Engineering Commons^™

Novel Design And Fabrication Of A High-Speed Transient Heat Flux Sensor For Application To Rotating Detonation Engines, Zachary Todd Tallman

Graduate Theses, Dissertations, and Problem Reports (ETD)

Rotating detonation engine (RDE) combustion systems have been a topic of interest in the pressure gain combustion community for their benefits over traditional gas turbine engine combustors. However, cooling requirements for these engines are significantly higher and less predictable than those of non-detonating engines. To understand and quantify the high-speed heat transfer dynamics within an RDE, a novel high-frequency heat flux sensor is presented. This study aims to design a robust, single-sided sensor that can withstand the high temperature and harsh environment of an RDE for extended durations. Screen printing is used to deposit a layered, platinum-yttria-stabilized zirconia (YSZ) film …

In-Plane Shear Stiffness Of Stay-In-Place Forms And Bracing Effects On The Torsional Stability Of Press-Brake-Formed Tub Girders, Ethan L. Host

Graduate Theses, Dissertations, and Problem Reports (ETD)

Press-brake-formed tub girders have welded internal angle bracing that is believed to be necessary for torsional stability under eccentric loading. However, this bracing creates fatigue weld hotspots overtime, which are subject to cracking. This study was performed to assess the torsional behavior of the Valmont U12 press-brake-formed tub girder (PBFTG) under various configurations using finite element analysis (FEA) modeling and experimental laboratory testing. The primary objective was to (1) determine the necessity of various angle bracing throughout the beam, and the effects removing said braces has on the torsional stiffness of the girder and (2) investigate the use of stay-in-place …

A Strategic Infrastructure Improvement Framework For Intermodal Transportation Networks, Ayoub Abusalih

Graduate Theses, Dissertations, and Problem Reports (ETD)

In this research, we propose a novel approach to design infrastructure networks for intermodal freight transportation systems, which incorporates railways, highways, and inland waterways (IWW). The objective of our study is to identify the optimal set of hubs to be built and operated over an extended time, based on the projected domestic cargo demand. Unlike traditional hub location models, our approach introduces hybrid hubs, where hybrid transportation modes are integrated to facilitate cargo handling. This innovative integration enables more efficient intermodal connections, leading to tangible reductions in operating costs, and carbon emissions. Specifically, we propose a mixed integer programming model …

La2nio4+Δ-Based Solid Oxide Electrolysis Cell (Soecs) Electrodes Enhanced With Complex Perovskite Nanocatalyst Processed By Surfactant-Enabled Infiltration, Cole Samuel Klemstine

Graduate Theses, Dissertations, and Problem Reports (ETD)

As the world seeks to reduce its reliance on hydrocarbons, the demand for sustainable hydrogen production methods has become increasingly critical. Hydrogen is a versatile energy carrier that can be produced from various sources, including water, natural gas, and biomass. Replacing the burning of hydrocarbons with hydrogen could significantly reduce greenhouse gas emissions, contributing to global climate goals like those set by the US H2NEW program. The joint technologies of solid oxide fuel and electrolysis cells present the ability to both produce and process clean hydrogen to meet these goals. Development into solid oxide fuel cells has been met with …

A Limb-Speed-Driven Locomotor Control System And Its Ability To Adapt, Emily Marie Herrick

Graduate Theses, Dissertations, and Problem Reports (ETD)

Despite how simple walking may seem, the locomotor control system is structurally and functionally complex. Its hierarchical organization of supraspinal and spinal networks with forward and feedback pathways has many interactions at multiple levels that are dependent on the dynamics of a high-dimensional musculoskeletal system. Having a comprehensive understanding of sensorimotor integration within a healthy locomotor control system is crucial for understanding changes to the system due to age or neurologic disease and developing effective technologies to recover mobility in those populations. In this dissertation, we address persistent gaps in knowledge pertaining to how the nervous system controls locomotion.

In …

Customer Segmentation And Fuel Economy Prediction Using Telemetry Data From Heavy-Duty Trucks, Batishahe Selimi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Heavy-duty trucks constitute only a modest fraction of on-road vehicles, yet their intensive duty cycles and high fuel demands yield a disproportionately large share of transportation fuel use and greenhouse gas emissions. Addressing this imbalance requires data-driven tools that capture the realities of fleet operation and translate complex telemetry into actionable insight.

This dissertation introduces a unified machine-learning framework that operates exclusively on high resolution time-series data collected from fifty-nine diesel trucks deployed across Southern California. It begins by constructing a multi-modal feature space that blends statistical summaries of key engine signals, static vehicle descriptors, and Mel-Frequency Cepstral Coefficients, thereby …

Microplastics Detection, Characterization, And Cytotoxicity Evaluation Via Lab-On-Chip, Liyuan Gong

Open Access Dissertations

Microplastics (MPs) pose a growing challenge to the ecological system, prompting increasing research efforts in diverse directions. Accurate characterization of MPs is essential for understanding their properties, relying on efficient sampling and detection techniques. Additionally, studying the cytotoxic effects of MPs is critical for evaluating their impact on biological systems. Lab-on-chip (LoC) systems offer significant advantages for precise particle manipulation and compatibility with advanced analytical instrumentation, making them valuable for MP detection and characterization. Microfluidic-based on-chip cell-culturing systems provide a controllable, physiologically relevant microenvironment for more realistic in vitro tissue modeling. By leveraging advanced LoC concepts and integrating state-of-the-art machine …

Comprehensively Understanding And Manipulating The Heat Transfer Mechanisms In Next-Generation Battery Materials, Connor Jaymes Dionne

Open Access Dissertations

Rechargeable batteries are paramount to the further development of green energy infrastructure as they allow for energy storage during peak production times, energy distribution during off-peak times, and provide the impetus to transition away from standard combustion engines in the transportation sector. The ability for rechargeable batteries to safely charge and discharge over multiple cycles is key to their successful application and long-term use. Moreover, the growing use of rechargeable batteries necessitates designs utilizing materials that are abundant and accessible to meet the ever-increasing demands required by the green energy and transportation sectors.

To address these needs, we first investigate …

Machine Learning Guided Insights Into Phonon Scattering Mechanisms For Tunable Thermal Transport In Materials From First-Principles, Niraj Bhatt

Open Access Dissertations

As device dimensions shrink in the current era of miniaturization, effective thermal management at the material level has become critical. In ultrasmall device lengths, traditional electronic heat transport becomes severely limited as boundary scattering effects curtail the electronic transport because the electronic mean free paths substantially exceed those of phonons. The resulting high-power- density devices generate thermal hot spots that compromise both performance and long-term reliability. This challenge has intensified the search for materials with superior phonon-mediated heat transport, a key requirement for effective thermal management in next-generation nanoelectronics. Accurately predicting thermal transport properties with near-experimental accuracy is therefore essential. …

Seasonality Of Cyanobacteria And Eukaryotes In Lake Geneva And The Impacts Of Cyanotoxins On Growth Of The Model Ciliate Tetrahymena Pyriformis, Niveen S. Ismail, Paul Seguin, Lola Pricam, Elisabeth M.L. Janssen, Tamar Kohn, Bas W. Ibelings, Anna Carratalá

Engineering: Faculty Publications

Toxic cyanobacteria are likely to be favored by global warming and other human impacts, posing significant threats to aquatic ecosystems. While cyanobacterial blooms in eutrophic lakes are widely investigated, the dynamics of cyanobacteria and the effects of their toxins and bioactive metabolites on the plankton communities in mesotrophic and oligotrophic lakes are less well understood. Here we investigated seasonal dynamics of cyanobacteria, eukaryotic algae and cyanotoxins in oligo-mesotrophic Lake Geneva—the largest and deepest lake in western Europe. High-throughput sequencing of the 16S rRNA genes in 143 samples along a water column revealed that Lake Geneva hosts diverse, co-dominant cyanobacterial genera, …

Pharmacological Or Genetic Inhibition Of Ltcc Promotes Cardiomyocyte Proliferation Through Inhibition Of Calcineurin Activity, Lynn A. C. Devilée, Abou Bakr M. Salama, Jessica M. Miller, Janice D. Reid, Qinghui Ou, Nourhan M. Baraka, Kamal Abou Farraj, Madiha Jamal, Yibing Nong, Todd K. Rosengart, Douglas A. Andres, Jonathan Satin, Tamer M. A. Mohamed, James E. Hudson, Riham R. E. Abouleisa

Markey Cancer Center Faculty Publications

Cardiomyocytes (CMs) lost during ischemic cardiac injury cannot be replaced due to their limited proliferative capacity. Calcium is an important signal transducer that regulates key cellular processes, but its role in regulating CM proliferation is incompletely understood. Here we show a robust pathway for new calcium signaling-based cardiac regenerative strategies. A drug screen targeting proteins involved in CM calcium cycling in human embryonic stem cell-derived cardiac organoids (hCOs) revealed that only the inhibition of L-Type Calcium Channel (LTCC) induced the CM cell cycle. Furthermore, overexpression of Ras-related associated with Diabetes (RRAD), an endogenous inhibitor of LTCC, induced CM cell cycle …

Advances In Magnetic Nanoparticles For Molecular Medicine, Xiaoyue Yang, Sarah E. Kubican, Zhongchao Yi, Sheng Tong

Markey Cancer Center Faculty Publications

Magnetic nanoparticles (MNPs) are highly versatile nanomaterials in nanomedicine, owing to their diverse magnetic properties, which can be tailored through variations in size, shape, composition, and exposure to inductive magnetic fields. Over four decades of research have led to the clinical approval or ongoing trials of several MNP formulations, fueling continued innovation. Beyond traditional applications in drug delivery, imaging, and cancer hyperthermia, MNPs have increasingly advanced into molecular medicine. Under external magnetic fields, MNPs can generate mechano- or thermal stimuli to modulate individual molecules or cells deep within tissue, offering precise, remote control of biological processes at cellular and molecular …

Functional Assessment Of Migration And Adhesion To Quantify Cancer Cell Aggression, Lauren E. Mehanna, James D. Boyd, Chloe G. Walker, Adrianna R. Osborne, Martha E. Grady, Brad J. Berron

Markey Cancer Center Faculty Publications

During epithelial-to-mesenchymal transition (EMT), cancer cells lose their cell–cell adhesion junctions as they become more metastatic, altering cell motility and focal adhesion disassembly associated with increased detachment from the primary tumor and a migratory response into nearby tissue and vasculature. Current in vitro strategies characterizing a cell’s metastatic potential heavily favor quantifying the presence of cell adhesion biomarkers through biochemical analysis; however, mechanical cues such as adhesion and motility directly relate to cell metastatic potential without needing to first identify a cell specific biomarker for a particular type of cancer. This paper presents a comprehensive comparison of two functional metrics …

Review: Dielectric Barrier Discharge Plasma Actuators For In-Flight Applications, Sabeel Saleem Mohammed

Anthós

Dielectric barrier discharge (DBD) is a phenomenon observed when high voltage is passed through a dielectric barrier at high frequencies. Current DBD plasma actuators (PAs) excel at laminar fluid boundary layer control but suffer from limited momentum flux and fluid mechanic inefficiencies. In this article, Mohammed analyzes previous discourse on DBD PAs and offers directions for future research and potential DBD PA applications. Previous work on DBD PAs documented thrust generation at high voltages and frequencies, thrust in varying fluid compositions, and vortex generation. However, certain arrangements hinder flow magnitudes, limiting the use of multiple DBD PAs in close proximity. …

Fault Identification And Localization In Distribution Grids Based On An Attention-Hybrid Graph Neural Network, Xingjian Shan

Theses and Dissertations--Electrical and Computer Engineering

This thesis proposes a multi-task fault diagnosis framework for distribution systems based on Graph Convolutional Networks (GCN) and an enhanced Graph Attention Network (GATv2). By representing the power grid as a graph with electrical features and topological connections, the model simultaneously performs fault type classification and fault location prediction. The architecture incorporates residual connections, multi-head attention, and a Jumping Knowledge module to capture multi-scale structural patterns, while dynamic loss weighting ensures balanced task optimization under noise and sparsity. Experimental results on the IEEE 123-node test feeder demonstrate a fault classification accuracy of 96.43%, and fault localization accuracies of 84.64% (strict), …

Surface Morphology And Moisture Adsorption/Desorption Characteristics Of Hybrid-Dielectric Moisture Sensors, Ronak Ali

Theses and Dissertations--Electrical and Computer Engineering

Relative humidity sensors are used for high-humidity measurement. Moisture sensors, or dew point sensors are used for low-humidity measurement (< 1 ppm_v). The dissertation contains two parts of studies. In the first part, the effect of surface morphology on the response speed of moisture sensors is studied. Moisture sensors using α-Al₂O₃ films as porous dielectric materials deposited by anodic spark deposition are studied. In this part of the study, a variety of small pores have been studied to investigate the response speed of moisture sensors. Three different surface morphologies have been studied using scanning electron microscopy. One …

Measurement Of Moisture Levels In Oils And Lubricants Using A Novel Moisture Sensor, Aaron Swartz

Theses and Dissertations--Electrical and Computer Engineering

It is very challenging to measure moisture levels in oils. There is not a good method to measure it. Using the novel moisture sensor, we tried various methods to measure the moisture levels in oils. The initial trials are to immerse the sensor chip into the oils to see any sensor reading changes with the change of moisture levels in oils. It was observed that the sensor reading was unstable. The idea for immersion of the sensor chip into the oils failed. The last idea is to heat the oil to let all moisture evaporate fully. Before heating, the dew …

Mathematical-Programming Modeling Of Power-Electronics-Based Microgrid Systems, Jack A. Robey

Theses and Dissertations--Electrical and Computer Engineering

The emergence of power-electronics-based microgrid systems is driven by the shift to cleaner energy, transportation electrification, renewable integration, grid modernization through smart grid advancements, and growing demand for energy-efficient solutions. For utilities, these systems present unique opportunities for enhancing grid resilience, improving load management, and enabling distributed energy resource integration. This work presents a modeling and simulation approach for microgrid systems that uses mathematical programming to represent power flow and capture the system dynamics. By solving an optimization problem at each time step, the method enables evaluation of power distribution and system performance under a range of operating conditions, without …

Computing With Photonic Phase Change Memory, David B. Pippen

Theses and Dissertations--Electrical and Computer Engineering

A recent breakthrough in silicon photonics includes the discovery and use of phase changing materials (PCMs). These materials can be programmed to store nonvolatile values, and when a stored value in a PCM cell is read, it changes the amplitude of the read signal, imprinting the value held into the PCM cell on the amplitude of the read signal. This thesis proposes a new approach to using PCM cells not only for photonic memory but also as a substrate to perform multiplications in the photonic domain. The proposed multiplier uses PCM cells to encode amplitude-analog weight values and differing lengths …

Scalable Hypergraph Structure Learning With Diverse Smoothness Priors, Benjamin T. Brown

Theses and Dissertations--Electrical and Computer Engineering

In graph signal processing, learning weighted connections between nodes from signals is a fundamental task when the underlying relationships are unknown. With the extension of graphs to hypergraphs, where edges can connect more than two nodes, graph learning methods have similarly been generalized to hypergraphs. However, the absence of a unified framework for calculating total variation has led to divergent definitions of smoothness and, consequently, differing approaches to hyperedge recovery. This challenge is confronted in this work through generalization of several previously proposed hypergraph total variations, allowing ease of substitution into a vector-based optimization. To this end, a novel hypergraph …

Electromagnetic Integral Equation Methods For High-Order Field Predictions, Jordon N. Blackburn

Theses and Dissertations--Electrical and Computer Engineering

Methods like the Method of Moments (MoM) or the locally-corrected Nyström (LCN) method are employed to discretize and solve electromagnetic integral equations. This process results in large, dense systems of linear equations that must be solved. In many cases, the elements of the system matrix can be computed analytically or approximated with high-order numerical methods. In this thesis, various approaches are presented to improve the accuracy and efficiency of integral equation solutions.

The second chapter derives a modified form of the low-rank matrix approximation algorithm known as the adaptive cross approximation (ACA). The original ACA has been observed to lose …

Lifecycle Carbon Footprint And Sustainability Evaluation Of Dram-Based Processing In Memory Computing Architectures, Samrat Pravin Patel

Theses and Dissertations--Electrical and Computer Engineering

The use of computing technologies has significantly enhanced several aspects of our day-to-day lives. But it has still revealed significant environmental concerns, primarily related to greenhouse gas emissions and energy consumption. Initially, the primary environmental problems associated with computing were energy consumption during device operation. However, with the rapid advancement of technology and increasing computational demands, attention has shifted towards the embodied carbon footprint. This term refers to the total greenhouse gas emissions throughout a product’s lifecycle from the extraction of raw materials to end-of-life processing. It has become increasingly significant in the context of manufacturing integrated circuits (ICs), such …

Afapbp: Aggregate Function Accelerated Parallel Bit-Pattern Computing, Charles Z. Armstrong

Theses and Dissertations--Electrical and Computer Engineering

Classical computing models have proven sufficient for problems of the complexity class ``P", but problems of a higher complexity class like ``NP", ``NP-Hard", etc. have been shown to be more resistant to efficient computation. Quantum Computing is an alternative computing model that specifically targets performing computations within the ``NP" complexity class in close to linear time. However, Quantum Computing has its own set of problems. Methods for dealing with quantum decoherence, error correction, and difficulty in scaling have all inhibited Quantum Computing from becoming a commonly used computational model. This thesis introduces AFAPBP (Aggregate Function Accelerated Parallel Bit Pattern), a …

Scalable Systems And Devices For Wireless Charging Of Electric Vehicles, Donovin D. Lewis

Theses and Dissertations--Electrical and Computer Engineering

The rising adoption of electric vehicles creates new opportunities that are not possible with conventional gas-powered vehicles such as wireless charging of electric vehicles (EV). Wide-scale implementation of wireless charging could result in benefits unique to EVs such as operation without human intervention, improved charging accessibility, and even in-route wireless charging for charge-sustaining or extended driving range operation. As the technology is in the early stages of development, there are many open-ended challenges to tackle including but not limited to coil and systems cost, weight and size, stray field emissions in high-power, high-frequency operation, and dynamic wireless charging system design …

Analysis And Design Optimization Of Electric Machines With Field Intensifying Configuration, Ali Mohammadi

Theses and Dissertations--Electrical and Computer Engineering

The design and optimization of electric machines face increasing demands for efficiency, improved torque density, manufacturability, and effective utilization of materials. Meeting these demands is particularly vital in for example, electric vehicles (EVs) and renewable energy systems, where performance, reliability, and cost are critical. In this dissertation innovative field-intensifying electric machine configurations have been explored, emphasizing advanced topologies, computational modeling, and optimization techniques to advance the state of the art in electric machine design and analysis.

Electric machines with high torque density are essential for many low-speed direct-drive systems, such as wind turbines, in-wheel traction, and industrial automation. This dissertation …

Multi-Objective Design Optimization Of Power Converters For Electric Aircraft Propulsion, Ben Luckett

Theses and Dissertations--Electrical and Computer Engineering

As global focus shifts to the electrification of the aviation sector, the need for high efficiency, lightweight, and reliable electric aircraft propulsion power converter systems has become apparent. These goals can be somewhat conflicting with each other, and a single multi-domain-optimized solution is not guaranteed. The search for a design which presents satisfactory merits becomes a drudge through various trade-off studies which can expend vast quantities of manpower and time. As a remedy to this, design automation allows the process to be computer-assisted. This dissertation presents the core fundamentals for a general multi-objective design optimization framework intended for the design …

Predicting Crises On The African Frontier Stock Markets With Investor Sentiment Indicators: A Machine Learning Approach, David Korsah, Lord Mensah

Journal of International Technology and Information Management

This study examined the predictive ability of machine learning algorithms in identifying crises within African stock markets. The study employed seven distinct machine-learning models, analyzing historical stock prices from eight stock markets, three major sentiment indicators, and the exchange rates of local currencies against the US dollar, with each data spanning from May 1, 2007, to April 1, 2023. Extreme Gradient Boosting (XGBoost) emerged as the most effective algorithm for predicting crises. Historical stock prices and exchange rates were identified as the most critical features for prediction. On the sentiment side, investors’ perceptions of potential volatility on the S&P 500, …

A Conceptual View Of Data For Decision-Oriented Databases: A Knowledge-Driven Approach, Sung-Kwan Kim, Wenjun Wang, Seunghyun Kim

Journal of International Technology and Information Management

Typical database design goes through three levels of data modeling: conceptual modeling, logical modeling, and physical modeling. In particular, conceptual modeling is important since it captures and documents user data requirements. Conceptual modeling serves as a blueprint for designing a database by defining information content to be included in a database. Presently, decision-oriented databases have no well-accepted conceptual modeling approach to apply. While some use conceptual modeling approaches for transaction-oriented databases such as the ER (Entity-Relationship) model, they are not well-suited for decision-oriented databases. It is hard to map from the ER Model to decision-oriented data models. Others attempt to …

Preventive Health Care Information Seeking Behaviors Among Baby Boomers In Taiwan, Alexander N. Chen, Michael J. Rubach, Tracy Suter, Hsin Ke Lu, Mark E. Mcmurtrey

Journal of International Technology and Information Management

Preventive health care is widely acknowledged as one of the most effective ways to reduce medical costs and enhance people's health. Preventive health care information (PHCI) is a crucial component. This study examines the PHCI-seeking behaviors of Taiwanese baby boomers. The study found some support for the idea that the preferred media used influenced the likelihood of Information seeking behavior. People with good health conditions were found to be more likely to seek PHCI, while people with greater health care needs sought out PHCI less frequently. The study examined social influences, which were found to be important. Three different types …

Pedagogy In The Age Of Ai: Exploring Generative Ai For Higher Education, Alison Munsch Phd

Journal of International Technology and Information Management

Generative Artificial Intelligence (AI) presents transformative opportunities for higher education, enabling personalized learning, enhanced student engagement, and efficient pedagogical practices. This tutorial-style article guides educators in integrating generative AI into their classrooms through hands-on activities, practical strategies, and reflective exercises. It explores the capabilities of AI tools such as ChatGPT, their applications across disciplines, and the ethical considerations for their use. By cultivating critical thinking and fostering student readiness for AI-driven futures, this article underscores the transformative potential of generative AI in higher education with an emphasis on the academic areas of business analytics, information systems, and computer science.