Engineering Commons^™

Towards Application-Driven Optimal Memory And Storage Management, Venkata Naga Prajwal Challa

Computer Science and Engineering Dissertations

Modern computing systems increasingly run on diverse hardware platforms and support applications with widely different access patterns, performance goals, and data lifecycles. In this setting, traditional one-size-fits-all approaches to memory and storage management are often inefficient because they apply fixed policies regardless of application behavior, workload context, or hardware asymmetry. Such generic designs can lead to unnecessary data movement, wasted bandwidth, excessive rewriting, poor resource utilization, and degraded user-perceived performance. This dissertation is motivated by the view that optimal memory and storage management should be application-driven: instead of treating all data uniformly, systems should adapt their decisions to how applications …

Development Of Multimodal Measurements And Analysis For Early Detection Of Alzheimer’S Disease, Fiza Saeed

Bioengineering Dissertations

Alzheimer's disease (AD) is the leading cause of dementia, and existing diagnostic methods such as PET scans, cerebrospinal fluid sampling and biomarker quantification, and gene sequencing are all either invasive, costly, or not sensitive enough for early detection. This dissertation introduces three different studies that develop a novel multimodal, non-invasive approach to diagnosing AD at its early stages by combining broad band near infrared spectroscopy (bbNIRS) and electroencephalography (EEG) technologies.

The first study showed cerebrovascular-cerebrospinal fluid coupling (CBV-CSF), which is measured by using 2-channel bbNIRS as an indicator of brain aging and early AD. Linear correlations between total blood (Δ[HbT]) …

Autonomous Uav Mission Planning Under Threat Using Model Predictive Control With Proportional-Navigation Pursuers, Mehmet B. Ozcelik

Mechanical and Aerospace Engineering Theses

Autonomous unmanned aerial vehicles (UAVs) operating in contested environments must

complete mission objectives while avoiding restricted regions, radar exposure, and pos-

sible interception. This thesis develops a MATLAB-based simulation framework for

two-dimensional UAV mission planning under threat using model predictive control and

proportional-navigation chasers. The mission requires the UAV to travel from a start

location to a goal while visiting required checkpoints and avoiding no-fly zones and radar

regions. A chaser attempts to intercept the UAV using either a basic pure-pursuit-style

law or a proportional-navigation guidance law.

The framework integrates environment generation, augmented visibility-graph rout-

ing, waypoint management, UAV kinematic …

Llm-Driven Closed-Loop Uav Control With Obstacle-Aware Model Predictive Control, Halimcan Yasar

Mechanical and Aerospace Engineering Theses

This thesis presents a closed-loop control architecture for uncrewed aerial vehicles (UAVs) in which a large language model (LLM) serves as a high-level decision module operating over a persistent, metric 3D world model.

Rather than generating low-level commands or open-loop plans, the LLM selects one parameterized maneuver per decision step from a small, verified library of flight primitives conditioned on a structured representation of the drone state, tracked object positions, and mission specification.

Translational motion is executed by a planar model predictive controller (MPC) with soft obstacle avoidance, using obstacle hypotheses provided by the LLM, so that safety-critical constraint handling …

Buckling Analysis Of Auxetic Composite Laminates And Optimal Design Using Lamination Parameters And Machine Learning, Hans Bendon Maria Tamil Selvan

Mechanical and Aerospace Engineering Theses

Composite materials are widely used as structural panels in aerospace, automotive, and civil engineering applications, where buckling is often a critical failure mode. This thesis focuses on the analysis and design of composite laminates that maximize buckling performance under prescribed stiffness and thickness constraints.

The first part of the study investigates the buckling behavior of auxetic laminates, which exhibit a negative Poisson's ratio. While previous studies suggest that auxetic laminates can achieve higher critical buckling loads than non-auxetic laminates under simply supported boundary conditions with lateral restraint, the influence of other boundary conditions and plate aspect ratios has not been …

Sewer Pipe Condition Assessment Using An Ensemble Machine Learning Framework For Infrastructure Decision Support, Mahnaz Rouhi

Civil Engineering Dissertations

Aging wastewater infrastructure presents significant challenges for municipalities across the United States, with many sewer networks approaching or exceeding their design life. Conventional inspection methods, such as closed-circuit television (CCTV), are limited by subjectivity, cost, and inefficiency. To address these challenges, this study develops an ensemble machine learning framework for assessing the structural condition of sewer pipelines using inspection records enriched with geospatial attributes.

The primary objective of this research is to enhance predictive accuracy, interpretability, and decision-support for risk-based asset management. The scope of the study encompasses 4,802 CCTV inspection records from Dallas, TX, and Tampa, FL, integrating physical, …

Videoscoop: A Non-Traditional, Domain-Independent Framework For Video Analysis, Umme Hafsa Billah

Computer Science and Engineering Dissertations

Due to the proliferation of cameras in handheld devices and the widespread use of CCTV, images and videos have become a preferred alternative for capturing and disseminating information. Automated analysis for understanding image or video contents (e.g., objects, activities, backgrounds, situations of interest, etc.) is critical for many applications such as Civic Monitoring, Surveillance (in general), monitoring activities in Assisted Living environments, and many more. Image and Video Analysis (IVA) research has been ongoing for several decades, resulting in numerous techniques for algorithmically analyzing and understanding image and video contents.

Image Analysis (IA) has advanced in several areas, including object …

Deep Learning For Wireless Communications, Swarada Ajit Kulkarni

Electrical Engineering Dissertations

The rapid evolution of wireless communication imposes stringent requirements for ultra-reliable, low-latency transmission in dynamic, interference-prone environments. Traditional model-driven signal processing struggles to adapt to nonlinear hardware effects, time-varying channels, and complex interference patterns. Deep learning (DL) offers a transformative, data-driven alternative, enabling end-to-end optimization and robust adaptation under uncertain propagation conditions.

This dissertation investigates deep learning architectures for intelligent and resilient wireless communication through three complementary contributions. The first introduces a Vision Transformer (ViT)-based modulation classification framework that leverages self-attention to capture local and global dependencies in spectrogram representations of Quadrature Amplitude Modulation (QAM) signals. The ViT achieves superior …

Generative Imaging For Computational Pathology, Md Jillur Rahman Saurav

Computer Science and Engineering Dissertations

Hematoxylin and eosin (H&E) staining remains central to cancer diagnosis, providing morphological information essential for pathological assessment. Immunohistochemistry (IHC) and newer multiplexed imaging technologies complement H&E by revealing molecular information critical for accurate tumor subtyping and treatment decisions. In practice, however, H&E and IHC are obtained from different consecutive sections that are not spatially aligned, comprehensive multiplexed panels are expensive and tissue-consumptive, and not all stains are available at every clinical site, limiting comprehensive molecular profiling and the full diagnostic potential of these technologies in clinical practice. This dissertation addresses these gaps through three complementary generative deep learning studies in …

Computational Study Of Rotating Detonation Combustors, Aditya Balasubramaniam

Mechanical and Aerospace Engineering Theses

Rotating detonation combustors (RDCs) are pressure-gain combustion devices that sustain one or more continuously rotating detonation waves, offering potential thermodynamic and performance advantages over conventional deflagration-based systems. Their behavior depends strongly on combustor geometry and operating conditions. Understanding these effects is therefore essential for the design and optimization of practical RDCs. Accordingly, this thesis numerically investigates annular RDCs with two primary objectives: (1) to evaluate the effects of propellant mass flux and (2) to assess the influence of annular width on detonation-wave dynamics and combustor performance.

A finite-volume framework is used to solve the compressible reactive Euler equations with hydrogen–air …

Scalable Quantum Network Routing Through Reinforcement Learning And Resource Optimization, Tasdiqul Islam

Computer Science and Engineering Dissertations

Long-distance quantum communication depends on distributing high-delity entanglement across quantum repeaters. Entangled states are fragile: they decohere in memory, are consumed when used, and lose delity after each swap. Quantum routing therefore diers from classical routing: an algorithm must decide not only the path, but when to generate, store, swap, and consume entanglement before they lose their usefulness. This dissertation studies scalable resource allocation and routing for quantum networks under delity, memory, and concurrency constraints. It rst addresses re- peater deployment with heuristics that nd near-optimal locations while cutting com- putation from days to seconds versus integer linear programming (ILP). …

Early Detection And Objective Assessment Of Neonatal Hypoxic-Ischemic Encephalopathy Severity, Soheila Norasteh

Bioengineering Dissertations

Hypoxic–ischemic encephalopathy (HIE) is a neonatal brain injury caused by reduced oxygen and blood flow to the brain around the time of birth. It remains a major cause of neonatal mortality and long-term neurodevelopmental impairment worldwide. Therapeutic hypothermia is the standard treatment for moderate-to severe HIE and improves outcomes when initiated within the first six hours of life. Therefore, accurate assessment of injury severity during this period is essential. Cur rently, HIE severity is determined primarily through neurological examination and classified as mild, moderate, or severe. However, these examinations are subjective, cannot provide continuous monitoring of brain function, and may …

Novel Methods For Environmental Fluoride Measurement, Cable Warren

Chemistry & Biochemistry Dissertations

Fluoride analysis has been an important focus of analytical analysis for many years and will continue to be so going forward. Today, fluorinated compounds, specifically per/polyfluoroalkyl substances (PFAS), better known as “forever chemicals” have captured the moment and are the subject of vast research and regulation. Under this context, I have researched new methods of fluoride separation and concentration in complex media as well as a novel method of PFAS destruction and total organic fluorine analysis for screening of PFAS in aqueous samples. Through research and work on micro-scale detection methods, an understanding of the state of the art and …

Development Of A Hypersonic Aerodynamic Analysis Methodology For Conceptual Design, Stephen Atkins

Mechanical and Aerospace Engineering Theses

This research promotes the advancement of the Aerospace Vehicle Design Synthesis (AVDS) system through the development of a low order numerical hypersonic aerodynamic analysis methodology. The AVDS methodology outlines how to utilize disciplinary tools and relies on the careful selection or development of those tools to carry out the aerospace vehicle sizing and evaluation processes. An overview of the aerodynamic analysis process from both industrial and academic perspectives is presented to provide context for the present work. The different philosophies of design are discussed insofar as they dictate how aerodynamic tools are used in the design process. Next, a literature …

Application Of Matlab Simulation For Quantum Wells And Absorption Modelling, Mohamed Nur

Electrical Engineering Theses

The Quantum-Well User Entered Simulation Tool (QUEST), originally developed at the University of Texas at Arlington in 2005, is a simulation program built in MATLAB for computing energy eigenvalues and wavefunctions in user-defined semiconductor quantum well structures. This thesis presents a new revision and extension of QUEST with three primary contributions: compatibility updates to the existing MATLAB codebase, intersubband absorption modelling, and a redesigned graphical user interface for ease-of-use in testing.

The modernization effort for this program addresses incompatibilities introduced by changes to the MATLAB runtime environment since QUEST’s original release in 2005, including corrections to the self-consistent Schrödinger-Poisson solver …

Strain-Induced Nonvolatile Domain Switching And Tunable Elastic Modulus In Ba1-Xsrxtio3 Membrane By Phase-Field Simulation., Laveeza Ahmad

Material Science and Engineering Dissertations

Ferroelectrics underpin a broad spectrum of technological applications due to its switchable ferroelectric polarization and the associated electro-mechanical responses under electrical, optical, thermal, and mechanical stimuli. Recent advancement in membrane technology offers new opportunities to tune ferroelectric polarizations via mechanical strains at relatively large magnitude and scale. However, its influence on the tunability of mechanical responses of the membrane remains underexplored. Herein, we developed a phase-field model for free-standing Ba_1-xSr_xTiO₃ ferroelectric membranes with stress-free boundary conditions on top/bottom surfaces and achieved strain-induced nonvolatile ferroelectric domain switching in the membrane. It is discovered that a …

Ai Data Center Dynamic Load Effects On Current Transformer Saturation, Sergio A. Hernandez

Electrical Engineering Theses

AI data centers can produce rapid changes in electrical demand that may influence current transformer performance during faults. This study evaluates the effect of an AI data center transient on CT saturation during single line-to-ground faults using a 400 V, 60 Hz grid connected inverter model in MATLAB/Simulink. The normal condition transient produced a maximum RMS current rate of approximately 211 A/ms, which was used along with the maximum power condition to define fault inception cases. A MATLAB time-domain CT model then swept the fault current DC offset coefficient to determine the minimum offset required for CT saturation. The calculated …

Experimental Thermal Characterization And Comparison Of Direct Liquid Cooling And Air Cooling For A High-Density Gpu Server Thermal Test Vehicle, Oluwagbolahan Esan

Mechanical and Aerospace Engineering Theses

As the power density of artificial intelligence (AI) and high-performance computing (HPC) servers escalates, air cooling is approaching fundamental scaling limits set by air's low convective heat transfer coefficient and rising parasitic fan power. This thesis presents an experimental comparison of direct-to-chip liquid cooling and air cooling for a high-density GPU server, using a Thermal Test Vehicle (TTV) that emulates the device layout and power-density regime of an 8-GPU SXM5-class baseboard (eight emulated GPU blocks and four NVLink Switch modules). The liquid configuration was tested at 8.8 kW (8.0 kW GPU, 800 W switch) across three Coolant Distribution Unit (CDU) …

End-To-End Development And Experimental Validation Of A 1/10-Scale Autonomous Vehicle, Rikkin Pankaj Panchal

Electrical Engineering Theses

Autonomous vehicle development demands vast resources, making scaled down platforms a critical alternative for solving core algorithmic challenges. The primary contribution of this thesis is the end to end development and validation of a complete real time autonomous driving pipeline deployed on a one tenth scale vehicle. To streamline platform development, an AI assisted annotation framework automates dataset generation, significantly reducing manual labor while improving training data quality. The system perception stack features a reinforcement learning guided online multi camera calibration framework that enables adaptive surround view stitching without the need for offline recalibration. This is paired with robust lane …

Deterministic Black-Box Context-Free Grammar Inference: Scaling From Small To Big Languages, Mohammad Rifat Arefin

Computer Science and Engineering Dissertations

Context-free grammars are essential for a number of software engineering tasks like program understanding, debugging, and grammar-based testing. However, formal language descriptions (i.e. grammars) are often unavailable, outdated, or inaccessible because parsers are closed-source or cannot be instrumented. Black-box grammar inference addresses this gap using only valid sample programs and parser acceptance decisions. The problem is challenging because finite samples rarely exercise all language features or their combinations, while the inference process cannot inspect the parser’s internal representation of syntax. This dissertation develops deterministic techniques for black-box context-free grammar inference. The first tool, TreeVada introduces the structural assumption that balanced …

Cross-Layer Supervisory Control For Low-Altitude Uav Swarm Networks, Nitin Singh Rathore

Computer Science and Engineering Theses

Low-altitude unmanned aerial vehicle (UAV) swarms are increasingly used in applications such as aerial sensing, disaster response, and communication support, where reliable operation under dynamic and uncertain conditions is essential. In these environments, performance degradation arises from multiple sources, including external disturbances, sensing uncertainty, and communication impairments. Although these effects originate from different layers of the system, such as dynamics, observation, and networking, they often manifest as similar tracking or coordination errors. Conventional control approaches, which rely primarily on error-driven feedback, do not explicitly account for the underlying cause of these deviations, limiting their effectiveness in multi-agent settings. This thesis …

Effects Of Metals On Persulfate Activation For The Decomposition Of Pfas, Malu Deav Devadasan

Civil Engineering Dissertations

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants widely used in industrial and consumer products due to their unique physicochemical properties. Their resistance to degradation, potential for bioaccumulation, and associated adverse health effects have prompted increasing regulatory attention, including the establishment of drinking water standards for six PFAS compounds by the U.S. Environmental Protection Agency in 2024.

Current PFAS treatment technologies are often energy-intensive and costly or generate secondary waste streams requiring further management. Meanwhile, this research investigated transition metal-catalyzed advanced oxidation processes for PFAS decomposition in water under ambient conditions. Previous studies demonstrated effective degradation of perfluorocarboxylic acids …

Gaussian Process Regression–Based Uncertainty Quantification For Unmanned Aircraft System Traffic Management And Advanced Air Mobility Applications, Aakarshan Khanal

Mechanical and Aerospace Engineering Dissertations

Uncertainty quantification has gained significant attention in recent years as a research area in dynamical systems. Mathematical representations of the physical system, combined with an understanding of model uncertainties, enable the propagation of uncertainty in temporal space, which allows us to make informed decisions. However, what if the true dynamics of the system is unknown or too complex to define explicitly? In such cases, the system’s behavior can instead be inferred or learned from observed input–output data rather than from an analytical or physics-based model. To this end, this dissertation focuses on developing a data-driven framework for nonparametric dynamics modeling, …

Anaerobic Digestion Of Food Waste Components: Modeling Biogas Production, Opeyemi E. Adelegan

Civil Engineering Dissertations

Food waste constitutes the single largest component of municipal solid waste landfilled in the United States — approximately 22% of 292.4 million tons generated in 2018 — and its anaerobic decomposition releases methane, a greenhouse gas with global warming potential approximately 27–30 times that of carbon dioxide over a 100-year horizon (IPCC, 2021). Anaerobic digestion (AD) offers an alternative management pathway that recovers energy and produces nutrient-rich digestate, but AD performance varies by as much as five-fold across food waste streams (130–630 m³ CH₄ per Mg VS added), and existing predictive tools either treat food waste as a …

Virtual Process Modeling Of Metal Additive Manufacturing Basedon Direct Energy Deposition In-Situ Failure, Jachin J. Ramirez

2025 Fall Honors Capstones Projects - Archive

This study builds a mesoscale finite element simulation to examine how internal stresses form during additive metal manufacturing using directed energy deposition. The goal is to track how heat and stress develop layer by layer and determine where a failure criterion could appear during the print. The model uses temperature-dependent material properties for Inconel 718 and a moving heat source defined with custom G-code.

Thermal results are mapped into a mechanical simulation to watch stress accumulate as new layers are added. Different scan paths were tested to determine whether varying heat exposure could reduce the extent of a region exceeding …

Power Solutions For Large Loads: Mastering Electrical Supply For New Industrial Facilities, Chris Boyer, William Bourgeois, Skyler Bryant

Mavs Open Press Open Educational Resources - Archive

The next 25 years will see unprecedented growth in U.S. electricity demand, driven primarily by data centers for AI and industrial electrification. This surge presents unique challenges for power generation, especially for large loads requiring hundreds of megawatts to gigawatts from a single location. Conventional grid expansion is inadequate, prompting the need for innovative, flexible, and sustainable solutions. This book explores the opportunities, challenges, and hybrid generation strategies to support the evolving landscape of large-scale electric loads.

Patent Searching With Uspto, Derwent Innovation And Lens.Org, Ibis Anette Moreno-Lozano

Day Family Research Lab Workshop Series

No abstract provided.

Performance Of Adaptive Wingtips On A Tailless Supersonic Business Jet, Khushi Piparava

2025 Fall Honors Capstones Projects - Archive

The growing interest in supersonic business travel has renewed focus on efficient, low-drag configurations that can achieve high performance while maintaining stability and structural integrity. This research investigates the aerodynamic and structural implications of adaptive folding wingtips on a tailless supersonic business jet (SBJ) concept designed under the SkyBreaker senior design program. Using a conceptual aerodynamic model based on linearized supersonic theory, the Polhamus leading-edge suction analogy, and an empirical compression-lift correlation, the study evaluates how varying wingtip droop angles influence lift, drag, lift-to-drag ratio (L/D), and static stability. The analysis was performed parametrically in MATLAB, using geometry inputs derived …

Turboindex: Making A Page-Based Db Index Both Memory-Space And Disk-I/O Efficient, Sujit Maharjan, Shuaihua Zhao, Song Jiang

Computer Science and Engineering Faculty Publications - Archive

Traditional Database (DB) systems use a DB buffer, a page-based cache management system, to load data and indexes from block storage devices into byte-addressable main memory. However, this approach is inefficient in terms of space and I/O when key-value pair sizes are significantly smaller than the page size. Inserting a single key-value pair results in reading and writing an entire page, consuming a full page's worth of memory in the buffer. Moreover, the entire page is immediately loaded even when just a single key-value pair is inserted into the page. Also, an infrequently accessed page is likely to be evicted …

Designing And Writing Effective Data Management Plans For Grant Proposals, Rubab Shahzad, Ibis Anette Moreno-Lozano

Day Family Research Lab Workshop Series

Fundamentals of research data management and how to create effective Data Management Plans (DMPs).