Physical Sciences and Mathematics Commons^™

Data-Assimilation-Enabled Fast Convergence Of The Uzawa Scheme For Navier-Stokes Equations With Large Reynolds Numbers, Jessica C. Franklin

All Theses

This work studies efficient techniques utilized to solve the Navier-Stokes equations that model incompressible Newtonian flow in the setting where partial solution data is available. First, we analyze the Picard iteration and Picard with continuous data assimilation applied and test convergence. Then, we analyze the Arrow-Hurwicz (AH) and Uzawa iterative procedures and test convergence. Finally, we apply continuous data assimilation to Uzawa, and analytical and numerical results show that CDA improves Uzawa convergence for the NSE, similar to CDA-Picard but it is much more efficient.

Influence Of Produced Water Runoff On Surface Water: A Statistical Analysis Of Water Quality In Petronilla Creek, Joshua Sierra

Water Resources Science and Technology Theses and Graduate Research Reports (Archived)

This case study research investigates the potential influence of produced water (PW), a byproduct of oil and gas (O&G) activities, on surface water quality. The study involved two sites along Petronila creek, located in Nueces County, with historical oil and gas presence. Data from nearby monitoring stations containing various water quality parameters typically associated with produced water, including total dissolved solids (TDS), chloride (Cl), sulfate (SO4), and specific conductance was used to perform a statistical analysis of spatial and temporal trends. Spatial comparisons were made between both sites and upstream, tributary, and downstream roles to test for variances in water …

Evaluating Nutrient Uptake Efficiency Of Texas Native Plants In Simulated Constructed Wetland Systems, Angelica Canizalez

Water Resources Science and Technology Theses and Graduate Research Reports (Archived)

Nutrient enrichment from wastewater effluent and runoff is a major driver of eutrophication in freshwater systems, increasing the need for effective and ecologically beneficial treatment strategies. Constructed wetlands (CWs) offer a nature-based solution for reducing nitrogen (N) and phosphorus (P) while simultaneously supporting habitat and biodiversity. However, most CW research has focused on traditional species such as cattails and bulrushes, with limited quantitative data on the performance of Texas native plants. This study evaluated the nutrient uptake potential and stress tolerance of two Texas native species—buttonbush (Cephalanthus occidentalis) and Maximilian sunflower (Helianthus maximiliani)—in simulated, recirculating wetland systems.

A Kinematic, Data-Parameterized Approach To Constrain Subducted Seafloor During The Emplacement Of Shatsky Rise, Alexzandrya Katrina Shotorban

OES Theses and Dissertations

This study investigates ridge spreading rates and plate boundary geometry in interactions between large igneous provinces and mid ocean ridges, and their role in the kinematics of Shatsky Rise, an undersea volcanic plateau in the western Pacific Ocean that is roughly the size of the state of California. Shatsky Rise formed at a ridge-ridge-ridge (RRR) triple junction (TJ) (Hilde et al., 1976; Sager et al., 1988), at the intersection of the Pacific-Izanagi, Pacific-Farallon, and Izanagi-Farallon ridges, beginning at approximately 147 Ma. Investigations into Shatsky Rise’s formation are limited by the fact that two-thirds of the seafloor data has subducted with …

Component Model Development Of Heat Exchangers, Expanders, And Control Valves For Autonomous Cryogenics Plant Cool-Down, William Harris Buhrig Iv

Mechanical & Aerospace Engineering Theses & Dissertations

The traditional method of cryogenic plant cool-down involves having continuous on-call staff to head into the office at any time to modify the existing multi-layered PID control systems if the on-call staff member detects a significant deviation from the cool-down plan. This thesis aims to outline an effective method for modeling the structure of systems with performance characteristics that deviate from design requirements and from ideal inlet-outlet correspondence, enabling the adjustment and modification of existing control structures across all Thomas Jefferson National Accelerator Facility (JLab) cryogenic refrigeration plants. Analytical Modeling and Gaussian Process Regression (GPR) are applied to model the …

Computational Expressions Of Void Reactions In Extended Chemical Reaction Network Models, Aiden J. Massie

Theses and Dissertations

Chemical Reaction Networks (CRNs) are a system of abstraction of real-world chemical dynamics. Each CRN system is defined as a pair of molecular species and reaction rules, which consume a set of reactant species and create a new set of product species. In this paper, we investigate the simple class of void reactions, which cannot create new species and are computationally weak with small-enough sizes in basic CRNs. Here, we study their computational expression in more powerful extended CRN models. Specifically, we consider the Step CRN model, in which new species are added into the system through a sequence of …

Interactive Effects Of Nutrient Loading And Hyposalinityon The Physiological Responses Of The Red Macroalga Gracilaria Tikvahiae, Donavuan Vincent Salazar

Theses and Dissertations

Coastal macroalgae face anthropogenic stressors such as nutrient enrichment from nitrogen fertilizers and reduced salinity linked to flooding. The physiological impacts of these combined stressors remain unclear. This study examined interactive effects of nitrogen loading and hyposalinity on Gracilaria tikvahiae through a 9‑day laboratory experiment. Samples experienced declining salinity (35–0 ppt) with nitrate or ammonia enrichment (120 µmol/L). Measurements included primary production, respiration, biomass, nitrate uptake, and chlorophyll‑a. Hyposalinity significantly reduced physiological performance, with gross primary production declining over 100%, chlorophyll‑a content 25–45% lower, biomass loss, and reduced nitrogen uptake. Nitrogen enrichment failed to mitigate the adverse impacts under hyposaline …

Modern Water And Sediment Transport Patterns In Alluvial Ridge Basins Of The Rio Grande Delta, South Texas, Usa, Waqid Nabi

Theses and Dissertations

Alluvial ridge (AR) basins are shallow, marine-influenced depressions within river deltas, yet their flow and sediment dynamics remain poorly understood. This study examines hydrodynamics and sediment transport patterns in the Bahia Grande Complex, which are AR basins of the Rio Grande Delta, using tilt current meters, water-level and turbidity loggers, and suspended and bed-sediment sampling. The AR basins function as wind-dominated, microtidal environments, where pre-existing basin geometry and hydrodynamic forcings control water flow and sediment distribution patterns. Seasonal wind patterns and storms modulate water levels and flow connectivity. Substrate patterns reflect frequent resuspension in the shallow northern basin, maintaining coarse …

Design And Evaluation Of Gamified Kahoot Modules For Improving Engagement And Conceptual Understanding Of Introductory Physics Students, Yaritza Villarreal

Theses and Dissertations

This study investigates the effectiveness of gamified learning modules in enhancing the engagement and conceptual understanding of introductory physics students. The first phase of this study focused on the design and development of gamified learning modules for selected topics in introductory physics. The modules were developed by integrating principles of Backward Design, following an escape-room theme with interactive scenarios, and incorporating classic game elements (e.g., points and leaderboards).

The second phase examined the effectiveness of the gamified Kahoot modules using a pretest-posttest control-group design. Sixty-eight (68) students were equally randomly assigned to the control and experimental groups. The experimental group …

Visionglow: Evaluating Minimal-Disruption Smart-Home Control In Apple Vision Pro, Hongxiao Zheng

Dartmouth College Master’s Theses

Smart-home control in mixed-reality environments like Apple Vision Pro often relies on disruptive, application-based paradigms, such as using a smartphone or a windowed virtual interface. These methods create a “mode switch” that imposes cognitive load and pulls users from their primary tasks. We present VisionGlow, a minimal-disruption spatial interaction technique for Vision Pro. VisionGlow represents devices as spatially-anchored “orbs.” To control a device, the user looks at its orb and performs a pinch gesture, which invokes a compact, contextual control panel. We conducted a within-subjects study (N=18) comparing VisionGlow against two baselines: the standard Apple Home app on a smartphone …

Evaluating Fall And Spring Planted Cover Crops For Integrated Management Of Herbicide Resistant Palmer Amaranth And Effect On Soil Health, Vipin Kumar

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Herbicide-resistant Palmer amaranth (Amaranthus palmeri S. Watson) pose a severe threat to agronomic crop productivity in the United States, including corn and soybean production in Nebraska. Therefore, there is an urgent need for diversified and sustainable management approaches. Integrating cover crops (CCs) with herbicide programs represents a promising strategy to achieve Palmer amaranth suppression, sustain crop yields, and contribute to long-term soil health in irrigated corn–soybean production systems in Nebraska.

A meta-analysis of 41 studies and 595 paired observations demonstrated that CCs reduced Amaranthus spp. density and biomass by 37–59% depending on the growing season, with grasses and mixtures …

Detecting Prescribed Fire, Haying And Grazing Events Via Remote Sensing To Create Grassland Disturbance Landcovers For The Ring-Necked Pheasant (Phasianus Colchicus), Megan Amy Baldissara

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation developed disturbance detection models to fulfill the need for remote sensing landcover products describing grassland structure. The use of landcover products derived from remote sensing is increasing over time in pheasant (Phasianus colchicus) research. Such landcover, however, does not provide relevant pheasant structural habitat information (Chapter 1). Pheasants require tall, high-density grassland for nesting, tall grassland with medium density for brood rearing, and tall grassland for wintering. Time since disturbance can serve as a proxy for structure, as it shapes vegetation by removing biomass and resetting succession. Disturbance is easier to detect than structure with current …

Global, Continental, And Local Scale Paleoenvironmental Reconstruction Methods For Interpreting The History Of Miocene North America And The Great Plains, Willow Hue Nguy

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The Miocene of North America is characterized by dynamic changes in herbivore communities, habitat composition, and global climate. Long-term cooling and drying trends influenced large changes in floral and faunal communities. The Great Plains, North America shifted from closed-canopy biomes to open-canopy biomes with C3-grasses to biomes with C4-grasses. This shift affected the herbivore communities as browsing-adapted ungulates were replaced by grazing-adapted ungulates. Much focus has centered on the Great Plains, so it is not well understood how the changes in biomes compare to other regions of North America. The models used for vegetation density indicate open-canopy biomes since at …

Investigating Programming Behaviors To Understand Student Engagement And Experience In Introductory Programming Courses, Marcus Eugene Gubanyi

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Introductory programming courses are foundational to developing students’ problem-solving abilities and shaping their persistence in computing pathways. Engagement with programming tasks plays a central role in student learning and experience. Many research measures, including self-reports and code submissions, offer only a limited view of student engagement with programming tasks. This dissertation leverages programming process data, consisting of keystrokes and compilation events, to capture the programming process as it unfolds and to investigate observable programming behaviors. Guided by educational theories, three studies examine how students’ programming behaviors vary across instructional and assessment contexts, how they relate to motivational profiles, and how …

Large-Scale Experimental Study On The Impact Of Air Cleaning & Ventilation On Indoor Air Quality And Student Illness-Related Absenteeism, Daud Nosham

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This large-scale randomized experimental field study investigated the effect of portable air purifiers (PAPs) on classroom’s air quality and student’s illness related absenteeism. PAPs were installed in 317 classrooms from various school districts located in Eastern Nebraska. The classrooms were randomly assigned into four conditions: three treatment conditions (T1, T2 & T3) and one control condition (device without any filter). T1 was equipped with HEPA filters, T2 added Activated Carbon (AC) layer to HEPA, and T3 further integrated Germicidal Ultraviolet (GUV) alongside HEPA and AC filters. The measured variables were carbon dioxide (CO2), fine particles (PN2.5) and coarse particles (PNcoarse), …

An Integrated Modeling Framework To Evaluate Circularity Of The Corn–Water–Ethanol–Beef Nexus, Heydi Han

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation examines the transition from conventional linear agricultural and food bioenergy systems toward more circular, resilient, and resource-efficient configurations. Prior research indicates that spatial and temporal variability in soil, weather, animal biological responses, and management decisions strongly influences productivity, nutrient-use efficiency, and profitability. Studies have also shown that a diversified circular system can buffer these sources of variability, improving stability and adaptive capacity. Building on these insights, the central focus of this work is to develop an integrated modeling framework to evaluate circularity within the Corn-Water-Ethanol-Beef (CWEB) nexus and explore how climate variability and management choices shape system-wide performance. …

Making Deep Neural Networks Trustworthy: Intelligibility And Safety Through Symbolic Methods, Eleanor Catherine Quint

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The rapid adoption of deep learning has come at the cost of properties long valued in artificial intelligence: intelligibility and safety. This dissertation develops methods that restore these properties by coupling neural networks with symbolic structure.

First, for supervised classification, I propose a differentiable decision tree integrated with a supervised variational autoencoder. The resulting model maintains competitive accuracy and generative performance while exposing clear macro-features in its latent space, improving interpretability.

Second, for reinforcement learning, I extend constrained Markov decision processes by specifying constraints in formal languages. This formal language constrained MDP enables the use of automata for state augmentation, …

Fractional Order Hierarchical Decompositions Using Multigrid Components, Panayot S. Vassilevski

Mathematics and Statistics Faculty Publications and Presentations

Motivated by the fractional order multilevel decompositions of finite element spaces developed previously, we exploit additive representations of popular multigrid (MG) cycles to design fractional order MG decompositions. The additive representations enable us to scale the individual hierarchical components thus ending up with fractional order hierarchical decompositions that are based on the readily available MG components. This results in a highly efficient and scalable (in terms of high-performance) fractional order hierarchical MG decompositions that we tested in the setting of finite element white noise sampling as an alternative to PDE-based white noise sampling using fractional order shifted Laplacians.

Optical, Mechanical, And Transport Characterization Of Two-Dimensional Magnetic Materials., Hiruni Weerahennedige

Electronic Theses and Dissertations

This work investigates the structural, magnetic, thermoelectric, and optoelectronic behavior of layered two-dimensional (2D) materials, with emphasis on Fe₃GeTe₂, Ni-substituted Fe₃GeTe₂ alloys, and GeSe. The study aims to clarify how dimensionality, alloying, and external perturbations influence charge transport, magnetic ordering, and light-matter interactions in van der Waals crystals. Single crystals of Fe₃GeTe₂ and (Ni_xFe_1-x)₃GeTe₂ (x = 0-1) were synthesized by chemical vapor transport and characterized using X-ray diffraction, Raman spectroscopy, and transmission electron microscopy. Angle-resolved polarized Raman spectroscopy resolved symmetry-dependent phonon modes and …

Direct And Satellite-Based Quantification Of Greenhouse Gas Fluxes In Small Ponds., Mark Christopher Tierney

Electronic Theses and Dissertations

As evidenced by their historic losses due to anthropogenic activities, wetlands are undervalued ecosystems that provide numerous ecosystem services, from recreational opportunities to carbon (C) storage. However, these wetlands are also the largest natural source of atmospheric methane (CH₄). Additionally, small water bodies (< 10,000 m²) are disproportionately large emitters relative to larger lakes and reservoirs. As construction and restoration efforts proceed, it is crucial to identify wetlands that need restoration and to understand the factors driving both greenhouse gas (GHG) fluxes and the C balance of these systems. This dissertation investigates the drivers of greenhouse gas fluxes …

Plasma-Enhanced Carbon Nanomaterial Synthesis: A Pathway To Reducing Greenhouse Gasses And Carbon-Based Waste., Zane Ronau

Electronic Theses and Dissertations

This research leveraged incorporation of capacitively coupled radio frequency plasma into chemical vapor deposition (CVD) for a reduction in the temperature requirements [a reduction of energy barrier] needed for the conversion of methane (CH₄), carbon dioxide (CO₂), and various carbon-based-waste to produce value-added carbon nanomaterials. An array of catalysts and catalyst supports were employed to optimize the synthesis of graphitic carbon under various gas environments, temperatures and pressures. The nanomaterials synthesized after fine tuning the growth parameters included graphene, carbon nanotubes (CNT), carbon microtubes and carbon nanocages with a variety of properties. Raman Spectroscopy was used …

Synthesis, Characterization, And Chemical Reactivity Of Calcium-Alginate Hydrogel Beads Containing Metal Nanoparticles And Nanoclusters., Rajiv Kumar Singh

Electronic Theses and Dissertations

This dissertation explores the synthesis, stability, and reactivity of various metal nanoparticles (NPs) and nanoclusters (NCs) of varied size and stabilizers contained within millimeter-sized calcium alginate (Ca-Alg) hydrogel polymer beads. Hydrogel beads synthesized by combining sodium alginate with Au or Ag NPs stabilized with trisodium citrate (Cit) and adding dropwise into a 4.0 M Ca²⁺ solution remained stable and contained within the beads. Those synthesized Au, Pd and AuPd NCs stabilized with glutathione (SG) became partially released from the hydrogel within a day. The synthesis of beads containing aggregated Cit Au NPs occurs by inducing aggregation with tetrakis(hydroxymethyl) phosphonium …

Predicting Major Solar Flares Using Convolutional Neural Networks And Multivariate Magnetic Field Time-Series Data, Arash Azizian Foumani

All Graduate Theses and Dissertations, Fall 2023 to Present

Major solar flares are sudden, intense bursts of X-ray energy from the Sun, capable of severely impacting critical technological infrastructure like satellites, communication networks, and power grids on Earth. Accurate prediction of these high-intensity events is crucial but presents a significant challenge. This is largely due to their infrequent occurrence and the complex, dynamic nature of the Sun's underlying magnetic activity which drives these events. This research focuses on improving the prediction of major solar flares by utilizing detailed historical data that tracks the evolution of magnetic properties within solar active regions over time. This time-based data, however, contains inherent …

Self-Assessment In Calculus I, Bertha Naa Dei Neequaye

All Graduate Theses and Dissertations, Fall 2023 to Present

The purpose of this research investigate how undergraduate students in Calculus I at Utah State University learn and reflect on their level of understanding of Calculus I. In the study, self-assessment practices refer to students reflecting on what they have learned, rating their level of understanding and providing examples that illustrate their level of understanding. The structured and unstructured self-assessment rubrics were the two types of self-assessment rubrics used in the study. The structured self-assessment rubric provides a clear list of objectives of Calculus I topics for students to rate themselves on, while the unstructured self-assessment rubric is an open …

Integrating Manager Perspectives Into The Evaluation Of Wetland Revegetation Strategies, Loren F. Taylor

All Graduate Theses and Dissertations, Fall 2023 to Present

Ecological restoration is the process of assisting the recovery of an ecosystem that has been degraded and is dependent on complex and context-specific decisions. The decision-making process influencing restoration is rarely examined alongside ecological processes. There is a need for research that incorporates the social, economic, institutional, and logistical considerations that shape real-world practices, as well as ecological processes. Decisions made by restoration practitioners and land managers (hereon “manager”) are challenged by the lack of information shared regarding the practical constraints (e.g., cost, labor, specialized equipment) they face. Revegetation, particularly in wetlands, poses challenges due to site conditions and degradation …

Software Developer Job Satisfaction: Interpretable Machine Learning Insights From The Stack Overflow Developer Survey, Reagan E. Hoopes

All Graduate Theses and Dissertations, Fall 2023 to Present

Many researchers have investigated the factors influencing software developer workplace outcomes, such as job satisfaction, due to the central role of the tech industry in the global economy and the specialized expertise of software developers. Past research has often relied on small surveys and traditional analysis methods, with limited use of modern machine learning techniques. This study introduces an efficient and scalable approach to analyzing software developer job satisfaction using interpretable machine learning.

We use data from the 2019 and 2024 Stack Overflow Developer Surveys, an annual survey of software developers worldwide that encompasses a broad range of topics, including …

Machine Learning Applications: Cell Tracking And Nonparametric Estimation Of Non-Smooth Divergences, Mina Mahbub Hossain

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis brings together two important research directions: how to compare different sets of data more accurately, and how to better understand how brain cancer cells move and change shape.

In the first part, we look at a problem in statistics: measuring how different two data sources are from each other. Traditional methods often make strong assumptions, which may not always hold in real situations. Our approach avoids those assumptions by using an ensemble method, a way of combining many weak estimators into one stronger result. This makes the method more flexible and reliable, especially when dealing with complex or …

Multi-Agent Robotaxi Dispatch Coordination In A Real-World Simulation – Optimizing Rider Assignment, Rebalancing, And Charging Using Battery-Dependent Rewards And Welfare Maximization, Paden Thompson

All Graduate Theses and Dissertations, Fall 2023 to Present

We propose an approach to coordinate a robotaxi fleet for an autonomous ride-hail service. This is a service similar to a traditional ride-hailing service (Uber, Lyft), where customers request a ride and are then picked up in a car and dropped off in a new location; except, driverless vehicles called robotaxis are used to transport the customers.

Our approach teaches helpful coordination strategies to a robotaxi fleet while taking into account the individual battery level of the robotaxis. Each robotaxi acts as an individual agent in our simulation and can choose to pick up a rider, reposition to a new …

Using Luminescence Of Quartz Temper From Archaeological Pottery To Infer Wildfire Intensity In The Southwestern Us, Brooklyn D. Dib

All Graduate Theses and Dissertations, Fall 2023 to Present

The size and frequency of wildfires have increased recently, impacting ecosystems, communities, and human health. This research uses the heat-sensitive luminescence signals of quartz sand temper within archaeological pottery to record past wildfire conditions. Pottery sherds, which are fragments of archaeological pottery, from the forest floor in sites in New Mexico and Arizona were collected from different fire contexts (no fire exposure, historical fires, prescribed burns, and modern wildfires). These forests are primarily Ponderosa Pine with a grassy understory. The interior sand grains of each sherd sample were analyzed using optically stimulated luminescence, which dates when the mineral grains were …

Data-Driven Streamflow Forecasting In The Upper Colorado River Basin Using Spatio-Temporal Graph Networks, Akhila Akkala

All Graduate Theses and Dissertations, Fall 2023 to Present

Forecasting river flow is essential for managing water supplies, reducing flood risk, and supporting healthy ecosystems. In the Upper Colorado River Basin, much of the yearly water comes from melting snow. However, many traditional models struggle to capture how snowpack and river flow interact, especially across such a large and complex region.

This study uses a modern machine learning approach called a Spatio-Temporal Graph Neural Network (STGNN) to improve streamflow prediction. The model uses Snow Water Equivalent (SWE)—a measure of how much water is stored in the snowpack—along with river flow data. By treating each river gauge as part of …