Engineering Commons^™

Nonlinear Oscillations In Structural Dynamics: Computational Techniques, Data-Driven Tools, And Model Order Reduction, Dalton Stein

Open Access Dissertations

Funding and support for this research was provided by the National Institute for Undersea Vehicle Technology (NIUVT) through the Office of Naval Research (ONR). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Office of Naval Research.

The content of this dissertation has been removed because it is CUI.

Advancing Ethical Innovation In Human–Ai Collaboration: Trust And Legitimacy In Technology-Mediated Teams, Sanket Ramchandra Patole

Human Resource Development Theses and Dissertations

Human Resource Development (HRD) confronts a central paradox in the digital age. The technologies designed to broaden access to learning and collaboration often reproduce the same social hierarchies that HRD seeks to challenge. Artificial intelligence (AI), digital collaboration platforms, and algorithmic management are widespread features of organizational life. Yet these systems do not generate inclusive outcomes for all workers. Women of Color (WoC), situated at the intersection of racialized, gendered, and technological structures, experience digital transformation as both possibility and constraint. They encounter opaque decision systems, diminished authority in virtual teams, and digitally-mediated microaggressions, while also developing new capacities for …

Beyond Permissions: A Privacy And Security Analysis Of Sensor And Network Activity On Xr Devices Using Xrmonitor, Gayatri Sravya Siripurapu

Computer Science and Engineering Theses - Archive

Standalone virtual reality headsets integrate multiple sensors and cameras whose runtime behavior is not transparently documented, creating potential privacy and security risks that are difficult to audit using existing tools. The relationship between software feature activation and the underlying hardware engaged at runtime remains opaque, limiting the ability of users and researchers to assess what data is being collected and when.

This thesis presents XRMonitor, a unified framework for monitoring and analyzing sensor activation behavior and network traffic on Meta Quest devices. The framework is motivated by the lack of transparency in how standalone XR devices engage their hardware sensors …

Pre-Training And Interpretability In Deep Learning Models, Weizhi An

Computer Science and Engineering Dissertations

In the evolving field of artificial intelligence, the efficacy of deep learning models is often gated by the quality of their training and the clarity of their decision-making processes. This dissertation addresses these crucial challenges by focusing on two key areas: enhancing pre-training strategies and improving model interpretability. Our approach is twofold, integrating novel pre-training methodologies that embed domain-specific knowledge early in the model training process, and developing advanced techniques for disentangling and clarifying the decision-making mechanisms within these models. The first direction of our research employs MoDNA, a motif-oriented pre-training framework specifically designed for DNA language models. By leveraging …

Uncertainty Quantification, Propagation & Conjunction Assessment In Orbital Mechanics Using Generalized Polynomial Chaos Expansion & 2-Dimensional Conjunction Plane Analysis Techniques, Monalisa Karim

Mechanical and Aerospace Engineering Theses

Uncertainties, that are inherent to dynamic models, can be associated with state initial conditions, force modelling errors, navigation and actuation errors. In system modelling stochastic differential equations are used to represent dynamic phenomena with uncertainties, for which the solutions are probability density functions of quantities of interest characterizing the realization of the stochastic processes. In Polynomial Chaos Expansion (PCE) propagation, these solutions are represented as weighted sums of multivariate spectral polynomials that are functions of the input random variables. Generalized polynomial chaos expansion (gPC) is an extension to the original homogenous PCE which projects the random solution onto a basis …

Reliability-Based Performance Evaluation Of Slurry Wall For Leakage Control At Chakaria Landfill, Bangladesh, Shishir Bhandari

Civil Engineering Theses

Landfill leachate threatens groundwater quality in low-lying coastal Bangladesh, where a shallow water table and a discontinuous natural clay barrier heighten contamination risk beneath municipal solid waste sites. At the Chakaria Landfill in Cox's Bazar District, a cement-bentonite slurry wall was proposed as a vertical cutoff to control seepage, but its reliability under the site's high-groundwater condition had not previously been evaluated in probabilistic terms.

This study evaluated the wall's performance using a two-dimensional SEEP/W finite-element seepage model, a validated response surface (RSM) equation relating seepage rate to wall permeability, thickness, depth, and a Hasofer-Lind first-order reliability (FORM) analysis built …

Adaptive Machine Learning Framework For Microstructural Optimization And Mechanical Performance Prediction In Steels, Henry Adekola Haffner

Doctoral Dissertations

Evolution of microstructures, such as polygonal ferrite, acicular ferrite, bainite, and martensite, plays a pivotal role in determining the final microstructural and mechanical properties of steel products. Given the established inter-relationship between processing parameters, microstructure, properties, and performance, precise control of phase transformation is essential to achieve pre-determined properties. To understand transformation routes in different steel grades, time-temperature-transformation (TTT) and continuous-cooling-transformation (CCT) diagrams are necessary and can be described using the Johnson-Mehl-Avrami-Kolmogorov equation and Scheil’s additivity rule. This study presents a comprehensive computational framework for predicting and optimizing microstructure and mechanical properties in advanced high-strength steels (AHSS) using adaptive machine …

Enhancing The Performance Of Disk-Based Key-Value Stores: From Learned Index Acceleration To I/O-Efficient Hybrid Caching, Sujit Maharjan

Computer Science and Engineering Dissertations - Archive

The exponential growth of data in modern computing environments has rendered the efficient extraction of information from massive datasets a critical systemic requirement. Key-value (KV) storage systems serve as the backbone for these operations; however, their performance is consistently bottlenecked by two primary functional requirements: identifying the data's location and managing the physical cost of accessing the storage device. Data locations are typically identified via an index, while disk I/O is minimized through caching. This dissertation presents LearnedStore, TurboIndex, and ReadBooster, which break these performance bottlenecks by introducing architectural modifications to the index and cache. LearnedStore accelerates operations by adapting …

Adaptive Synchronization In Digital Twin–Enabled Iot Systems: A Unified Framework For Energy, Fidelity, And Latency Trade-Offs, Uzma Zehra

Computer Science and Engineering Theses

Digital twin technology has emerged as a foundational paradigm for enabling real-time monitoring, analysis, and control in Internet of Things (IoT) systems by maintaining virtual representations of physical processes. Its effectiveness, however, critically depends on timely and accurate synchronization between distributed sensing devices and their corresponding digital counterparts. Frequent synchronization improves reconstruction fidelity and system responsiveness but incurs significant communication energy consumption and network latency. In contrast, infrequent synchronization conserves communication resources but can lead to stale or inaccurate digital twin states, particularly in environments with rapidly changing dynamics. These opposing effects give rise to a fundamental trade-off among energy …

Performance Evaluation Of Modified Moisture Barrier For Subgrade Stabilization Of Pavements On Expansive Soils, Md Tamim Shahriar

Civil Engineering Theses

Expansive soils inflict an estimated nine to fifteen billion dollars in annual damage to infrastructure across the United States, surpassing the combined losses from earthquakes, floods, hurricanes, and tornadoes (Nelson and Miller, 1997; Jones and Jefferson, 2012). In Texas, eighteen of twenty-five TxDOT districts contend with pavement failure rooted in moisture-driven volume change of subgrade clay, consuming roughly twenty-five percent of the agency's annual budget for maintenance and repair (Sebesta, 2002; Wanyan et al., 2010). Conventional remediation approaches, including soil replacement, chemical stabilization with lime or cement, and prewetting, are either prohibitively expensive, unsuitable for high-sulfate soils, or confined to …

Array Signal Processing And Machine Learning In 5g/6g Networks, Roopesh Kumar Polaganga

Electrical Engineering Dissertations - Archive

This dissertation investigates advanced methodologies in Array Signal Processing (ASP) and Machine Learning (ML) to enhance the performance, efficiency, and intelligence of next-generation wireless networks, with a primary focus on 5G and emerging 6G systems. As wireless networks face rapid traffic growth, increasingly heterogeneous service requirements, and more complex propagation environments, conventional design and optimization approaches become insufficient to meet evolving demands in reliability, capacity, spectral efficiency, and energy efficiency. On the network intelligence side, this work develops data-driven frameworks for causal discovery, scheduler enhancement, session-duration prediction, and Radio Resource Control (RRC) state optimization using real-world telecommunication network data. On …

Passive Communication Across Diverse Swarm Formations And Scales Utilizing Wake Signatures For Messaging And Object Inference, Bryan Varela

Open Access Master's Theses

Passive wake signatures in fluid flows can support perception and low-rate communication in swarms. In cluttered or contested underwater environments, conventional acoustic, radio, and optical links can be power-hungry, intermittent, or undesirable when low observability is required. Wake-mediated cues offer a local, directional channel that does not require line of sight because each agent naturally sheds coherent vortices that persist downstream and can be sampled by followers with only a small number of probes.

This study evaluates whether sparse downstream probes are sufficient to infer agent attributes and decode simple messages from wakes generated by established source shapes. Computational fluid …

The Effect Of Aluminum Substrate Surface Topography And Surface Energy On The Peel Strength Of Polyurethane Coatings, Christopher Ryan Grivers

Open Access Master's Theses

CUI information not included.

Peel Strength Of Polyurethane Coated Marine Metals In Air And In Underwater Environments, Maximillian Hill

Open Access Master's Theses

This study aims to characterize the hydrostatic peel strength of a hyperplastic material on three distinct and widely used marine-grade metals, using a primer. Aluminum 6061, HY-80 steel, and Nickel 400 (commonly known as Monel) are among the more popular metals used in the marine industry due to their unique material properties. To better understand the relationship of these materials and how we might quantify them, a peel test is performed at varying curing temperatures.

Following the investigation into varying curing temperatures, several specific marine environments will be considered. Submersible marine vehicles are designed to operate in a range of …

An Investigation Of Quiet Bunks For Improved Rest On Marine Vessels, Jacob Milman

Open Access Master's Theses

Those who spend an extended period of time living in a marine setting (e.g. living and working on a research/commercial vessel) are subject to a variety of annoying/disturbing noises during periods of sleep. Numerous past studies (Kim et al., 2024; Sunde et al., 2016; Li et al., 2024) have linked noise exposure levels and poor sleep to health and safety risks, both in personal and professional settings. Thus, it is necessary to take a closer look at the typical levels of noise exposure which mariners aboard a research vessel are subjected to, as well as any factors relating to personal …

Ensemble Dependence Of Mechanical Relaxation In Molecular Dynamics Simulation, Mason E. Hyde

Open Access Master's Theses

This thesis investigates whether the selection of thermodynamic ensemble introduces quantifiable differences in the stress relaxation modulus G(t), storage modulus G”(w), loss modulus G”(w), and phase angle d(w) computed from equilibrium molecular dynamics simulations of the AAA-1 asphalt model. A 72-molecule, 12-component representation of AAA-1 bitumen was simulated under three ensembles (NPT, NVT, and NVE) at three temperatures (400.15 K, 443.15 K, and 533.15 K) with three independent replications at each condition, yielding 27 total simulations. Stress autocorrelation functions were computed from each production trajectory and Fourier-transformed to obtain frequency-dependent rheological properties.

The computed properties …

Noninvasive Optical Assessment Of Tissue Hemodynamics In Preterm Infants And Mastectomy Skin Flaps, Samaneh Rabienia Haratbar

Theses and Dissertations--Biomedical Engineering

Adequate tissue blood flow and oxygenation are essential for maintaining cellular viability and normal organ function. Disruptions in microvascular perfusion and oxygen delivery contribute to ischemia- and hypoxia-related diseases, including stroke, cancer, retinopathy of prematurity (ROP), and mastectomy skin flap necrosis. Reliable, noninvasive approaches for assessing tissue hemodynamics are therefore critical for improving diagnosis and therapeutic decision-making, particularly in settings where conventional methods are limited. This dissertation investigates the clinical and physiological importance of measuring tissue blood flow and oxygenation across neonatal and surgical applications using both clinical monitoring and advanced optical imaging techniques. In the first study, high-speed pulse …

Evaluating Training Effectiveness And Learning Transfer In The Kentucky Transportation Cabinet Safety Academy, Amanda L. Casolare

Theses and Dissertations--Civil Engineering

Effective evaluation of safety training is crucial to ensure that learning translates into safe work practices, particularly in high-risk public sector environments. The Kentucky Transportation Cabinet (KYTC) is developing a Safety Academy to enhance hazard recognition, risk management, and safety leadership within the organization. However, the Safety Academy has not yet been implemented, and formal evaluation methods for training have not been established. This study aimed to examine evidence-based training evaluation techniques and develop recommendations for evaluating the KYTC Safety Academy prior to program implementation.

This study employed an applied pre-implementation research design grounded in a comprehensive review of safety …

Mental Health And Help-Seeking In Engineering Education: Beliefs, Norms, And Intervention Pathways For Undergraduate Students, Matthew D. Whitwer

Theses and Dissertations--Chemical and Materials Engineering

Engineering education is at a critical juncture where supporting student mental health is essential for fostering persistence, equity, and the development of a resilient and innovative workforce. While engineering students experience high levels of distress and low rates of mental health treatment seeking (known as a mental health treatment gap), there is a gap in knowledge around how this compares to that of students in other fields of study. Further, while efforts have been made to improve the mental health treatment gap in engineering, they are limited by a lack of actionable, theory-based targets. Therefore, this dissertation aims to characterize …

A Specification-Driven Framework For Self-Supervised Learning In Specialized Vision Domains, Mahmut S. Gokmen

Theses and Dissertations--Computer Science

Self-supervised learning (SSL) has emerged as a principled approach to visual representation learning that derives supervisory signal directly from unlabeled data, enabling foundation models to be trained at scale without manual annotation. Deployments in medical imaging and biometric recognition have demonstrated the potential of this paradigm, yet the assumptions that make SSL effective on natural image benchmarks fail systematically in specialized domains. Generic SSL pipelines encode a tacit assumption that the most informative correspondence is spatial proximity within a single acquisition. In specialized domains this assumption breaks at the level of the data-generating process: the signal that carries domain-specific information …

Linking S‑Pillar Empirical Criteria With Boundary And Finite Element Models For Underground Stone Pillar Analysis, Benjamin Diddle

Theses and Dissertations--Mining Engineering

The objective of this thesis is to strengthen the relationship between empirically based stone pillar design methods and two numerical modeling techniques by calibrating boundary element and finite element models to the S‑Pillar empirical criteria and observed pillar behavior in underground stone mines. The first component of the research investigates the displacement‑discontinuity boundary element method implemented in LaModel, quantifying the influence of the lamination thickness and element size on stone pillar safety factor predictions. Results showed that optimal thickness depends on overburden modulus, while larger element sizes introduce significant SF differences from S-Pillar values once the grid size exceeds 5 …

Validation Of Final And Dynamic Subsidence Prediction Models Using The Influence Function Method, Carlos M. Hernandez Garcia

Theses and Dissertations--Mining Engineering

This study evaluates the Surface Deformation Prediction System (SDPS Version 7) for predicting final and dynamic subsidence in longwall mining. Using the influence function method, SDPS 7 was calibrated using data from the Quarto 7 Mine (Ohio, USA) and two panels in Anhui Province, China, to test the reliability of the method under varying geological and operational conditions, particularly low advance rates.

For the Quarto 7 Mine, monument line C provided the optimal set of subsidence parameters: SSF of 78%, tanβ of 2.97, edge‑effect offset of 160 ft, with an RMSE of 0.108 ft. These values aligned with estimates obtained …

Evaluation Of The Proclivity For Recovering Rare Earth Elements Via Heap Leaching Of Coal And Coal Byproducts, Dylan Connell

Theses and Dissertations--Mining Engineering

Rare earth elements (REEs) - 17 elements classified as light (LREE) or heavy (HREE) - underpin modern technology. This thesis presents the development, design, and testing of a heap leach pad (HLP) to extract REEs from Western KY No.13 seam coal refuse. Testing included resource estimation, column and heap leaching, and an economic feasibility study. Drillhole analyses identified average REE concentrations in two refuse piles of 286 ppm and 290 ppm. The resource base totaled approximately 7,085 metric tons of REOs. The HLP, constructed with 2,000 metric tons of coal refuse material, was tested continuously over 308 days. Fresh lixiviant …

Field-Assisted Post-Processing Of Cold-Sprayed Pure Copper, Alan Hensley

Theses and Dissertations--Mechanical and Aerospace Engineering

The properties of materials processed through cold spray, and many other AM processes, are non-uniform and unpredictable. In most cases, post-processing is required to achieve desired properties and better uniformity. In cold spray, the typical method is an annealing heat treatment (AHT), which can improve bond strength, reduce porosity, and restore ductility, among other effects. AHT alone, however, is unable to completely remedy any of the unfavorable properties. In addition, long treatments at high temperatures are often needed for satisfactory results. This increases energy consumption and extends production times for products made by the process. For these reasons, numerous investigations …

Multiphysics Transport In Porous Thermal Protection Systems: Experimental Characterization Of Gas Permeability And Radiative Properties, Yejajul Hakim

Theses and Dissertations--Mechanical and Aerospace Engineering

Porous thermal protection systems (TPS) used in hypersonic vehicles exhibit coupled gas and radiative transport across multiple regimes and length scales. Accurate performance prediction requires reliable characterization of permeability, slip-flow behavior, and radiative transport properties, particularly for low-permeability and charred materials where existing data are limited. This dissertation presents experimental methods for characterizing multiphysics transport in porous TPS materials. A modular flow system was developed to measure permeability and slip behavior in both virgin and charred materials under relevant environments. A transient pressure decay method enables accurate permeability estimation in low-permeability regimes and provides insight into effective pore structure. Results …

Reciprocity-Based Transfer Function Techniques For Acoustic Source Reconstruction, Spring Isolator Characterization And Structural Damping Assessment, David Pum Thian Lal Paite Neihguk

Theses and Dissertations--Mechanical and Aerospace Engineering

Reciprocity implies that a system responds identically when the source and receiver positions are interchanged. This dissertation applies this principle to address three practical challenges in noise and vibration characterization, where conventional approaches are limited by inaccessible interfaces, constrained excitation conditions, or metrics that do not fully capture vibroacoustic behavior.

The first study develops and validates an inverse method to characterize ducted acoustic sources using acoustic free velocity. Acoustic reciprocity is applied to simplify transfer function measurements. The method is extended to large cross-section ducts, where the source is reconstructed as a collection of point sources along a plane. Validation …

Process-Guided Learning Via Data-Driven Modeling And Controller Synthesis, Benton Clark

Theses and Dissertations--Mechanical and Aerospace Engineering

This work introduces process-guided learning, a framework in which process characteristics and learning algorithms are combined in the modeling process of engineering applications with the aim of uniting traditional and data-driven modeling and control techniques. Traditional engineering methods using simplified analytic models fail to capture the increasing complexities of engineering problems with sufficient accuracy to achieve modern requirements. More advanced modeling and control techniques using high-fidelity models often produce a computational burden that is infeasible for real-time solutions. Data-driven modeling offers a simple and flexible algorithm for producing real-time capable, high-fidelity models, but naive implementations lack the physical constraints of …

From Floodplain To Floodplain: Analyzing Stream And Riparian Restoration Methodologies And Impacts, Noah P. Lane

Theses and Dissertations--Biosystems and Agricultural Engineering

Stream restoration is a relatively new scientific field. Currently, there is not a definitive methodology for performing restorations that all professionals in industry and academia can agree upon. This has allowed for multiple ideologies to be developed and altered that vary by geographic location and the professional using them. In addition to the methodologies used, the publicly available design guidance published by state government organizations also varies by regulatory authority, method of analysis, ecoregion, and restoration objectives. In some cases, design guidance is replicated from a different geographical area and may not satisfy local needs or existing site conditions. Since …

Constrained Dynamics Of Rapid Orbit Motion Emulator (Rome) Using Udwadia-Kalaba Approach, Keanu Brayman

Honors Undergraduate Theses

The Rapid Orbit Motion Emulator (ROME) is designed to be a hardware-in-the-loop (HIL) testbed for orbital control algorithms. It consists of a four-wheeled ground vehicle and a six-degree-of-freedom robotic manipulator. This work investigates the use of optimal control to execute orbital trajectories on ROME using the Udwadia-Kalaba (UK) formulation to model the system dynamics. The UK formulation is a novel method to derive equations of motion for constrained systems. Unlike traditional approaches, the UK approach can be applied directly to any constrained dynamical system. This project utilizes the UK approach to derive dynamics with trajectory following constraints for the ROME …

Structural And Magnetic Characterization Of A Magnetite Nanoparticle-Based Aggregation Assay And Its Application To In Vitro Cytokine Monitoring, Gabrielle Rose Moss

Dartmouth College Ph.D Dissertations

Magnetic particle spectroscopy (MPS) based aggregation assays rely on target induced changes in functionalized magnetic nanoparticle (fMNP) hydrodynamic diameter and/or changes in fMNP aggregation level to enable target detection. fMNP target binding can be modeled via Brownian and Néel relaxation. We are engineering an MPS-based aggregation assay to sense tumor necrosis factor (TNF)-⍺ in a 3D melanoma tissue culture to aid in the development of immunotherapies for cancer treatment. TNF-⍺ is an inflammatory cytokine, whose production can be linked to cell death.

The first part of this thesis investigates the effects of ligand density, off-target proteins, and salts on fMNP …