Engineering Commons^™

Evaluation Of Intracavity Electromagnetic Field Probes And Sources: Implications For Shielding Effectiveness, Joseph Anthony Ferreri

Electrical and Computer Engineering ETDs

To measure the electric field in a reverberant cavity, a small, minimally invasive probe is required. Common solutions include electrically small surface mounted monopole antennas, B-dots, and D-dots. To obtain an accurate field measurement with a particular probe, it is necessary to characterize it to compensate for its ability to convert electric field into voltage which requires a gauge factor known as effective height. The characterization process is straight forward in open space on a ground plane but requires more insight when in situ in a reverberant cavity. This work adapts ground plane probe characterization methods for cavity measurements, facilitating …

An Analytical Framework For Quantifying Urban And Community Resilience To Natural Hazards From Cell-Phone Gps-Location And Traffic-Flow Data, Georgios Chatzikyriakidis

Civil and Environmental Engineering Theses and Dissertations

Urban areas are increasingly exposed to natural hazards while accommodating a growing share of the global population, yet a consistent science-based framework for quantifying urban and community resilience remains lacking. This dissertation develops a physics-based analytical framework grounded in statistical mechanics and the quantitative theory of Brownian motion. A city is conceptualized as a complex medium in which citizens move analogously to Brownian particles within a viscoelastic environment, influenced by socioeconomic interactions and infrastructure functionality.

A central premise is that urban resilience, interpreted as engineering resilience (an outcome), can be quantified through a single metric: the mean-square displacement MSD=⟨r²(t)⟩, of …

Predictive Natural Language Metrics Of Alzheimer's Disease And Cognitive Decline Trend Analysis, Zerui Ma

Computer Science and Engineering Theses and Dissertations

Inspired by Dr. David Snowden's Nun Study, which linked early-life Propositional Idea Density (PID) to later-life Alzheimer's disease, this thesis investigates two questions: whether fine-tuned Transformer-based large language models (LLM) can detect cognitive decline from patient speech transcripts with meaningful feature attribution, and whether longitudinal PID trends are observable across large-scale internet and academic text corpora. We evaluate dementia prediction on the DementiaBank Pitt Corpus and conduct an exploratory longitudinal PID analysis across seven diverse datasets spanning up to 29 years and over 12.6 million documents. This work suggests that linguistic ability metrics, traditional PID metrics and novel LLM-based analysis, …

Machine Learning And Formal Methods In Quantum Chemistry: Theory And Application, Ishna Satyarth

Computer Science and Engineering Theses and Dissertations

In recent years, the progress in inter-disciplinary application of machine learning and artificial intelligence (ML/AI) have truly transformed various fields, from weather forecasting and drug development to medical diagnostics, energy, and sustainability. Computational chemistry uses computational tools to model, predict, analyze, and explain chemical phenomena, while the Quantum chemistry specifically uses techniques based on quantum mechanics (as opposed to classical mechanics or empirical models). Quantum chemistry or Computational chemistry has also observed a momentum in application of ML techniques over the past decade significantly accelerating results and providing valuable insights into vast datasets, often surpassing traditional methods.

This dissertation explores …

Helium Effects In High Entropy Alloys For Fusion Reactor Plasma Facing Components, Shane Evans

Nuclear Engineering ETDs

The plasma facing materials (PFMs) within fusion reactors, such as the divertor, must be able to withstand high temperature (>1000 K) for extended durations of time, in addition to extreme flux from neutrons, helium (He) ash, and neutral species such as deuterium and tritium. These materials must withstand these conditions while maintaining their selected mechanical properties, minimal sputter yield, and low fuel retention. In recent years refractory high entropy alloys (RHEAs) have been investigated due to their improved mechanical and irradiation-resistant properties when compared to pure W, the current material for PFMs. In this work RHEAs have undergone fusion …

Cfd Simulation Analyses Of The Blowdown Phase Of A Depressurized Loss Of Forced Cooling Accident In A Htgr, Keenan Kresl-Hotz

Nuclear Engineering ETDs

This research numerically investigates the helium-air mixing in HTGR containment cavities during the blowdown phase of a simulated DLOFC accident. The results of the performed CFD simulation analyses, using the commercial code STAR-CCM+, are compared with reported measurements from an experiment conducted at CCNY. The analyses investigate the effects of the RANS and LES turbulence models, numerical mesh refinement, time-step size, and flow rate and temperature of the injected hot helium into the scaled reactor cavity. Calculated parameters analyzed include the pressure and spatial distributions of temperature and oxygen concentration in the simulated reactor and steam generator cavities. CFD oxygen …

In-Situ Measurement Of Dynamic Deuterium Retention In Tungsten-Based Alloys Under Plasma Exposure, Ethan Gabriel Rashap

Nuclear Engineering ETDs

Nuclear fusion is a promising pathway for sustainable energy production, but the performance of plasma-facing materials remains a key challenge for reactor operation. In particular, hydrogen isotope retention in tungsten—the leading candidate material for divertor components—affects tritium inventory, fuel recycling, and overall material lifetime. In this work, the temperature-dependent deuterium retention behavior of W–Ti and W–TiTa alloys was experimentally investigated under fusion-relevant ion irradiation conditions between 400 and 700 K. In-situ nuclear reaction analysis (NRA) was used to track retention during plasma exposure and subsequent cooldown, providing depth-resolved insight into deuterium accumulation and release. The results show that deuterium retention …

Self-Supervised Spoofing Detection, David S. Choi

Electrical and Computer Engineering ETDs

Global Navigation Satellite Systems (GNSS) are vulnerable to spoofing attacks that can mislead receivers with counterfeit signals. Traditional detection techniques, such as antenna-based, encryption based, and signal processing approaches, often face limitations in adaptability, computational cost, or reliance on predefined thresholds. Supervised machine learning models, while powerful, require large labeled datasets and struggle to generalize to unseen spoofing scenarios. In this work, we propose a self-supervised spoofing detection framework based on Adaptive Sparse Gaussian Processes (ASGP). The method predicts incoming GNSS features using past observations and identifies spoofing as anomalous deviations in the prediction residuals. Unlike supervised approaches, ASGP adapts …

Millimeter-Wave Antenna Gain Enhancement Through Stacked Planar Substrates, Zachary Bergstedt

Electrical and Computer Engineering ETDs

This work presents a new wideband millimeter-wave (mmWave) and sub-terahertz antenna design with flexible directivity through the integration of stepped horn antennas and transverse substrate integrated waveguide (SIW) slots for radar and communication applications. The work gives a theoretical and analytical basis for this filter-inspired approach to improving bandwidth and directivity, and presents design and results for a standalone stepped horn, a Ka-band antenna with a solid stepped horn and SIW feed, and W-band antennas with empty SIW feeds and stepped horns manufactured out of multiple planar layers. The realized antennas show bandwidth up to 40% and gain up to …

Quantum Control Protocols For Robust Quantum Computing, Leeseok Kim

Electrical and Computer Engineering ETDs

The fundamental goal of quantum computing is to precisely control quantum systems to perform meaningful tasks, including implementing high-fidelity quantum gates for reliable quantum computation and accurately simulating complex quantum many- body dynamics. In this dissertation, we develop improved quantum control protocols for three distinct objectives, quantum error suppression, quantum optimal control, and analog quantum algorithms, achieving performance beyond standard approaches. First, we introduce new dynamical decoupling protocols, including both determin- istic and randomized constructions, that can substantially outperform conventional deterministic sequences. We then extend the randomized approach to dynamically corrected gates. Second, we propose a randomized quantum optimal control …

Fault Tolerant Quantum Computing With Lower Overhead, Benjamin E. Anker

Electrical and Computer Engineering ETDs

Quantum computation promises asymptotic speedups over classical algorithms, but realizing these advantages requires overcoming the noisiness of quantum hardware. Although fault-tolerant error correction can allow for reliable quantum computation even using unreliable components, the resource overheads required can substantially erode the asymptotic performance gains. This dissertation focuses on constructing and optimizing fault-tolerant procedures with lower overhead than previous methods were capable of. We present new frameworks for fault-tolerant syndrome extraction using flag gadgets with exponentially reduced ancilla requirements, explicit measurement schedules that achieve asymptotically fewer measurements than stabilizer generators, and a general method for making arbitrary Clifford circuits fault tolerant. …

Alternative Positioning, Navigation, And Timing In Global Navigation Satellite System Denied Environments, Joshua R. Atencio

Electrical and Computer Engineering ETDs

Global Navigation Satellite Systems (GNSS) provide the majority of critical positioning, navigation, and timing (PNT) services for civilian, commercial, and military applications. However, GNSS is vulnerable to service denial from spoofing and jamming from adversaries and environmental obstruction. These vulnerabilities highlight the need for resilient Alternative PNT (APNT) methods. This dissertation investigates APNT frameworks operating in GNSS denied environments. We develop coalition formation and matching theoretic models that allow users APNT services from anchor nodes under resource constraints and in adversarial or emergency conditions. The proposed frameworks optimize positioning accuracy, network utility, and system stability while accounting for geometric dilution …

Assessing Uranyl-Specific Dnazymes And Dna-Aptamers For Uranium Binding In Environmentally Relevant Waters, Ashley R. Apodaca-Sparks

Civil Engineering ETDs

The legacy of uranium mining affects many communities in the western United States, resulting in elevated levels of uranium in surface water. The ability to quickly and accurately detect uranium on site in affected communities can lead to real-time water quality analysis that informs risk assessment and remediation efforts. The objective of this work is to advance the application of biosensing technologies for the measurement of uranium in waters affected by mining legacy. The third chapter of this thesis compares ANDalyze by AlpHa Instruments, a commercially available uranium biosensor, and inductively coupled plasma mass spectrometry (an EPA-verified method for uranium …

Post-Fire Flood Modeling In Ruidoso, New Mexico: Improving Burn Scar Runoff Predictions, Pramesh Bhaila

Civil Engineering ETDs

Recent large wildfires in New Mexico have demonstrated severe hydrological driven by vegetation loss and the development of hydrophobic soil surfaces. This thesis evaluates the performance of three infiltration models—Curve Number (CN), Linear Constant (LC), and Green–Ampt (GA)— for the watershed impacted by the 2024 South Fork and Salt Fires near Ruidoso, New Mexico. All three models performed comparably during post‑fire simulations, with strong performance in 2024 and notable degradation in 2025, particularly for the CN. Post-fire analyses indicate substantial reductions in infiltration capacity, with CN increasing by 18–24%, LC initial deficit decreasing by 65–77%, effective hydraulic conductivity reduced by …

Investigating Workforce Development Gaps In Tribal Transportation Agencies, Benson Long Jr

Civil Engineering ETDs

Tribal transportation programs face challenges in recruiting and retaining qualified staff, prompting reliance on external consultants for key responsibilities. This study explores how workforce constraints and organizational structures influence tribal outsourcing decisions. Survey data from 57 tribes informed a logistic regression model examining how geographic isolation, population size, training access, and the presence of a transportation department affect preferences for internal work, actual task completion, and instances where tribes intended to perform tasks in-house but outsourced instead. Findings indicate that outsourcing is driven by limited internal capacity, including staffing shortages, lack of certified personnel, and training opportunities. Geography also plays …

Hierarchical Safe Reinforcement-Learning Framework For Mission-Aware, Edge-Enabled Multi-Uav Iot Networks, Abee F. Alazzwi

Electrical and Computer Engineering ETDs

This Ph.D. dissertation presents a unified Hierarchical Safe Reinforcement Learning (HSRL) framework for mission-aware, edge-enabled multi-UAV Internet of Things (IoT) networks. The work addresses the need for autonomous aerial infrastructures capable of delivering low-latency communication, scalable edge computation, and provably safe operation in dynamic environments. The dissertation develops three primary contributions. First, it formulates longhorizon drone base station placement and load balancing as a strategic actor–critic learning problem, enabling proactive adaptation to spatiotemporal demand variations. Second, it introduces a mission-aware multi-agent reinforcement learning controller for coordinated mobility, sensing, and computation offloading under latency and energy constraints. Third, it integrates a …

Assessing The Impact Of Multi-Physics Effects On Photovoltaic Module Degradation Using Computational Modeling, James Yuan Hartley

Mechanical Engineering ETDs

This dissertation describes research to develop and apply multi-physics simulation capabilities using finite element methods to analyze photovoltaic module damage mechanisms. Analyses of full-scale solar modules under mechanical load are presented, including experimental validation against measurements of external deflection and internal strain. Module damage by solar cell breakage and interconnection fatigue are discussed, and the applicability of simplifying analyses using mathematical plate theory is assessed. Detailed sub-module component models undergoing thermal-mechanical stressors are also presented, to identify the design features and materials most influential to stress generation and to assess the representativeness of using sub-module assemblies in accelerated testing. Finally, …

Brain-Based Mechanisms Of Behavioral Impairment In Fetal Alcohol Spectrum Disorder (Fasd): The Neuroimaging Biomarkers Of Inhibitory Control, Zinia Pervin

Biomedical Engineering ETDs

The developing brain is highly susceptible to alcohol-induced toxicity, often resulting in long-term deficits in executive function and behavioral regulation. Inhibitory control impairments are among the most prominent deficits observed in Fetal Alcohol Spectrum Disorder (FASD). This study investigated the neural mechanisms of inhibitory dysfunction using a multimodal MEG–DTI approach in 67 children aged 6–8 years (34 with FASD, 33 controls) who performed a Go/No-Go task. Source-level MEG analyses revealed reduced stimulus-locked cortical activation in the anterior cingulate cortex and significant group-by-hemisphere interactions in the superior parietal cortex and cuneus. Time–frequency analyses showed diminished response-locked beta power in the sensory-motor …

Technical Advancements In Single-Molecule Spectroscopy For High-Throughput Measurement Of Long-Time Dynamics, Quyen B. Le

Chemical and Biological Engineering ETDs

Single-molecule fluorescence spectroscopy is a powerful technique for resolving transient biomolecular dynamics and quantifying free energy landscapes, kinetics, and binding interactions. However, two fundamental limitations restrict its broader application: slow, labor-intensive data acquisition and the limited observation time imposed by fluorophore photobleaching. These limitations hinder its use in drug discovery and biomedical engineering applications that require both high-throughput and access to long-time dynamics. In this work, both challenges are addressed through technical advancements. First, a simple, generalizable approach is introduced to automate data acquisition, eliminating manual intervention during experiments. This increases the acquisition rate by more than an order of …

Development Of A Lead-Lithium Eutectic Magnetohydrodynamic Loop For Corrosion Studies, Xavier S. Angus

Nuclear Engineering ETDs

Lead–lithium eutectic (LLE) is a leading candidate coolant and tritium breeder for fusion reactor blankets due to its favorable heat transfer properties and high tritium breeding ratio. However, LLE is highly corrosive and, in the strong magnetic fields present in fusion reactors, experiences magnetohydrodynamic (MHD) effects that can produce significant pressure drops and flow instabilities. Understanding corrosion behavior in these extreme environments is essential for assessing the viability of LLE blanket systems. This work presents the design and construction of a forced-convection LLE corrosion loop to study corrosion behavior at temperatures up to 425 °C and flow velocities up to …

Design And Analysis Of An Intermediate Heat Exchanger And Passive Decay Heat Removal System For A Generic Fluoride Salt-Cooled High-Temperature Reactor Application, Bao Hoang Nguyen

Nuclear Engineering ETDs

Generation IV reactors, such as the Fluoride salt-cooled High-temperature Reactor (FHR), feature efficient heat transfer and passive heat removal systems. However, accurately predicting thermal behavior under steady-state and transient conditions remains challenging. This work designs and evaluates a twisted tube heat exchanger (TTHX) serving as an intermediate heat exchanger (IHX) and a reactor cavity cooling system (RCCS) serving as a passive decay heat removal system for a generic FHR (gFHR), integrating both systems into a system-level MELCOR model. The TTHX was first designed and assessed using a MATLAB-based framework, followed by detailed MELCOR simulations. The results demonstrate effective heat transfer …

Sensitivity-Informed Resonance Parameter Cross Section Adjustments, Matthew Juan Lazaric

Nuclear Engineering ETDs

This work details the process of developing several new features into the MCNP6.3 Monte Carlo code for use in uncertainty quantification and reduction. These new capabilities, which include the CLUTCH method of calculating k-eigenvalue cross section sensitivities and the Windowed Multipole method of calculating cross sections, are implemented and verified against previous implementations and existing cross section data, respectively. These capabilities are then combined to produce sensitivities of k-eigenvalue to resonance parameters, which are verified against direct perturbation sensitivity estimates. The resonance parameters are calibrated using linear Bayesian methods and the accuracy of the resulting cross section is evaluated via …

Representativeness And Sensitivity Analysis Of Accident Tolerant Fuel Cladding Behavior In Reactivity-Initiated Accidents, Melissa Andrea Moreno

Nuclear Engineering ETDs

Accident Tolerant Fuels (ATFs) such as FeCrAl are being developed to enhance safety margins in light water reactors during transients like Reactivity Initiated Accidents (RIAs). This dissertation evaluates the accuracy and representativeness of TRACE thermal hydraulic models for predicting FeCrAl C36M cladding behavior under steady state and transient flow boiling conditions. Benchmarking against University of New Mexico separate effects experiments shows that TRACE reproduces key thermal trends but underpredicts cladding temperatures near CHF by approximately 25 to 30%. A calibrated uncertainty and global sensitivity analysis, using Sobol indices, demonstrates that CHF and cladding temperature variability are dominated by mass flux, …

Nuclear Deterrence: Enhancing The Mission Through Smart Factory Predictive Solutions, Jarrod Matthew Ronquillo

Chemical and Biological Engineering ETDs

To meet the stewardship and modernization initiatives set by the Department of Energy new technologies must enter the manufacturing facilities within the nuclear deterrent complex. Predictive solutions begin with collecting data. An equipment health monitoring device was created to streamline data collection and organization for equipment and processes. A predictive and process performance dashboard was developed for a deionized water system. The dashboard used Western Electric statistical process rules and a machine learning regression algorithm to predict when the resistivity would fall out of specification. Lastly, a remaining useful life calculation was developed for all equipment related to nuclear deterrent …

Calibration Methodology, Diagnostic Performance, And Redesign Of The Current Monitors On The Z Machine At Sandia National Laboratories, Stacie Hernandez

Electrical and Computer Engineering ETDs

A proper evaluation of the current diagnostics fielded in the inner-MITL region of the Z facility in 3D simulation models had not been performed until now. The evaluation of the current monitors has brought insight to their performance in a new view that has led to discoveries. The B-dot probe was the current diagnostic-of-choice since before the refurbishment of the Z facility [1] and until the development of the Inductively Driven Transmission Line (IDTL) current diagnostic [2]. Experimental data has shown that the IDTL can produce cleaner signals and it is more robust than conventional B-dots. Simulation (modeled using COMSOL …

Statistical And Spectral Theory For Spatially Correlated Random Aperiodic Antenna Arrays, Thomas Edward Christian Jr

Electrical and Computer Engineering ETDs

Aperiodic phased arrays enable beam steering, interference suppression, and spectrum efficiency for 6G, radar, biomedical imaging, and distributed sensing. Minimum inter-element spacing and keep out zones induce spatial correlation, violating the i.i.d. element-position assumption behind classical probabilistic random array theory. This dissertation develops a unified probabilistic spectral framework for correlated (non-i.i.d.) arrays. Second moment power pattern analysis incorporates the pair-correlation function  and structure factor , recovering the i.i.d. limit when  and accommodating unequal excitations. Side lobe and main lobe fields deviate from Rayleigh/Exponential and are modeled by weighted Nakagami and Gamma-mixture distributions, parameterized via Monte Carlo. The blue noise spectral …

Novel Algorithmic Methods For Random Telegraph Noise Detection And Characterization In Electronic Devices, Victor Darie Pepel

Electrical and Computer Engineering ETDs

Random telegraph noise (RTN) produces discrete stochastic fluctuations in nanoscale semiconductor devices and increasingly limits performance and reliability as dimensions scale. This dissertation introduces three algorithmic contributions enabling automated and accurate RTN characterization across diverse devices and operating conditions. First, a computationally efficient histogram-based detection algorithm enables rapid identification of RTN in large focal plane array datasets for statistically robust defect analysis. Second, a frequency decomposition framework separates slow and fast RTN components, extending the range of extractable time constants and reducing estimation error in multi-trap signals obscured by background noise. Third, to address the lack of standardized RTN metrics, …

Applications And Comparisons Of Machine Learning Methods In Ultra-Fast Laser Control, Aasma Aslam

Electrical and Computer Engineering ETDs

This dissertation demonstrates the applications and comparative analyses of machine learning methods in ultrafast laser control. By learning the relationship between the system’s input parameters and output pulse characteristics, the performance of a laser can be significantly improved. In this work, the results are presented in two stages by utilizing data from the femtosecond laser system. The first stage concerns two neural networks, named NN1 (fitrnet) and NN2 (feedforwardnet). The second stage, which extended with five different models, namely the linear regression (fitlm), the support vector machine (SVM), the Gaussian process regression (GPR), the boosted tree (fitrensemble), and LASSO (fitrlinear), …

Visual Interpretability Of Multimodal Tissue Perfusion Classification Using Grad-Cam And Saliency Maps, Metehan Zorluoglu

UNLV Theses, Dissertations, Professional Papers, and Capstones

Accurate identification of the tissue perfusion phase from hand images can aid doctors in decision-making with non-invasive techniques. The present study proposes a multimodal deep learning model for classifying the tissue perfusion phase using infrared, thermal, and visible spectrum images of the human hand. The proposed model consists of various preprocessing techniques such as manipulation, homography alignments, and masking. The significant contribution of this thesis is the interpretability analysis of deep learning models, achieved through the analysis of saliency maps and the Gradient-weighted Class Activation Mapping (Grad-CAM) methods. The purpose of this method is to find out how the convolutional …

Exploring Ai-Driven Scaffolding For Critical Questioning In Argument Evaluation, Ebenezer A. Belete

UNLV Theses, Dissertations, Professional Papers, and Capstones

The fast-paced changes caused by generative AI (GenAI) innovations call for exploring the potential benefits of GenAI in empowering 21st-century pedagogical strategies. Previous studies in the field of argumentation have shown how students can benefit from using critical questions. However, scaffolding argument evaluation through custom GenAI using critical questions has not been systematically investigated. This study involved two components: (1) designing and determining the usability of a GPT-powered conversational assistant (CQMAA Conversational Assistant) and (2) testing its impact on participants' efficacy for argument evaluation and their acceptance of GenAI as a learning tool through a pretest–posttest experiment. A convergent mixed-methods …