that includes a parameter that accounts for the change in free stream. This model, however, contains an inherent stability issue at the instant that the velocity changes direction.

The effects of this instability can be mitigated in certain flow conditions. A purely oscillatory …

Feasibility Study Of Transitioning From Thick Plates (0.250”) Mounted On 30-Point Pvc Carriers To Thinner Plate Technologies Mounted On Recyclable Foam And Pet (0.155”) For Post-Print Corrugated, Nathaniel J. Poole

All Theses

In the United States, the most common press configuration for brown-box printing is a 0.280” undercut press. These press configurations have long relied on thick 0.250” plates mounted on 0.030” PVC sheets to print onto corrugated substrates. Each year, around twenty million pounds of waste are produced by the printing industry, through paper waste, plate waste, among other materials. One large factor of that waste is flexographic plate waste, which either ends its life in a landfill or is repurposed into other products. This study establishes a comparison between traditionally used 0.250” plates on 30pt PVC versus 0.155” plates mounted …