Digital Commons Network^™

Impact Of Gas Interactions With Nano Porous Geological Material In The Presence Of Water Vapor, Matthew D. Powell

Chemical and Biological Engineering ETDs

Predicting gas transport in nanoporous geological material requires understanding competitive adsorption and transport under humid conditions. However, most adsorption studies rely on single-component equilibrium measurements that do not capture these effects. This dissertation develops an experimental methodology to directly quantify multicomponent gas adsorption and breakthrough behavior under controlled relative humidity. The method was first applied to the Kr/Xe–N2–H2O system, where it resolved competitive adsorption behavior in humid porous media and produced a bivariate model relating noble gas adsorption to noble gas partial pressure and water saturation. The methodology was then extended to the CO2–N2 H2O system. Results showed that water …

Control Of Reshock In A Shock Tube, Alexander Sweis

Mechanical Engineering ETDs

Reshocks can pose a threat to the structural integrity of structures and buildings. While incident shock waves pose larger threats, the study of reshocks and reshock attenuation is important to consider. This thesis investigates methods for controlling and attenuating reshock strength within a shock tube through material-based damping and modifications to baffle box geometric configurations. Experiments are performed using a custom-built shock tube in the University of New Mexico fluid mechanics laboratory. Four baffle box configurations are examined: a foam-lined configuration, a foam-lined configuration with ”egg crate-like” textured foam, an empty (no foam) configuration, and a configuration which incorporates a …

Design And Feasibility Study Of An Air-Cooled Reactor Cavity Cooling System For Fluoride-Salt-Cooled High-Temperature Reactors, Alexandra D. Martinez

Nuclear Engineering ETDs

Licensing efforts for Fluoride-Salt-Cooled High-Temperature Reactors (FHRs) are dependent on passive safety systems designed for decay heat removal, yet no prior study has evaluated an air-based Reactor Cavity Cooling System (RCCS) for this role. This thesis addresses that gap by determining whether an air-cooled RCCS can be designed to passively remove post-shutdown decay heat from the Mk 1 FHR. An RCCS configuration was developed and sized using a one-dimensional lumped-parameter design methodology, then evaluated through system-level thermal-hydraulic modeling in RELAP5-3D under a conservative, lower-bound post-shutdown transient. The analysis characterizes the radial heat-transfer pathways from the FHR core to the RCCS …

Development Of Dynamic Proof-Mass Configurations For Broadband Piezoelectric Energy Harvesting, Nico E. Galarza

Electrical and Computer Engineering ETDs

The purpose of this thesis is to investigate and develop dynamic proof-mass configurations for broadband piezoelectric energy harvesting. Conventional piezoelectric energy harvesters are typically limited by narrow operating bandwidths, restricting their performance under variable-frequency excitation. This research presents the design, fabrication, and experimental evaluation of multiple proof-mass concepts intended to increase the usable frequency range of cantilever-based piezoelectric energy harvesters. Several dynamic mass configurations were developed using additive manufacturing techniques and integrated with commercially available piezoelectric cantilevers. Experimental testing was conducted under controlled vibration conditions to characterize voltage response, resonant behavior, and bandwidth performance. The results demonstrate that dynamic proof-masses …

Synergizing Crowd Collaboration: Enhancing Crowdsourcing Matching Via Integration Of Matching Theory And Coalition Games, Rowan Aengus Kinney

Electrical and Computer Engineering ETDs

This paper tackles the challenges inherent in crowdsourcing dynamics by introducing the CROWDMATCH mechanism. Aimed at enabling crowdworkers to strategically select suitable crowdsourcers while contributing information to crowdsourcing tasks, CROWDMATCH considers incentives, information availability and cost, and the decisions of fellow crowdworkers to model the utility functions for both the crowdworkers and the crowdsourcers. Specifically, the paper presents an initial Approximate CROWDMATCH mechanism grounded in matching theory principles, eliminating externalities from crowdworkers’ decisions and enabling each entity to maximize its utility. Subsequently, the Accurate CROWDMATCH mechanism is introduced, being initiated by the outcome of the Approximate CROWDMATCH mechanism, and employing …

Simulations Of Atmospheric Pressure Streamer Discharges: Mechanisms Of Streamer Propagation And Related Physics, Dejan Nikic

Electrical and Computer Engineering ETDs

Gas discharge simulations are performed with particular focus on photoionization process in a positive streamer discharge. The effects of this process are investigated by isolating the change in photoionization mean free path (MFP) and keeping the additional processes constant. Furthermore, comparison are made between various effects of simulation parameters, such as initial conditions, geometry extent, simula- tion particle count etc. All of these simulations are performed using a modern Direct Simulation Monte Carlo Particle-in-Cell (DSMC-PIC) code developed by Sandia Na- tional Laboratories. Large scale simulations including 1 cm and 5 cm electrode gaps are performed under standard atmospheric condition air. …

Computationally Tractable Methods For Constrained Optimal Control And Reachability Analysis Of Nonlinear Stochastic Dynamical Systems, Karthik Sivaramakrishnan

Electrical and Computer Engineering ETDs

Autonomous systems operating in uncertain environments require methods that can rigorously quantify safety, predict future behavior, and compute optimal decisions tractably. The unifying challenge is reasoning about uncertainty propagation in constrained dynamical systems. Motivated by autonomous spacecraft inspection, this dissertation develops model-based and data-driven methods for stochastic optimal control and stochastic reachability. First, it studies optimal on-orbit inspection of an uncertain tumbling spacecraft in both single-agent and multi-agent settings, and derives computationally efficient reformulations for exploring trade-offs among sensing, trajectory deviation, and fuel use. Second, it develops a probabilistically safe penalty-based reinforcement learning method that preserves gradient information during training …

Wildfire Impacts On Fluvial Hydrology From Watershed To National Scales, Paige G. Tunby

Civil Engineering ETDs

Wildfires alter the water quantity and quality in downstream river networks. Fires promote biodiversity, maintain habitat, and provide many ecosystem services in a fire-adapted landscape. However, changes in the natural fire regimes can alter ecosystem function and threaten the water security of impacted downstream communities. The magnitude, timing, and persistence of these impacts are difficult to predict due to the lack of high-resolution datasets with adequate coverage to evaluate spatiotemporal trends after a fire. This dissertation moves us beyond the status quo to evaluate post-fire fluvial responses across scales, from the event-scale impacts after the Hermit’s Peak-Calf Canyon wildfire in …

Effect Of Geothermal Conditions On Silica Flour Modified Wellbore Cement, Travis Benjamin Broadhurst

Civil Engineering ETDs

Considerable work has been conducted on modified wellbore cements, but a knowledge gap exists in the effects of downhole conditions on cement, especially tensile strength. In this study, a pressure vessel simulates representative downhole conditions (200⁰C, 1.5 MPa) with a reference solution for geothermal brine and naturally occurring geothermal gases. Samples are removed after 28-days for unconfined compressive strength testing, Brazilian tensile strength testing, elastic moduli measurement, and chemical analyses by X-ray diffraction and electron microprobe. Aqueous chemical analysis suggests multiple active reactions between the geothermal fluid and cement that are exacerbated by higher temperatures, but do not …

Mechanisms Of Advanced And Energy Efficient Wastewater Treatment Technologies, Derek Belka

Civil Engineering ETDs

This dissertation combines meta-omics, microbial ecology, and hydrodynamic analysis to explore mechanisms of enhanced biological phosphorus removal (EBPR) and aerobic granular sludge (AGS) in municipal wastewater treatment. Metagenomic and functional gene profiling of a laboratory sequencing batch reactor fed with amino acids and proteins, and with a low abundance of known polyphosphate-accumulating organisms (PAOs), revealed abundant Herpetosiphonaceae and Dermatophilaceae families possessed key PAO metabolic traits, including phosphate scavenging, anaerobic carbon pathways, and ppk2 gene variants aligned with established PAOs. These findings suggest amino acid-driven EBPR can occur via previously unrecognized taxa, challenging current engineering assumptions and highlighting the need for …

Investigating The Corrosion Behavior Of Stainless Steel 316 In Static Lead Lithium Eutectic Under Applied Stressed Conditions, Daniel E. Levario

Nuclear Engineering ETDs

As fusion power moves closer to feasibility, identifying structural materials compatible with breeding blanket environments remains a critical challenge. Lead-lithium eutectic (LLE) is a leading candidate breeder and coolant material due to its low melting point and combined tritium breeding and neutron multiplication capability. However, the corrosive nature of LLE toward structural steels at elevated temperatures must be characterized before these systems can be reliably deployed. This study investigates the corrosion behavior of Type 316 stainless steel in static LLE under applied stress conditions at 550°C using C-ring stress corrosion specimens. Post exposure analysis via optical microscopy, SEM, EDS, and …

Mapping And Modeling Threat-Evoked Brain States After Early Life Adversity, Taylor W. Uselman

Biomedical Sciences ETDs

Early life adversity (ELA) increases lifelong neuropsychiatric vulnerability. Yet how ELA reorganizes brain-wide activity and circuit coordination across later experience remains unclear. This dissertation tests the hypothesis that ELA alters adult brain-wide activity and responses to threat through disrupted coordination among neural systems that regulate emotional experience, including prefrontal-limbic and monoaminergic systems. Longitudinal manganese-enhanced MRI of adult mice exposed to standard or fragmented early care, combined with computational processing and statistical modeling, quantified brain states before, during, and long after innate predator threat. These studies established that acute threat evokes large-scale, distributed brain activity that evolves over time. ELA potentiates …

Helmholtz Reciprocity In Bidirectional Y-Junction Couplers, Hosuk Lee

Optical Science and Engineering ETDs

This thesis explores the light propagation characteristics in Y-junction couplers based on the Helmholtz reciprocity principle. The Helmholtz reciprocity principle is a crucial concept in optical system design, and it has primarily been understood based on input-output symmetry. However, this study emphasizes reciprocity needs to consider the entire system, beyond the traditional input-output symmetry reciprocity interpretation. For this study, we specifically examined the direction-dependent asymmetrical outputs, in the Whistle-geometry Ring Laser (WRL) structure. And the WRL results cannot be fully explained by simple input-output symmetry for reciprocity. The Y-junction coupler in the WRL structure makes different output characteristics based on …

Algorithmic Sculpting Of Complex Fused Silica Surfaces For Nondestructive, Mode-Matched Cavity Quantum Electrodynamics: Adaptive Co2 Milling And Simulation-Guided Ultrafast Inscription, From Fiber Fabry-Perot Cavities To Monolithic Architectures, Meagan E. Parker

Optical Science and Engineering ETDs

Quantum sensors achieve exceptional measurement sensitivity through coherent, well-isolated quantum systems, but practical deployment is hindered by destructive readouts that require repeated state preparation and create long system dead times. Optical cavities enable continuous, nondestructive measurements with minimal back-action, yet integrating high-finesse cavities into scalable quantum devices remains limited by existing fabrication methods. To overcome these constraints, an adaptive CO₂ laser-milling platform was developed. Guided by glass thermodynamics and melt dynamics, this closed-loop system uses in-situ phase-shifting interferometry to sculpt complex fused-silica surfaces with sub-nanometer root-mean-square roughness. The platform was validated by fabricating extended-length fiber Fabry–Pérot cavities and monolithic micro-cavity …

3d Electromagnetic Simulations Of A 1.6 Cell S-Band Photoinjector: Emittance Studies For Electron Microscopy, Trudy Bolin

Electrical and Computer Engineering ETDs

Modern beam-based materials research demands electron sources with increasingly precise time resolution, high brightness, and stability. For example, there are various instruments across the U.S. dedicated to ultrafast electron diffraction (UED), but fewer are dedicated to ultrafast electron microscopy (UEM), which demands beam stability. Modeling femtosecond electron bunches with ultra-low emittance < 50 nm-rad inside a 1.6-cell S-band (2856 MHz) rf photoinjector with full 3D electromagnetic simulations can require high-performance computing (HPC) environments due to the scale disparity between the macroscopic cavity geometry and the femtosecond-scale bunch kinematics. To enable optimization in a desktop computing environment, this work presents a streamlined 3D electromagnetic Particle-in-Cell (PIC) simulation framework optimized for 400-femtosecond bunch regimes. The covariance method was employed to study emittance properties for electron bunch counts ranging from thousands to millions and has successfully resolved highly transient, pure rf phase-space rotations, such as a localized energy-spread minimum occurring at the gun exit iris. To overcome the computational cost of these simulations, a machine-learning-based Bayesian optimization approach was deployed to construct multi-objective Pareto fronts from sparse datasets. Because the simulation software is scalable from desktop to HPC facilities, the framework is ready for experiments at the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory (LBNL).

Real-Time Waveform Synthesis For Rfsoc-Based Quantum Control Systems, Tiamike I. Dudley

Electrical and Computer Engineering ETDs

RFSoCs are gaining adoption in many labs for quantum control systems thanks to their compactness and affordability. Making full use of the many components on an RFSoC evaluation board is a challenging engineering problem that must be solved to realize scalable control systems. In this dissertation, I evaluate the performance of various RFSoC components in the context of quantum information science. I present two custom FPGA engines that accelerate and parallelize arbitrary waveform generation. The first engine can be instantiated many times to power low-speed DACs for ion-shuttling trap electrodes. The second engine synthesizes CPMG-XY8n dynamical decoupling pulse sequences on …

Multi-Robot Cooperative System For Complex Aerospace Manipulation Tasks: Theory And Application, Longsen Gao

Electrical and Computer Engineering ETDs

Multi-robot systems can extend manipulation capabilities beyond the limits of a single robot, particularly for tasks involving large, flexible, delicate, or free-floating payloads. Reliable cooperative manipulation, however, remains difficult when payload dynamics, contact geometry, compliance properties, deformation-induced forces, and external disturbances are only partially known, and when safety constraints must be enforced during physical interaction. This dissertation develops a two-layer control framework for resilient multi-robot manipulation under uncertainty, with emphasis on space servicing, satellite stabilization, aerial transportation, and cooperative manipulation of free-floating structures.

Enhanced Computational Modeling Of Photoionization And Streamer Formation, Anahita Alibalazadeh

Electrical and Computer Engineering ETDs

Photoionization is a key mechanism governing the formation and propagation of streamer discharges in air by generating electron-ion pairs ahead of the streamer front. Accurate and computationally efficient modeling of this non-local process is essential for reliable plasma simulations. However, the widely used Zheleznyak photoionization model relies on empirical assumptions and requires computationally expensive domain-wide integration.

This dissertation advances photoionization modeling in three ways. First, the classical integral model is enhanced by incorporating experimentally measured vacuum ultraviolet (VUV) emission spectra together with photoabsorption and photoionization cross-section data, enabling direct calculation of the photoionization source term as a function of pressure …

Developing A Dispersion Interferometer For Characterizing Power Flow Plasma Formation And Transport Studies, Nathan R. Hines

Electrical and Computer Engineering ETDs

Sandia's refurbished $Z$-pinch machine experiences persistent current loss in its post-hole convolute and inner magnetically insulated transmission line regions, widely attributed to low-density electrode plasmas whose formation and transport remain poorly constrained by existing diagnostics. This dissertation develops and validates a fiber-coupled, continuous-wave, second-harmonic orthogonally polarized dispersion interferometer for time-resolved measurements of electron areal density in millimeter-scale gaps. The diagnostic employs single-laser second-harmonic generation, non-steering differential phase control, and polarization-based phase retrieval to achieve sub-$10^{15}$~cm$^{-2}$ sensitivity, multi-hundred-megahertz bandwidth, and sub-$200$~$\mu$m effective cross-gap spatial resolution. Performance is benchmarked against a $94$~GHz interferometer on the UNM Helicon-Cathode plasma device and then fielded …

Load Balancing Algorithms For Cloud Computing Systems, Mark Rakesh Christian

Electronic Theses and Dissertations 2020 - Present

Cloud computing depends on load balancing to allocate user requests among virtual machines (VMs), affecting response time, utilization, and scalability. Round Robin, Equally Spread Current Execution, and standard Throttled scheduling are widely used; however, standard Throttled selects among eligible VMs using an implementation-dependent order with no explicit preference. This thesis proposes the Weighted Throttled Load Balancing (WTLB) algorithm, which introduces an explicit, deterministic selection priority among eligible VMs, implemented by modifying the Throttled scheduler within CloudAnalyst.

Evaluated under an identical six-region, multi-data-center configuration against Round Robin, ESCE, and standard Throttled, WTLB preserves the aggregate response-time, processing-time, and cost profile of …

A Multidimensional Conceptual Framework For Supportive Outdoor Environments In Healthcare Settings, Mona Ali, Dalia A. Beheiry, Rowaida Kamel, Hammam Serageldin

HBRC Journal

The integration of supportive outdoor environments (SOEs) in healthcare settings has gained increasing attention for their potential to enhance patient recovery, support staff well-being, and contribute to holistic therapeutic outcomes. This scoping review examines design recommendations for inclusive outdoor environments in healthcare settings that impact user health and experience. Guided by the Joanna Briggs Institute (JBI) framework for scoping reviews, a comprehensive search was conducted across five databases (Google Scholar, PubMed, ScienceDirect, JSTOR, Sage), yielding 697 records. Following screening and applying the inclusion and exclusion criteria, 18 articles were selected for analysis. This scoping review identified consistent evidence linking outdoor …

Artificial Intelligence-Driven Framework For Enhancing Risk Management In The Architectural Design Process In Egypt, Ayman Ahmed Ezzat Othman, Nadia Mohamed Algheetany, Fatma Othman Alamoudy

Mansoura Engineering Journal

The construction industry is crucial for achieving the United Nations Sustainable Development Goals (SDGs). However, it faces significant risks during the Architectural Design Process (ADP) that affect project quality, cost, schedule, and sustainability. Due to its limitations, traditional risk management (RM) is often inadequate for addressing these challenges. This study aims to develop a novel Artificial Intelligence (AI) driven framework to enhance RM practices in Egyptian Architectural Design Firms (ADFs) through proactive RM and improved data-driven decision making. A mixed methods research approach was adopted to achieve the research objectives. A comprehensive literature review examined RM, ADP, and AI applications …

Stop Blaming My Users: Illumination Of The Technocentric Mythos Bias, Ervin H. Frenzel, Richard Lightcap

Journal of Cybersecurity Education, Research and Practice

 Abstract -This conceptual essay addresses the need for systemic and systematic transdisciplinary analytical techniques within cybersecurity and technical security. This conceptual essay is contingent upon recognition that cybersecurity is not simply technical in nature, it does not need an adversary, and more importantly it is based upon systems engineering and systems thinking.  The essay contributes a socio-technical attribution chain and field-specific ontology/taxonomy which distinguish user-triggered events from root causes, latent conditions, technical debt, validation failures, governance failures, and attribution bias before assigning responsibility to end users. It systematically defines an ontology inclusive of developer technical debt, organizational debt arising from …

Moral: Multimodal Reasoning For Autonomous Language Models With Sensor-Grounded Spatial Bev Rendering, Ambarish Govindarajulu Kaliamurthi

Master's Theses

Autonomous-driving vision-language models describe scenes fluently but reason poorly about metric, safety-critical spatial relationships because they do not read sensor geometry in a grounded way. This thesis presents MoRAL (Multimodal Reasoning for Autonomous Language Models), a two-stage fine-tuning pipeline that teaches a compact 2-billion-parameter VLM to decode a physics-encoded Bird’s Eye View (BEV) representation – LiDAR distance as color, object class as cluster shape, radar Doppler velocity as directional wedges – and then trains it to reason over that representation for driving decisions. Stage 2 then fine-tunes on 57,696 teacher-generated chain-of-thought examples across eight question types, using Cosmos-Reason2-8B as teacher …

The Zeal Instruction Set Architecture, Joseph A. Gerani

Master's Theses

The Instruction Set Architecture of a CPU (Central Processing Unit) determines what type of instructions the CPU is able to understand, how those instructions are encoded, and what it should output upon receiving those instructions as input. There are currently three popular ISAs meant for the consumer market: x86, RISC-V, and ARM, as well as a fourth that mostly now exists in the server market by the name of Power. One of the most important parts of an ISA is for engineers to be able to understand it and make use of it. If an ISA is too complicated, nobody …

Towards Neural Network Optimization: Addressing Issues With Corrupted Weights Within Models, Nick Najafizadeh

Master's Theses

Neural networks are a recent popular technology inspired from human brains. Much of their popularity arises from how they excel in reasoning and logic, and are generally rather efficient in their tasks. With those strengths, they are frequently used in transportation and business among many other fields. However, neural networks have many factors that can deteriorate their performance, one of the most critical being weight corruption. Therefore, it is of utmost importance to detect and handle them as soon as possible so as to minimize the negative impact on a network’s performance. The optimization of neural networks would be especially …

Pipeline Optimization Of Agentic Llms For Text-To-Sql, Peter Conant

Master's Theses

Current database interfaces limit users’ interaction to those with technical skills, creating timely roadblocks for non-technical professionals. Text-to-SQL aims to simplify database interactions by translating natural language questions into database queries, but long-standing challenges like question understanding, question-schema linking, and SQL generation have held the field back. In the AI era, foundational LLMs prove to be very capable of question understanding SQL, perform well in Schema Linking, Generation, and Evaluation tasks. However the cost to run these model is a hurdle for many organization with low funds and resources. Text-to-SQL solutions often operate across large enterprise size databases with, and …

Analysis Of Electronic Control Unit Optimization On The Performance Of A 150 Cc Motorcycle Engine Using Ethanol-Blended Fuel, Agus Achmad Syaiful, Annisa Bhikuning, Muhammad Rizal Baihaqi, Muhammad Aulia Rafli

Journal of Mechanical Engineering Science and Technology (JMEST)

The use of ethanol-blended fuel in a standard vehicle can reduce combustion quality, which has an impact on decreasing vehicle performance. At the above 20% blend level, it affects vehicle performance and requires adjustments to engine settings or the Electronic Control Unit (ECU) before use on conventional engines. This study investigates the effect of aftermarket ECU settings on the performance of a 150 cc motorcycle operating on a gasoline-ethanol blend. Four fuel variations were tested: Pertalite (P100), revvo 90 (R100), and 30% ethanol blends (PE30 and RE30). This study analyzes the effects of optimizing injection duration and ignition timing settings …

Adaptive Task-Driven Lidar Point Cloud Compression For Autonomous Driving, Su Hyun Kim

Master's Theses

Autonomous-driving systems generate large LiDAR point clouds, but compression can damage the sparse object-support structure needed by 3D detectors even when reconstructions appear visually plausible. This thesis asks whether adaptive LiDAR compression can preserve downstream detection better than uniform compression by allocating more fidelity to detector-relevant regions. The main study builds a mask-aware range-image codec with an encoder-decoder bottleneck, an importance head, and an adaptive quantization variant. It compares this adaptive variant package with a confirmed masked uniform baseline under one fixed RangeDet evaluation surface and one fixed KITTI validation subset. Two supporting studies bound the result: a projection-reconstruction PointPillars …

Development Of Proposed Airworthiness Certification Criteria For Interference-Tolerant Radio Altimeter Systems, Matheus B. Furstenberger

Student Works

Radio altimeters provide height-above-ground information to flight deck displays and multiple safety-critical aircraft systems, however legacy certification standards were not developed for high-power terrestrial wireless services operating in adjacent C-Band spectrum. This study addressed the absence of a consolidated airworthiness certification framework for interference-tolerant radio altimeter systems installed on Title 14 Code of Federal Regulations Part 25 transport category airplanes. An archival research synthesis was conducted using publicly available regulations, proposed and final rules, technical standard orders, advisory circulars, airworthiness directives, industry standards, spectrum-management documents, technical studies, and stakeholder comments. Qualitative content analysis and source triangulation were used to identify …