Digital Commons Network^™

Emotional Complexity In Context: Within-Person Variability In Emotional Granularity, Emotion Covariation, And Emodiversity, Kristen Diann Petagna

Doctoral Dissertations

Key features of emotional complexity include emotional granularity, the ability to identify feelings with precision; emodiversity, the number and evenness of different emotions experienced; and emotion covariation, the tendency to experience positive and negative emotions independently. Prior work has largely treated these features as trait-like. This dissertation examines whether these features are dynamic by investigating how they vary within individuals over time and across contexts. In Chapter 2, participants (N =123) reported their emotions multiple times a day for 6 weeks and completed biweekly assessments of mental health symptoms. Emotional granularity and covariation increased over time, whereas emodiversity decreased, and …

Harnessing Coherent-Wave Control For Sensing Applications In Scattering Media, Pablo Xavier Jara Palacios

Doctoral Dissertations

"Diffuse electromagnetic waves are widely used for non-invasive sensing and imaging in complex scattering media such as biological tissues. A fundamental limitation of such techniques is the scarcity of detected photons: as the source-detector separation increases to access deeper regions of the medium, the signal strength decays rapidly, leading to poor signal-to-noise ratio and limited sensitivity. This dissertation addresses this challenge through a combination of theory and computation.

We show that coherent control of the incident optical wavefront can compensate for the scarcity of detected photons that limits conventional diffuse optical imaging, typically performed in the near-infrared spectral region. By …

Analytical And Empirical Data-Driven Risk-Governance Design Across The Different Phases: Creating Informed Policy Adjustments For The Transportation Project Lifecycle, Mariam A. Elazhary

Doctoral Dissertations

"Transportation infrastructure is a critical foundation for economic productivity, yet agencies still face challenges in translating the expanding transportation datasets into defensible, phase-specific risk-governance tools. This dissertation addresses this gap by developing analytical and empirical, data-driven approaches to support risk governance across the transportation project lifecycle. Module 1 uses a panel model with bid-letting data to examine how out-of-state contractor participation affects pre-award competition and to derive entry-governance rules. Module 2 analyzes nonfatal injury data through iterative multiple linear regression and fatality data through association-rule change mining to identify multi-factor safety-risk configurations and develop adaptive safety-governance provisions. Module 3 develops …

Trust-Aware Algorithms For Stackelberg Ground Vehicle Routing, Doris Evelyn Meredith Brown

Doctoral Dissertations

Despite decades of research focused on reducing ground vehicle traffic congestion, urban traffic networks worldwide continue to experience traffic flows that lead to increased network travel times, largely resulting from the routing decisions of individual vehicles. To address this challenge, this work leverages a Stackelberg game framework to model the interaction between a vehicle agent and a routing authority as a leader–follower game, in which the routing authority proposes routing interventions to which the agent responds. This research contributes to existing traffic mitigation literature by exploring the role of trust in route decision-making and providing trust-aware algorithms that influence vehicle …

Manufacturing And Performance Evaluation Of Carbon/Epoxy Laminated Composites Cured Using Single- And Six-Magnetron Microwave Applications, Nayan Pundhir

Doctoral Dissertations

Microwave curing is fast, energy-efficient, and a viable alternative to conventional thermal curing processes. It has been widely adopted for processing carbon fiber-reinforced polymer (CFRP) composites because the high electrical conductivity of carbon fibers enables strong microwave coupling, leading to rapid volumetric heating and reduced energy consumption. The aim of this study is to investigate the use of microwave curing for manufacturing CFRP composites. IM7/Cycom 5320-1 unidirectional prepreg was utilized to fabricate laminated composites in two thickness ranges: 16-layer laminates (2.5 mm thickness) and 64-layer laminates (9.2 mm thickness). Two lay-up configurations were examined: symmetric cross-ply and quasi-isotropic. Different curing …

Probability Of Detection For Corrosion-Induced Mass Loss And Yield Strain In Metal Structures Using Fe-C Coated Long Period Fiber Gratings Sensors And Electroresistive Strain Gauges, Ying Zhuo

Doctoral Dissertations

"Graphene-based, Fe-C coated long-period fiber grating (LPFG) sensors individually reveal a causal relation between LPFG wavelength change and Fe-C mass loss. Their correlation parameters vary significantly between the sensors mainly because hydrophobic multilayer graphene and graphene oxide make sensor fabrication inconsistent. This study explores MXene-based, Fe-C coated LPFG sensors due to MXene’s inherent hydrophilic property in the presence of surface functional groups such as hydroxyl and oxygen and the probability of detection (POD) for mass loss from Fe-C coated LPFG sensors when deployed at a fixed location. A novel fabrication process incorporating Piranha solution pretreatment is proposed to ensure uniform …

Innovative Methods In Intact Rock Deformation Detection, Ali Abdullah M Alzahrani

Doctoral Dissertations

"An accurate assessment of intact rock deformation is imperative in engineering activities carried out either in or above rock masses. However, instruments used for post-peak deformation are easily debonded and cannot record the whole process of post-peak deformation required in the failure modeling of rocks. This dissertation focuses on the investigation of the performance of two non-contact measuring systems (Laser Displacement Sensor (LDS) and Inductive Proximity Sensor (IPS)) compared to the contact type instrument (conventional Strain Gauge System (SGS)) in monitoring intact rock deformations. Subsequently, an IPS was installed in a high-pressure triaxial testing system before investigating its performance in …

Temperature-Dependent Dielectric Function Of Solids From Coupled Oscillators With Radiation Reaction: Application To Atom–Surface Interactions, Tuhin Kanti Das

Doctoral Dissertations

In this dissertation, we propose a uniform functional form of the dielectric function of solids that is applicable over a wide range of frequencies. We apply our model to describe the dielectric function of two technologically important materials: silicon and calcium fluoride. The temperature dependence of their dielectric functions is also described using simple analytic forms. We found that a generalized Sellmeier-type model with complex denominators (“damped oscillators”) does not lead to a satisfactory fit of experimental data for the dielectric function. In contrast, our model, which is analytically only slightly more involved (“complex oscillator strengths”, complex numerators), allows us …

Exploring New Poly-Anion Based Materials For Lithium – Ion Battery Cathodes, Sutapa Bhattacharya

Doctoral Dissertations

The escalating global demand for sustainable energy storage solutions has driven intensive research into novel electrode materials. Polyanion-based cathode materials have emerged as promising candidates due to their structural stability, safety, and voltage tunability enabled by the inductive effect of polyanionic groups. This research explores the synthesis, crystal structure, and electrochemical performance of new polyanion-based cathode materials featuring vanadium, molybdenum, and iron within phosphate and selenite frameworks.

Novel selenite-based materials, such as LiFe(SeO₃)₂ and Li₀.₂₅V₂O₃(SeO₃)₂, were synthesized and characterized, revealing stable electrochemical cycling associated with Fe2+/Fe3+ and V⁴⁺/V⁵⁺ transitions. Additionally, a systematic investigation was conducted on molybdenum phosphate compounds, including …

Theoretical Study Of Long-Range Molecular Interactions, Adrian Luis Batista-Planas

Doctoral Dissertations

Describing intermolecular forces is fundamental to modeling and predicting the behavior of molecular systems. In particular, long-range molecular interactions—with electrostatic, induction, and dispersion as main components—play a critical role, especially for low-temperature and low-density regimes. Long-range interactions are often described through perturbation theory, representing the electronic charge distribution via multipolar series of the moments and polarizability tensors corresponding to each molecule. However, while the theory is well-established, obtaining the resulting analytical expressions (and their practical implementation) constitutes a highly complex and system-dependent task. To address this challenge, we developed Long-Range-Fit (LRF), an interactive and user-friendly software package designed to automate …

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 …

Security And Energy-Efficiency In Federated Learning, Priyesh Ranjan

Doctoral Dissertations

Federated Learning (FL), which facilitates collaborative model training and protects users' privacy, has drawn great interest from the research community. With FL, the participants train their models on local data and submit the corresponding updates for aggregation to a server. While concealing the participants' identities, FL may attract adversaries aiming to hamper the underlying model. These adversaries aim to submit malicious weight updates that corrupt the performance of the server model. Further, these models when communicated to the participating clients extend the behavior which is undesirable. Additionally, FL suffers from increased energy consumption at the edge device level due to …

Zirconium Carbide Based Materials For Extreme Aerospace Environments, Nathaniel Hyman Blatt

Doctoral Dissertations

This research focuses on the processing and properties of zirconium carbide-based materials to promote their use in extreme environment aerospace applications, including nuclear thermal propulsion and hyper sonics. Several carbide systems including ZrC, ZrC-Mo cermets, (Zr, Nb)C, and a high entropy carbide were developed. The ZrC-Mo cermet was studied extensively to understand the effect of starting carbide grain size on the final microstructure, composition, elastic moduli, hardness, fracture toughness, room and elevated temperature flexural strength, thermal diffusivity, electrical resistivity, thermal expansion coefficient, and thermal conductivity. It was shown that heat transport in the cermets was dominated by the ZrC phase …

Investigations In Hydrogen Ironmaking, Joseph William Govro

Doctoral Dissertations

The purpose of this research is to contribute to the Grid Interactive Steelmaking with Hydrogen (GISH) project. This research investigates the viability of both producing and melting Direct-Reduced Iron (DRI) utilizing hydrogen. Conventional CO reduced DRI will be referred to as “C-DRI” and DRI produced using hydrogen gas will be referred to as “H-DRI”.

An H-DRI pilot plant was constructed in Golden Colorado. The pilot plant was commissioned and successfully operated four campaigns. Process improvements were made throughout the campaigns and the process was optimized. In addition to running the pilot plant in a pure hydrogen condition, the pilot plant …

Strontium Titanate For Capacitor And Energy Storage Applications At Cryogenic Temperatures, Hung Trinh

Doctoral Dissertations

This study investigates the dielectric properties of single crystal and ceramic strontium titanate (SrTiO₃) for cryogenic capacitor applications from room temperature to 4 K. Permittivity (k) and loss tangent are dependent on temperature, frequency, mechanical stress, and applied DC electric field. Accordingly, the dielectric constant and loss tangent were measured at various frequencies and DC bias levels. Loss tangent data are also presented as equivalent series resistance (ESR). For single crystal SrTiO₃, an impurity level of ≈500 ppm barium resulted in an increase of the maximum permittivity to approximately 50,000 at 6 K. This relatively high …

Essays On Accelerated Failure Time Models For Recurrent Event Data, Emmanuel Masavo Djegou

Doctoral Dissertations

Recurrent event data arise in many fields such as medicine, reliability, insurance, and economics, where the same event may occur repeatedly for a subject. Accelerated Failure Time (AFT) models provide an intuitive framework for relating covariates to event times and offer a useful alternative to proportional hazards models, allowing direct prediction of event timing under right censoring. However, existing AFT extensions for recurrent events, such as accelerated gap time (AGT) models, often fail to account for interventions between events and may not capture complex temporal patterns.

In this work, we first propose a class of semiparametric AGT models incorporating an …

Machine Learning Based Automation Of Pcb Pdn Design And Optimization, Haran Manoharan

Doctoral Dissertations

The rapid increase in power density and stringent power-integrity requirements in modern System-on-Chip (SoC) platforms have made Power Delivery Network (PDN) design an increasingly complex, multi-stage challenge. Critical decisions must be made both during pre-layout planning, such as stackup configuration, power-plane geometry, and early decoupling capacitor (decap) budgeting, and during post-layout refinements. Traditional heuristic and evolutionary optimization techniques struggle with scalability, require extensive manual iteration, leading to long runtimes and limited adaptability across varying board configurations. To address these challenges, this work proposes a unified reinforcement-learning-driven framework for automated PDN synthesis and decap optimization that spans both pre-layout and post-layout …

Advancing Coal Rib Support Design Through The Integration Of Field Studies And Numerical Simulations, Alper Kirmaci

Doctoral Dissertations

Coal rib stability remains a major safety concern in U.S. underground coal mines, with rib failure-related injuries and fatalities still occurring. A key challenge is the lack of a standardized methodology for designing rib support systems that can address varying geological conditions. As a result, many mines rely on trial-and-error or traditional practices, leading to inconsistent designs. This research aims to develop a systematic methodology for rib support design to improve coal rib stability in U.S. mining operations.

The study consists of: i) field monitoring in active room-and-pillar coal mines, ii) in-situ pull-out tests on coal ribs, iii) numerical model …

Critical Parameters Controlling Oxide Scale Formation And Hydro-Descaling Efficiency During Steelmaking, Tochukwu Princewill Ojiako

Doctoral Dissertations

In modern steelmaking, cast slabs are exposed to high-temperature oxidizing environments during secondary cooling, reheating, and hot rolling, resulting in the formation of multilayer oxide scales on the steel surface. These scales interact with mold-flux residues originating from the casting process (CC). The morphology, chemistry, and adhesion of oxide scale strongly influence its removability during high-pressure hydraulic descaling and ultimately determine the surface quality of hot-rolled products. However, the mechanistic relationship between oxide scale evolution, scale-steel interfacial structure, and hydraulic descaling performance remains poorly understood.

This dissertation investigates oxide scale formation, modification, and removal in low-carbon thin-slab steels produced by …

Incremental Cluster Validity Indices And Their Role In Interpreting Lifelong Learning Systems, Niklas Max Melton

Doctoral Dissertations

Clustering and supervised learning are often treated as distinct paradigms, yet both rely on structure in feature space. This dissertation investigates the relationship between cluster validity indices (CVIs) and supervised learning in real-time and lifelong learning settings where data arrive incrementally and cannot be revisited. Across four studies, it develops methods for online cluster validation, uses supervised learning to improve their interpretability, and applies these ideas to evaluating performance degradation in continual learning.

The first study extends incremental cluster validity indices (iCVIs), enabling widely used validation metrics to operate in streaming environments. Experiments on synthetic and real-world datasets show systematic …

Fully Differential Studies On Dissociative Capture In P + D2 Collisions And On Ionization In P + He Collisions, Shruti Majumdar

Doctoral Dissertations

Advancing our understanding of few-body dynamics in simple atomic systems is a fundamental objective in atomic scattering research. The underlying problem is that the Schrödinger equation is not analytically solvable for more than two mutually interacting particles. This involves a comprehensive exploration of various channels, such as ionization, capture, and excitation. A common theoretical approach to describe ion-atom collisions is based on perturbation theory, where the scattering amplitude is expanded in powers of the interaction potential. Here, understanding the few-body problem means accurately describing the relative importance of the higher- vs the first order terms.

In the case of ionization, …

Milankovitch Paleoclimatic Signals In Upper Permian–Lower Triassic Fluvial-Lacustrine Records, Bogda Mountains, Greater Turpan-Junggar Intracontinental Rift Basin, Nw China, Wentao Zhang

Doctoral Dissertations

"The objective of this study is to understand whether Milankovitch climatic and/or tectonic processes influenced the sedimentation of the upper Permian–Lower Triassic fluvial-lacustrine cyclic deposits in Bogda Mountains, greater Turpan-Junggar intracontinental rift basin, Xinjiang Uygur Autonomous Region, NW China. This study carried out gamma analysis, gamma and astronomical tuning, and spectral analysis on the Wutonggou, Jiucaiyuan, and Shaofanggou low-order cycles of the South and Central Taodonggou, South and North Tarlong, Dalongkou, and Zhaobishan sections. Stable and positive gamma values support the assumption of facies-dependent sedimentation rates for non-marine facies. The sedimentation rates range from 0.04 to 2.43 m/kyr, and 0.21 …

Accelerating Circular Economy Transition For A Sustainable Built Environment: A Systems-Based Framework, Radwa Walid Yassin Eissa

Doctoral Dissertations

"The Circular Economy (CE) has gained momentum as a transformative framework for steering the construction value chain towards greater sustainability. However, this transition requires shifts in production and consumption patterns, adoption of circular business models, and the replacement of linear practices. Despite growing interest, CE adoption in construction faces persistent challenges, including sectoral fragmentation, lack of integrated governance frameworks, and limited coordination among stakeholders. This dissertation aims to accelerate the CE transition in the built environment through a multi-scale, interdisciplinary approach spanning five modules: (1) Module 1 develops a construction value chain-structured portfolio of CE strategies and assesses their implementation; …

Bond Graph And Extended Generalized Average Method With Applications In Cyber-Physical Systems And Power Electronics, Arnold Anthony Fernandes

Doctoral Dissertations

"This research examines two applications of control theory. The first application considers the bond graph (BG) modeling technique, which is used to develop the MATLAB structural analysis toolbox (MATSAT), an open-source toolbox for sensor placement and qualitative system analysis that considers the observability and fault-detection capabilities of multi-domain cyberphysical systems. The toolbox provides information on redundant sensors, guiding the system designer in cost and security trade-offs. The toolbox uses traditional BG causality assignment procedures. Additionally, MATSAT provides optimal causality assignment methods that perform significantly better at assigning causality to BGs with increased junctions, sources, and simple meshes, without encountering causality …

Integrating Stakeholder Priorities Into Resilience Planning And Investment Decision-Making, Victoria Jeaneen Kraemer

Doctoral Dissertations

"Resilience is a system’s ability to bounce back from a disruption. However, resilience needs may vary across different stakeholders. To better integrate stakeholder input into resilience planning and investment decision-making, existing frameworks were combined to develop the Integrated Stakeholder-Centered Resilience Framework. This broad framework is tailorable across contexts and stakeholder types. Research results demonstrate the use of this framework to evaluate the effects of disruptions and represent stakeholder preferences for investments. In the first study, participants were randomly assigned to power outage scenarios, which did not affect their criteria priorities. An exploratory factor analysis revealed two main priorities, (1) Absorption …

An Energy-Stable Mixed Cg-Dg Scheme For A Full Shliomis Phase Field Model Of Two-Phase Ferrofluid Flows, Mahdi Gharehbaygloo

Doctoral Dissertations

"Ferrofluids are magnetic nanoparticle suspensions whose motion couples surface tension, flow field, magnetostatics, and magnetization dynamics. This dissertation develops, analyzes, and validates an energy-stable finite element method for a two-phase ferrofluid model that couples the Cahn-Hilliard equations with the full Shliomis model of single-phase ferrofluids, retaining its damping torque term, magnetic torque term, and magnetic stress term.

The spatial discretization is a mixed continuous Galerkin (CG) and discontinuous Galerkin (DG) formulation. It uses continuous ��2 elements for the phase field, chemical potential, velocity, and magnetostatic potential, discontinuous ��2 elements for the magnetization, and discontinuous ��1 elements for the pressure. The …

Ai Ethics And Governance For Leaders In Higher Education: A Hermeneutic Phenomenology Of Faculty Early Adopters’ Sensemaking, Pedagogical Innovation, And Transformation, Freddie Seba

Doctoral Dissertations

Artificial Intelligence (AI), especially Generative AI (GenAI), is transforming how we work, learn, acquire, produce, and deliver knowledge, as higher education experiences existential pressures, including demographic changes that reduce enrollment and revenues, as well as shifting public and government perceptions of higher education's value.

This hermeneutic phenomenology dissertation study explores how faculty early adopters critically engage, innovate, and experiment with this nascent transformational technology in their pedagogies amid multilevel pressures: macro—market-driven (neoliberalism) logic, Big Tech, and demographic change; meso—institutional policy, broader faculty community, and pedagogical innovation; micro—widespread student adoption, pedagogical experimentation, and innovation.

This dissertation study centers on shifting AI …

Program Outcome Evaluation Of A Flexibly Structured Individual Outpatient Program For Severe Obsessive Compulsive Disorder In A Private Practice Setting, Jason R. David

Doctoral Dissertations

The current study is a quantitative program evaluation of the effectiveness private practice for treating obsessive compulsive disorder while incorporating multiple validated components to reduce common barriers of treatment access. There were three outcomes used to evaluate the first being the reduction in symptom severity across treatment, the second being the length of time in treatment before reduction can be seen, and the third being the rates completing treatment as agreed by therapist and participant. The current study was able to complete analysis for the first and third research question, and unable to answer the second. The first and primary …

The Effects Of Applying Self-Regulated Learning Prompts On Academic Achievement In A Public Middle-School Science Classroom, Andrew Barham

Doctoral Dissertations

Student success in science courses is a critical focus for K–12 educators, particularly during the transition period of middle-school, where students face increasing academic and social demands. Self-regulated learning (SRL) strategies have been shown to enhance academic outcomes by fostering independent learning and metacognitive awareness. However, research on the implementation and effectiveness of SRL interventions in middle school science classrooms, particularly within the constraints of public school settings, remains limited.

This study investigated the effects of an SRL intervention on the academic achievement of eighth-grade students during a six-week astronomy unit. Students from a public middle school in the San …

A Comprehensive Study Of Uncertainties In The Modeling Of Binary Neutron Star Outflows, Amelia Michele Henkel

Doctoral Dissertations

Binary neutron star (BNS) mergers have recently become a tool to study extreme gravity, nucleosynthesis, and the chemical composition of the Universe in a new way. In order to accurately identify electromagnetic signals of neutron star mergers, both in the future and retroactively, better constraints on their merger signatures are required. Specifically, BNS outflow properties (such as the mass and composition) are particularly insightful, as they provide a link between the intrinsic properties (such as the stellar masses and radii) and observables. In this thesis, I put forth multiple ways of classifying uncertainties associated with BNS mass outflow models. First, …