Engineering Commons^™

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 …

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 …

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 …

Modeling For You: A Personalized Approach To Residential Energy Simulation And Distributional Reinforcement Learning, Nestor Gabriel Pereira

Electrical and Computer Engineering ETDs

The growing complexity and uncertainty of residential energy use, driven by electric

vehicles and renewable technologies, demand more intelligent and robust

management systems. Traditional methods often fail when faced with unpredictable

electricity prices and user behavior. This dissertation addresses this gap by presenting

a novel personalized framework combining detailed household energy modeling with

a risk-aware reinforcement learning agent for appliance scheduling.

The first contribution is a probabilistic, bottom-up simulation model that captures

the interdependent behaviors of occupants, appliances, and electric vehicles to

generate realistic, high-fidelity load profiles. The second contribution is a lightweight,

tabular Distributional Q-Learning (D-QL) algorithm that schedules …

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.

Rthermal: Gate Level Power And Thermal Simulation For 3d-Stacked Chips, Peter Xiong

Master's Theses

As the number of transistors in modern processors increases, heat dissipation has become a major bottleneck to scalability. The use of 3D stacking further intensifies this problem, as heat from multiple layers can accumulate vertically. These challenges create a growing need for tools that can accurately and efficiently simulate the thermal behavior of 3D chips during design and validation. Several existing tools model thermal behavior for 3D-stacked chips and can simulate average heat over large spatial regions or long time intervals. However, when heat is concentrated in a small area or over a short time window, such models can miss …

Assessment Of Anaerobic Co-Digestion Of High Strength Organic Feedstocks Diverted From Landfills, Sumaiya Sharmin

Electronic Theses and Dissertations

The increasing generation of high-strength organic wastes such as food waste and fats, oils, and grease (FOG) presents challenges for landfill capacity and waste management. Anaerobic co-digestion offers a sustainable alternative by converting these wastes into renewable energy and nutrient-rich digestate. This study evaluated the co-digestion performance of single fruit waste residuals and mixed food waste with wastewater sludge to identify substrate combinations that maximize methane production while maintaining process stability. Laboratory-scale batch experiments were conducted under mesophilic conditions using thickened waste activated sludge (TWAS) with varying proportions of food waste and co-substrates, including seaweed, aquatic weed, grease trap waste, …

System Design And Validation Of Radio Astronomy Phased Arrays, Rebecca Shiu Haymore

Theses and Dissertations

Modern radio astronomy instruments require a wide field of view and high sensitivity. To this effect, BYU and Cornell University have developed the Advanced L-band Phased Array Camera for Astronomy (ALPACA), a fully cryogenic 69 dual-pol dipole array that produces 80 beams on the sky with 305 MHz instantaneous bandwidth centered on 1500 MHz. Integration testing has demonstrated proper beamforming and calibration, and ALPACA has been commissioned as an all-sky monitor to search for bright transients. Commissioning testing for ALPACA measured an element system noise temperature of 24 K and a beamformed system noise temperature of 17 K, making ALPACA …

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 …

Early Failure Detection In Web Navigation Agents Via Closed Sequential Pattern Mining, Sergio Talavera

Master's Theses

LLM-based web navigation agents fail on the majority of tasks while consuming substantial computational resources before failure becomes apparent. This thesis investigates whether closed sequential pattern mining on the first K steps of agent execution traces can predict task failure early enough to enable meaningful computational savings with interpretable justification. We develop a two-phase system: an offline pipeline that symbolizes agent traces, extracts K-step prefixes, mines closed patterns via BIDE+, and ranks them by failure precision; and an online detector that matches live executions against the resulting pattern library. We evaluate on 1,544 MiniWoB++ traces across three open-weight language models …

Data Augmentation For Vision-Language-Action Models: Bridging Vision And Language, Miaosen Zhou

Master's Theses

This thesis focuses on real-time task execution and object detection for autonomous robots through dataset augmentation. We propose a data augmentation approach to address dataset imbalance in Vision-Language-Action (VLA) models across both image and text modalities during the fine-tuning process. The proposed method takes an image as input and generates a structured textual description using a prompt engineering strategy to augment the textual input. The generated augmented text includes key elements such as the task goal, scene description, reasoning, and execution plan, along with other relevant contextual information. This enriched representation improves the quality of the training data and supports …

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 …

Prepration And Characterization Of Alginate Biocomposite Films From Natural Seaweed Containing Glycerol And Silica, Bahareh Ebrahimi Mojaveri

Master's Theses

This study focuses on the development of sodium alginate, a seaweed-derived biopolymer, as a sustainable alternative to conventional food packaging films. The alginate is extracted from natural brown seaweed with a yield of 31% and is formed into alginate films by the solution casting method. This study discusses the alginate extraction and film formation techniques as well as the conditions that affect film properties. Additionally, it explores using composite formulations to enhance alginate properties through additives such as glycerol and silica. Glycerol, tested at different concentrations (15, 25, and 50 wt.%), works as a plasticizer to enhance the flexibility of …

Object Avoidance Onboard An Autonomous Underwater Vehicle In Support Of Geomagnetic Based Navigation System, Eric Benavidez

Electronic Theses and Dissertations

The objective of this thesis was to collect and analyze magnetic field data in the vicinity of the Mercy, Tracey, and Jay Scutti with an autonomous underwater vehicle (AUV) and a forward mounted magnetometer. The collected data was used to develop geomagnetic contour maps and magnetic thresholds of known anomalies to compare the results with validated sources such as NOAA.

In addition, this collected data was used to develop a Gazebo simulation which accurately modeled the magnetic field data and ocean effects of the Fort Lauderdale Shipwreck Trail. This Gazebo simulation allowed for proper testing and refinement of object avoidance …

Evaluation Of Microwave Treatment Of Pfos-Laden Granular Activated Carbon, Rachel Melo Fonseca

Electronic Theses and Dissertations

This study investigated the microwave treatment as a potential regeneration approach for PFOS-laden granular activated carbon (GAC). PFOS was used as a model legacy PFAS, and calcium was selected to examine how inorganic constituents may influence PFAS loading and fluorine behavior during treatment. Microwave temperature profiling showed that GAC temperatures increased with treatment time and power level, reaching approximately 400-950°C. Selected microwave conditions reduced PFOS-derived extractable organic fluorine (EOF), with apparent EOF reduction increasing from 65.5% after 1 min to 96.8% after 4 min. Calcium increased PFOS-derived EOF loading before microwave treatment but did not show a consistent effect on …

Radiation Effects On The Amd Versal Running An Automatic Modulation Classification Model, Allan D. Howe

Theses and Dissertations

With the recent increase of interest into artificial intelligence (AI), graphics processing units (GPUs) have been used as the main hardware architecture for AI computation. Because of their high power consumption and large size, it is necessary to consider other architectures to perform AI computing in outer-space where size, weight, power, and cost (SWaP-C) are tightly constrained. One such architecture is the Advanced Micro Devices (AMD) Versal Adaptive Compute Acceleration Platform (ACAP), which can achieve acceptable AI throughput at a lower power and size compared to a GPU. As the Versal ACAP gets used in space applications, it is necessary …

Equivocation Analysis Across Continuous And Discrete Memoryless Channels, Md Munibun Billah

Theses and Dissertations

Physical-layer security uses the noise already present in the channel to keep a message secret without making any assumption about the eavesdropper's computing power. In Wyner's wiretap channel model, coset coding uses randomness to map the message to many codewords and protects against information leakage from an active eavesdropper. The secrecy provided by such codes is measured by their equivocation, which is the eavesdropper's remaining uncertainty about the message after she observes her channel. So computing equivocation is an important aspect of analyzing the wiretap channel model. Many channels of practical interest have no closed-form expression for equivocation, and exact …

Experimental Evaluation Of Membranes In The Recovery Of Hydrogen From Serpentinization, Rafael Dos Santos

LSU Master's Theses

Natural hydrogen generated through serpentinization reactions has emerged as a promising low-carbon energy resource. However, serpentinization-derived gas streams commonly contain methane (CH₄) and carbon dioxide (CO₂), requiring purification before hydrogen can be utilized in industrial applications. Membrane-based gas separation technologies offer a potentially cost-effective solution for hydrogen recovery; however, to the best of the author's knowledge, no previous studies have specifically investigated their application to serpentinization-derived gas streams.

This work evaluates the performance of two commercial polymeric membrane modules (Evonik and Generon) and one palladium-copper (Pd-Cu) membrane module (Okaya) for hydrogen recovery from gas compositions representative of serpentinization environments. An …

Effect Of Solid Particle Size And Density On Incipient Motion In A Turbulent Boundary Layer, Robert Bryan

Doctoral Dissertations and Master's Theses

Wind-blown sand and other instances of solid particles mobilized and suspended in gaseous turbulent boundary layers (TBLs) are seen in a wide variety of engineering contexts. An experimental framework was developed to study the incipient particle motion driven by external forcing within a turbulent boundary layer, which is provided by an airfoil section oscillating in the free-steam flow, resulting in a periodic disturbance in the near-wall region through production of synthetic large-scale structures at a fixed frequency. The incoming unsteady carrier-phase eddies were measured with a hot-film sensor upstream of a particle bed, and the particle motion was captured by …

Identifying Failure Behaviors In Stereolithography From Varied Print Orientations, Kevin Veltre

Theses and Dissertations

Stereolithography (SLA) is an additive manufacturing (AM) technique that utilizes photopolymerization to create three-dimensional shapes by strategically printing layers of material. Printing parameters such as layer orientation, print resolution and post cure can affect a specimen’s homogeneity, longevity and mechanical characteristics. Because of this variability, print parameters must be carefully considered when designing products and print processes for desired components, as manufacturers often fail to include all relevant print settings when advertising mechanical properties. For this study, 130 SLA-printed specimens were created with 100-micron print layer thickness and print orientations varying between 0 and 90, including intermediate orientations, to observe …

Privacy-Preserving Intrusion Detection For The Internet Of Medical Things Using Ensemble And Federated Learning, Theyab Alsolami

Electronic Theses and Dissertations

The rapid proliferation of the Internet of Medical Things (IoMT) has transformed healthcare by enabling continuous monitoring, intelligent diagnostics, and data-driven clinical decision-making. However, this increased connectivity has significantly expanded the attack surface of healthcare systems, exposing sensitive patient data and critical medical devices to cyber threats such as intrusion and data exfiltration attacks. Ensuring both strong security and strict privacy preservation in IoMT environments remains a fundamental and unresolved challenge.

This dissertation investigates the design and evaluation of robust and privacy-preserving intrusion detection systems (IDS) for IoMT networks using advanced machine learning techniques. The research first examines the effectiveness …

Impact Of Asphalt Binder Chemical Composition On The Performance Of Asphalt Mixture., Sagar Parajuli

LSU Master's Theses

Asphalt binder is composed of four chemical fractions, namely, saturates, aromatics, resins, and asphaltenes (SARA). Binders with the same performance grade (PG) can exhibit different chemical compositions due to variability in crude oil sources and refining processes. The objective of this study was to evaluate how such chemical variations influence the mechanical performance of asphalt mixtures at high, intermediate and low temperatures.

Eighteen 12.5-mm nominal Maximum Aggregate Size mixtures were designed using two aggregate types (limestone and gravel), and three binder grades (PG 67-22, PG 70-22m and PG 76-22m), each from three different sources with varying chemical fractions. A suite …

Explainable Machine Learning For Biomedical Diagnostics: Optical Imaging And Eeg Signal Analysis, Fozia Rajbdad

LSU Doctoral Dissertations

The growing convenience of complex biomedical data begins new roads for better disease detection and functional identification via artificial intelligence (AI). Nevertheless, conventional analysis methods often rely on basic metrics that drop sensitive biotic differences, and various AI systems are difficult to infer, limiting their clinical reliability and practical use. There is a growing need for explainable, physiologically relevant computational models that can extract key biomarkers from diverse biomedical data sources. This dissertation addresses this problem by obtaining explainable machine learning and deep learning procedures for studying biomedical signals and optical imaging data.

This dissertation is divided into two parts; …

Characterization Of Various Corrosion-Resistant Rebars Embedded In Concrete After 20 Years Of Exposure, Samantha Mavrak

Electronic Theses and Dissertations

In aggressive marine environments, the deterioration of reinforced concrete structures is primarily caused by chloride-induced corrosion of embedded carbon steel reinforcement, resulting in concrete cracking, spalling, and costly maintenance or premature replacement. Corrosion-resistant reinforcement has been developed to mitigate these effects; however, long-term field performance data remain limited. This study evaluates the long-term corrosion performance of several corrosion-resistant rebars embedded in simulated deck slab concrete specimens following approximately 20 years of chloride exposure.

Concrete specimens containing 304SS, 316SS, and 2304 duplex SS, two types of clad reinforcement (316SS with carbon steel core), and an intermediate alloy with 12% Cr were …

Enhancement Of A Copolyester’S Impact Resistance Via Inorganic Reinforcement, David Felipe Gonzalez

Electronic Theses and Dissertations

Thermoplastic copolyester elastomers (TPEEs) are widely used in engineering applications because of their flexibility, toughness, and chemical resistance. However, prolonged exposure to marine environments can reduce their mechanical performance through moisture-induced degradation. This research investigated the use of titanium dioxide (TiO2) nanoparticles and APTES-functionalized TiO2 nanoparticles to improve the mechanical, thermal, and environmental durability of Hytrel 5556. Nanocomposites containing 1 wt.% and 2 wt.% TiO2 were fabricated through melt blending and compression molding. Mechanical properties were evaluated through tensile, compression, flexural, and impact testing, while thermal behavior was characterized using differential scanning calorimetry (DSC). Nanoparticle dispersion was examined using scanning …

A Reduced-Order Framework For Stochastic Criticality Estimation In Granular Energetic Materials, Philip T. Melton

LSU Master's Theses

Granular energetic materials (EMs) exhibit stochastic shock initiation because pore collapse, frictional dissipation, and localized thermal activation depend on microstructural descriptors that vary between nominally identical samples. Fully resolved mesoscale and atomistic calculations can represent these mechanisms, but their computational cost limits direct ensemble evaluation of microstructure-conditioned criticality thresholds. This thesis introduces a reduced-order framework for stochastic criticality estimation in granular EMs by coupling five explicitly defined model components: first, a one-dimensional steady compaction-shock model that maps initial solid volume fraction and shock pressure to a bulk mass-specific dissipated-work budget; second, an SEM/synthetic-image segmentation workflow that extracts pore area, perimeter, …