Digital Commons Network^™

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 …

Lidar-Based Point-Cloud Human Modeling: Pose Estimation, Body-Parts Segmentation, 6g Localization, And Applications, Omar Rinchi

Doctoral Dissertations

"The human body represents a rich source of physiological and behavioral information, where precise analysis of anatomy, body parts, 3D pose, and motion enables cross-disciplinary precision applications. This dissertation formulates this challenge as a human modeling problem, where proposed algorithms convert the human body into a three-dimensional digital twin capturing anatomical structure and pose. These representations are further analyzed using additional algorithms to enable precision applications. To realize this vision, LiDAR sensing is adopted due to its privacy-preserving nature, robustness to lighting conditions, color-blind sensing characteristics, and decreasing cost.

Human modeling using LiDAR is challenging due to sparse, irregular, and …

Quantifying, Forecasting, And Mitigating Construction Labor And Material Challenges In A Dynamic Global Economy Using Econometrics And Deep Learning, Ahmed Gamal Elsayed Mohamed Shiha

Doctoral Dissertations

"The construction industry contributes to the global economy, yet its cost management practices remain constrained by labor shortages and material price volatility. These challenges are intensified by economic disruptions, geopolitical tensions, and trade policy shifts. Despite a growing body of literature, five knowledge gaps remain unaddressed: (1) the absence of dynamic, and localized measures of construction labor shortages; (2) limited empirical investigation of macroeconomic leading indicators of labor shortages; (3) underutilization of deep learning (DL) algorithms in forecasting local construction labor earnings; (4) the limited treatment of structural breaks in existing construction material price forecasting models; and (5) the lack …

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 …

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 …

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 …

Unified Attack Modeling And Mitigation Framework For Multiple Physical Attacks In Sensor Networks For Advanced Manufacturing, Mohammad Mezanur Rahman Monjur

Doctoral Dissertations

The advanced manufacturing industry (AMI) faces unique challenges in security assurance. Security threats in AMI can originate from both software and hardware. Over the past decade, software security has been addressed extensively, but hardware security has not received enough attention. This work focuses on the security vulnerabilities of typical electronic devices deployed to AMI. Three attack models are proposed to characterize sensing nodes, local processing edge devices, and wired/wireless communication interfaces. Moreover, practical security attacks on hardware are demonstrated to inspire the development of feasible countermeasures against common physical attacks. To explore effective attack mitigation methods, we examine two attack …

The Garden Of The Machine: Simulated Wildness And Digital Domestication In American Literature 1970-2020, Cameron Netland

Doctoral Dissertations

Studying American literature produced during the Information Age, from 1970 to 2020, reveals an evolution of wild human resistance to the increasing powers of digital technology. These increasing powers include capturing attention, fostering dependence, and training behavior through a process I call digital domestication. Digital domestication distances people from wildness, and as William Cronon writes in “The Trouble with Wilderness”, “Learning to honor the wild—learning to remember and acknowledge the autonomy of the other—means striving for critical self-consciousness in all of our actions.” (20). Through this framework of wildness, one reads characters in fictional narratives resisting non-coercive new technologies as …

Reframing Coral Reef Monitoring With Machine Learning And Remote Sensing: Detection, Classification, And Change, Gabrielle Ann Trudeau

Doctoral Dissertations

Coral reefs are vital ecosystems facing rapid decline from climate-driven stressors, yet existing monitoring approaches lack the spatial coverage and temporal resolution needed to capture ecosystem dynamics at meaningful scales. This thesis develops a scalable, integrated remote sensing framework by combining ICESat-2 LiDAR, multispectral imagery, and machine learning to move beyond static habitat maps toward quantitative, multi-factor characterization of reef structure and change. First, machine learning models were applied to ICESat-2-derived rugosity, slope, and bathymetric metrics to detect and delineate coral reef habitats at large scales. Next, a novel nonlinear spectral unmixing approach integrating Planet imagery and ICESat-2 terrain metrics …

Ai-Enabled Urban Decision-Making: From Infrastructure To Policy Implementation, Amir Hosein Taherkhani

Doctoral Dissertations

Urban infrastructure systems face unprecedented compound threats from aging physical stock, climate-driven hazard escalation, and large-scale systemic shocks, yet the analytical tools available to decision-makers remain inadequate in both empirical scope and equity orientation. This dissertation advances urban resilience science along two complementary empirical frontiers.The first investigation develops a deep reinforcement learning framework for socially equitable, flood-aware bridge portfolio maintenance optimization. Using Proximal Policy Optimization, a portfolio of 19 flood-vulnerable bridges in Suffolk County, Massachusetts is optimized over a multi-year planning horizon integrating HAZUS-based flood hazard simulation across four return-period scenarios (10, 50, 100, and 500 years), HEC-18 hydraulic scour …

The Long And Short Of It: Exploring The Essential Dynamics Of Select Geophysical Flows, Adhithiya Sivakumar

Doctoral Dissertations

Geophysical flows are central to important climatological processes, yet their strong turbulence and additional complexities -- density stratification, wave-current interaction, and phase change -- make analytical prediction and direct numerical simulation infeasible in many regimes. This dissertation adopts a reductionist approach in which simplified representations -- often inspired by observed scale disparities -- are utilized to isolate and investigate the organizing mechanisms of these complex flows. Within this framework, three distinct but thematically connected problems are studied.

We first study Langmuir turbulence in the open ocean, in which surface gravity waves interact with wind-driven currents to organize the mixed layer …

Tighter Bidirectional Heuristic Search And Lazy Optimal Sampling-Based Motion Planning, Yi Wang

Doctoral Dissertations

Heuristic search is a core area of artificial intelligence (AI) that explores state spaces using heuristic estimates to support planning and decision-making. In robotics, motion planning is a fundamental problem of computing feasible robot motion under constraints. A central challenge shared by both domains is how to substantially reduce unnecessary computation while preserving strong theoretical guarantees, such as completeness and optimality.

In response to this challenge, each domain has developed its own distinct methodological paradigms. In heuristic search, approaches broadly fall into unidirectional and bidirectional paradigms. Unidirectional heuristic search (Uni-HS) has a mature ecosystem, supported by decades of theory and …

From Surfaces To Scaffolds: Tuning Hydrogel Microenvironments To Control Cell-Material Interaction, Tran Truong

Doctoral Dissertations

The last 40 years of in vitro cell and tissue biology have relied heavily on tissue culture plastic (TCPS), which offers high transparency and a simple, user-friendly method for growing adherent cells. Unfortunately, TCPS has limitations, such as its rigidity, which may alter cell shape, disrupt cell signaling, and ultimately affect cell fate. The poor control over the adsorption of proteins to TCPS and the fact that surface chemistry is fixed on this material are only two examples of the limitations that motivate the development of hydrogel-based culturing platforms, during which the mechanical properties, charge, hydrophobicity, and ligand presentation can …

Entrainment And Surfacing Dynamics Of Submerged, Buoyant Turbulent Jets, Zeeshan Saeed

Doctoral Dissertations

Turbulent entrainment (TE) in buoyant jets plays a key role in dispersing environmental contaminants, carrying significant socio-economic implications. For example, the transport of heat and solutes through submarine volcanoes and the discharge of subglacial meltwater crucially affect the marine ecosphere. This, in turn, impacts coastal communities, the supply chains they support, and the broader socio-economic landscape. Therefore, advancing our understanding of how submerged buoyant jets mix and developing remote sensing tools to help monitor their changing status is crucial for devising strategies to mitigate marine-related challenges quickly, economically, and effectively. Therefore, this dissertation has three primary objectives: (I) examine the …

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 …

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 …

Advancing Management Strategies For Airport Infrastructure Development: A Holistic Project Delivery And Contractual Perspective, Ramy Ahmed Anwar Ahmed Khalef

Doctoral Dissertations

The airport sector plays a vital role in the US infrastructure. Neglecting the maintenance and improvement of such critical domain poses serious repercussions. Current initiatives within the aviation sector have fallen short in providing substantial quantitative or qualitative support for comprehensive project and risk management processes. This research fills this knowledge gap. The associated objectives include: (1) identifying a holistic set of Design-Build risk factors and providing associated research recommendations; (2) enhancing the understanding of Design-Build (DB) with respect to Design-Bid-Build (DBB) on key risks impacting schedule/cost performance in airport projects; (3) establishing a risk-based benchmarking framework to evaluate schedule/cost …

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 …

Geometric Effects Of Warfighters On Body Armor Fit And Protective Capabilities Against Shock Wave Energy, Melissa Lynn Sutter

Doctoral Dissertations

Body armor is a vital piece of protective equipment for warfighters to defend against threats, necessitating continued development to improve comfort, weight, and protection. However, female warfighters often wear unisex body armor, designed primarily for the male torso. Current research has evaluated the short- and long-term detriments of female warfighters wearing these armors, focusing on comfort and performance. However, these studies do not comprehensively consider how a non-form-fitting armor compromises warfighter safety from battlefield threats. This research examines the geometric effects of female warfighters on armor protection level when defending against shock threats by evaluating the energy distribution on a …

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 …

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 …

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 …

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 …

Architecting A Complex Adaptive System Model For Selecting Policies To Reduce Kidney Discard, Lirim Ashiku

Doctoral Dissertations

"The kidney allocation system is a complex, evolving system involving multiple heterogeneous agents. Each agent exhibits emergent behavior that may not fully align with the complex system goals. Therefore, there is a need for a transdisciplinary systems approach to visualize the interdependency among agents and understand the dominant patterns that shape the kidney allocation system.

First, this research presented an incremental hierarchical system engineering approach in identifying the agents’ needs and behaviors toward the complex systems’ goal of maximizing deceased donor kidney utilization and reducing kidney discard. The hierarchical systems approach linked with model-based system engineering aided in eliciting agents’ …

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 …

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 …

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 …

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 …