Engineering Commons^™

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 …

Characterization Of The Solid-State Bonding For Simulated Charge And Seam Welds In The Porthole Die Extrusion Process, Randall L. Bowers

Theses and Dissertations--Chemical and Materials Engineering

The isothermal (ISO-T) compression configuration is ideal for utilizing as a material input of flow stress at temperature and strain rate in models of the porthole die extrusion process due to the isothermal nature of the test. Micro-tensile testing was conducted to validate the solid-state welding integrity of the ISO-T samples at various temperatures and strain rates. Results of the mechanical testing were correlated with fractography and microstructural evaluations of the welds to confirm bonding behavior. Both clean interface conditions and oxidation and lubrication layers were evaluated to simulate the difference of seam and charge welds in the process. Results …

Computational Modeling Of The Heat Treatment Of White Oak Bound For Spirit Maturation, Kate E. Mclarney-Popham

Theses and Dissertations--Chemical and Materials Engineering

Maturation of distilled spirits in white oak barrels is a long standing practice known to have great impact on spirit character. Much of this impact can be controlled by the thermal modification of the barrel, since thermal degradation of the wood determines what wood compounds are available to interact with the spirit during maturation. In this work, a computational model for the thermal degradation of wood was developed and, with flavor compound data from literature, was used to investigate the effect of heat treatment on lignin-derived flavor compounds. The computational model in this work accounted for three solid species, three …

The Optimization And Manufacturing Scale-Up Of Polymeric Membranes Using Eco-Friendly Solvents, David Lu

Theses and Dissertations--Chemical and Materials Engineering

Polymeric membranes have become a prominent technology applied in water filtration due to the lower cost, energy input, and simpler manufacturing process relative to other separation technologies. However, the environmental impact of polymeric membrane fabrication remains a hindrance due to the use of hazardous solvents derived from fossil fuels (e.g., DMAc, NMP, DMF) that pose a risk to the environment and human health. Whereas recent studies have demonstrated the proof-of-concept of polymeric membrane derived from eco-friendly solvents, the next steps of optimizing and upscaling the production of these membranes remains understudied and a gap between lab-scale studies and the path …

Combinatorial Thin Film Approach To Accelerate Materials Discovery: Development Of Nanoporous And Bulk Multi-Principal Element Alloys, Tibra Das Gupta

Theses and Dissertations--Chemical and Materials Engineering

Multi-principal element alloys (MPEAs) have garnered significant attention in materials science due to their potential for exhibiting a combination of desirable properties stemming from their unique configurational entropy. While early research focused on equiatomic compositions, recent studies have indicated that non-equiatomic MPEAs may offer superior mechanical performance. However, the identification of optimal non-equiatomic compositions remains challenging due to the vast compositional space and the reliance on time-consuming and computationally expensive methods. This dissertation presents a combinatorial thin film approach as a rapid and efficient strategy for discovering two types of materials: nanoporous and bulk MPEAs.

The first study explores the …

Microstructural Characterization Of Complex Metal Alloy Systems With A Focus On Electron Microscopy, Alexandra Allamon

Theses and Dissertations--Chemical and Materials Engineering

Multi-principal element alloys (MPEAs)/high-entropy alloys (HEAs) are a class of materials that provide novel and superior combinations of properties, with promise for use in challenging application areas that many of the current established materials cannot fit. With a higher number of constituent elements, many of the newly created alloys are compositionally complex in nature, known to contain combinations of relatively soft FCC phases, hard BCC phases, and, in some cases, even harder intermetallic phases. Microstructural study of these new materials is essential to understanding the enhanced properties they may possess, but their complexity can make this study much more challenging …

Ion Hydration In Bulk And Nanoconfined Water: Insights From Machine Learning Force Fields, Zachary D. Baker

Theses and Dissertations--Chemical and Materials Engineering

Understanding ionic hydration remains a central challenge in physical chemistry and materials science, as the interactions between ions and water molecules govern diverse phenomena ranging from electrolyte transport to selective ion separation. While experimental techniques have provided invaluable insights into solvation energetics and coordination numbers, they often lack atomistic resolution, particularly under nanoscale confinement where direct measurement becomes infeasible. Molecular dynamics (MD) simulations can bridge this gap; however, conventional classical force fields are limited by their simplified, fixed functional forms and empirical parameterization, whereas ab initio molecular dynamics (AIMD) achieves higher accuracy at the expense of severe computational cost and …

Understanding The Influence Of Applied Magnetic Field On Aluminum Alloys: Implications On Strength, Precipitate Development And Diffusion Of Solutes, Damilola David Alewi

Theses and Dissertations--Chemical and Materials Engineering

The processing of certain metals and alloys under magnetic fields presents a promising yet underexplored frontier for controlling microstructure alongside improving physical and mechanical properties. Magnetic fields can be strategically applied at different stages of materials processing, from melting and solidification to subsequent heat treatments to achieve targeted properties in materials. Although magnetic fields have been found to aid changes in microstructural evolution and phase equilibria in ferrous materials, there is limited application of this technique in non-ferrous material systems. This dissertation aims at contributing to the understanding of the influence of magnetic field on the mechanical properties and solid-state …

Catalytic Deoxygenation Of Oleaginous Biomass To Renewable Diesel And Sustainable Aviation Fuel Via Decarboxylation/Decarbonylation, Chukwudalu Great Umenweke

Theses and Dissertations--Chemistry

Several technologies have been developed to produce hydrocarbon biofuels – renewable diesel (RD) and sustainable aviation fuel (SAF) – from fats, oils, and greases (FOG), with the hydroprocessing of esters and fatty acids (HEFA) representing one of the most mature pathways. In its current form, HEFA is mainly reliant on the hydrodeoxygenation (HDO) reaction, which has several drawbacks since HDO requires large amounts and pressures of hydrogen, feedstocks of high purity and cost, as well as problematic sulfided catalysts that risk contaminating the biofuel product with sulfur. A process based on decarboxylation/decarbonylation (deCO_x) offers an attractive alternative to …

Reevaluating The Opportunity For Wind Energy In Kentucky: Advancing Technology, Changing Economics, And Generation Complementarity, Lawrence E. Holloway, Aron Patrick, Dan M. Ionel

Electrical and Computer Engineering Faculty Publications

Recent developments in wind turbine technology, new wind resource data, and new federal tax credits for renewable energy are increasing the suitability of wind electricity generation in Kentucky. In 2022, Kentucky had 68% of its electricity from coal and in 2023 was one of eight U.S. states with no utility-scale wind generation. In the past, the state has been viewed as being generally unsuitable for wind power generation. While wind is not the most economic resource in Kentucky, all states bordering the Commonwealth have wind power. Wind power generation in Kentucky appears increasingly likely in the coming decades to play …

Physicochemical Property Effects On Immune Modulating Polymeric Nanoparticles: Potential Applications In Spinal Cord Injury, Daniel J. Kolpek, Jaechang Kim, Hisham Mohammed, John C. Gensel, Jonghyuck Park

Markey Cancer Center Faculty Publications

Nanoparticles (NPs) offer promising potential as therapeutic agents for inflammation-related diseases, owing to their capabilities in drug delivery and immune modulation. In preclinical studies focusing on spinal cord injury (SCI), polymeric NPs have demonstrated the ability to reprogram innate immune cells. This reprogramming results in redirecting immune cells away from the injury site, downregulating pro-inflammatory signaling, and promoting a regenerative environment post-injury. However, to fully understand the mechanisms driving these effects and maximize therapeutic efficacy, it is crucial to assess NP interactions with innate immune cells. This review examines how the physicochemical properties of polymeric NPs influence their modulation of …

Smart Systems For Employing Iot Devices For Monitoring And Control Of Electric Vehicle Residential Charging, Grant M. Fischer, Steven B. Poore, Rosemary E. Alden, Donovin D. Lewis, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

As the number of electric vehicles (EVs) on the road continues to increase, the rise in power demand may pose challenges, especially for the localized grid capacity during peak load events. This paper briefly reviews methods of power monitoring and load shedding such as smart charging and load management systems. An internet-of-things (IoT) power monitoring system is proposed for high-resolution power monitoring and control of J1772 standard level 2 EV charging systems to provide detailed data to enable future studies on EV grid integration. Additionally, a hardware test bench (HTB) including a DC battery emulator, oscilloscope, and commercial EV charger …

A Critical Analysis Of Circular Product Attributes And Limitations Of Product Circularity Assessment Methods, Junwon Ko, Gisele Bortolaz Guedes, Fazleena Badurdeen, I. S. Jawahir, K. C. Morris, Vincenzo Ferrero, Buddhika M. Hapuwatte, Ryan Bradley, Ardeshir Raihanian

Institute for Sustainable Manufacturing Faculty Publications

The Circular Economy (CE) has been proposed as a strategy to promote the efficient use of resources, maximizing the benefits derived from materials and products through value recovery strategies, and minimizing waste generation. However, ambiguity remains in defining what makes a product circular and its characteristics when adapting the CE concept for application at the product level. More clarity about the constitutive characteristics of Circular Products (CPs) is also vital to facilitate their design. To address this challenge, and with the intention to increase the adoption of CE concept within the industry, the descriptions and attributes of a Circular Product …

Causes And Prevention Of Thermal Runaway In Lithium-Ion Batteries — A U.S. Utility Perspective, Shaun Lavin, Kwabena Kyeremeh, Elias Nemeh, David Beyerle, Chad Alkire, Samuel Kelty, Lakshmi Srinivasan, Stephanie Shaw, Erin Minear, Haresh Kamath, Dan Ionel, Aron Patrick

Power and Energy Institute of Kentucky Faculty Publications

Lithium-ion batteries are a critically important technology for maintaining grid reliability with the integration of variable intermittent renewable energy resources. However, lithium-ion batteries also pose significant human safety and infrastructure hazards due to the inherent risk of thermal runaway, fire, and explosion, which should be understood, mitigated, and managed. While battery manufacturers have primary responsibility for the design, manufacturing, and software which are necessary to keep battery storage systems safe, electric utilities also have an important role in understanding these risks and adopting best practices to mitigate them. This paper provides background on utility-scale battery deployment, an overview of a …

The Effect Of Organic Semiconductor Electron Affinity On Preventing Parasitic Oxidation Reactions Limiting Performance Of N-Type Organic Electrochemical Transistors, Maryam Alsufyani, Benjamin Moss, Claudia E. Tait, William K. Myers, Maryam Shahi, Katherine Stewart, Xiaolei Zhao, Reem B. Rashid, Dilara Meli, Ruiheng Wu, Bryan D. Paulsen, Karl J. Thorley, Yuanbao Lin, Craig Combe, Charlie Kniebe-Evans, Sahika Inal, Sang Young Jeong, Han Young Woo, Grant Ritchie, Ji-Seon Kim, Jonathan Rivnay, Alexandra F. Paterson, James R. Durrant, Iain Mcculloch

Chemical and Materials Engineering Faculty Publications

A key challenge in the development of organic mixed ionic-electronic conducting materials (OMIEC) for high performance electrochemical transistors is their stable performance in ambient. When operating in aqueous electrolyte, potential reactions of the electrochemically injected electrons with air and water could hinder their persistence, leading to a reduction in charge transport. Here, the impact of deepening the LUMO energy level of a series of electron-transporting semiconducting polymers is evaluated, and subsequently rendering the most common oxidation processes of electron polarons thermodynamically unfavorable, on organic electrochemical transistors (OECTs) performance. Employing time resolved spectroelectrochemistry with three analogous polymers having varying electron affinities …

Economic Contribution Of Kentucky Airports, P. Gayle Marks, Bethany Paris, Bryan Gibson

Kentucky Transportation Center Research Report

Airports generate economic impacts that are felt well beyond their physical boundaries by supporting commerce, tourism, and the provision of essential services. To understand the economic contributions of airports throughout Kentucky, researchers collected data from general aviation (GA) airports and commercial service (CS) airports across the state on operational statistics, levels of employment, and usage patterns in calendar year 2022. IMPLAN^® econometric models were developed to estimate the economic contributions of the state’s airports. These models show that in 2022 Kentucky’s airports contributed $23.7 billion in total economic output, which equals 9.1 percent of its gross domestic product ($261.5 …

Combined Machine Learning And Differential Evolution For Optimal Design Of Electric Aircraft Propulsion Motors, David R. Stewart, Matin Vatani, Rosemary E. Alden, Donovin D. Lewis, Pedram Asef, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Electric aircraft propulsion requires highly efficient and power-dense fault-tolerant electric motors optimized for specific flight profile operation. State-of-the-art design of electric motors involves substantial computational resources and combines electromagnetic finite element analysis (FEA) and optimization techniques. This paper proposes a new approach using a physics-based machine learning (ML) multi-input univariate meta-model trained on FEA and differential evolution (DE) optimization results to predict electromagnetic torque output. Hundreds of individual designs, generated through multiple generations of a DE algorithm, are analyzed by 3D FEA to create a database, which is then employed for the training and satisfactory validation of the ML model. …

Improving Transportation Resiliency, Ben Blandford, Erin Lammers-Staats, Emma Gregory

Kentucky Transportation Center Research Report

Transportation agencies are increasingly more challenged by the effects of extreme weather and national hazards on transportation assets.  Severe weather events in Kentucky have become more frequent and more costly. These extreme events damage transportation assets, increase maintenance costs and strain transportation budgets. Climate models predict changing conditions to occur over the next century that differ from historical data. In Kentucky, models predict a warmer and wetter environment. The goal of this research is to help KYTC plan for extreme weather and natural hazards events, as well as absorb, recover from, and adapt to the resulting damage.  Researchers determined where …

Spatiotemporal Wind Energy Assessment For Transmission Network Integration Considering The Location Of Electrical Substations And Loads, Kwabena Kyeremeh, Rosemary E. Alden, Aron Patrick, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Wind energy is an abundant renewable resource that can support decarbonization of energy supply. It is, therefore, essential to conduct a comprehensive assessment of wind energy potential for effective transmission network planning and integration. This work introduces a spatial-temporal assessment methodology for wind energy name plate-rated power capacity that considers the locations of electrical substations and transmission lines. This methodology applies Geographic Information System (GIS) land cover data to define siting exclusions for wind turbine installations. The correlation between generated wind power and estimates of power system load, as well as capacity factor, on a sub-regional basis for specific latest …

Investigating The Effect Of Microwave Pretreatment On Bastnasite Grinding For Comminution Energy Reduction And Rare Earth Recovery, Kaveh Asgari, Qingqing Huang, Rick Q. Honaker, Edward Sabolsky

Chemical and Materials Engineering Faculty Publications

This study explored the impact of microwave pretreatment on the grinding efficiency of bastnaesite ore using a stirred mill. Bastnaesite ore was prepared using a staged crushing and sieving process, followed by microwave pretreatment in a specially designed microwave furnace system. Representative samples of the crushed ore underwent stirred mill grinding, with power draw measurements recorded and adjusted to reflect only the specific energy input required for grinding. Particle size distribution was analyzed periodically using laser particle size analysis. In addition, a Box–Behnken design was used to statistically assess the effects of various parameters on the results, ensuring a robust …

Combined 3d Fea And Machine Learning Design Of Inductive Polyphase Coils For Wireless Ev Charging, Lucas A. Gastineau, Donovin D. Lewis, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Wireless power transfer (WPT) technologies are currently researched and developed for charging the batteries of electric unmanned air and ground vehicles. This paper presents systems with special polyphase inductive coils, which generate rotating fields and achieve high power density and efficiency. The complex geometry is modeled and studied with 3D electromagnetic finite element analysis (FEA). In order to reduce the substantial computational effort, machine learning techniques are proposed for surrogate modeling. A deep learning algorithm is introduced to capture the physics-based relationships between geometry and electromagnetic properties in inductive coils for wireless charging. Parametric models are systematically generated and analyzed …

Beyond 2d: Novel Biomaterial Approaches For Modeling The Placenta, Samantha G. Zambuto, Adrienne K. Scott, Michelle L. Oyen

Biomedical Engineering Faculty Publications

This review considers fully three-dimensional biomaterial environments of varying complexity as these pertain to research on the placenta. The developments in placental cell sources are first considered, along with the corresponding maternal cells with which the trophoblast interact. We consider biomaterial sources, including hybrid and composite biomaterials. Properties and characterization of biomaterials are discussed in the context of material design for specific placental applications. The development of increasingly complicated three-dimensional structures includes examples of advanced fabrication methods such as microfluidic device fabri- cation and 3D bioprinting, as utilized in a placenta context. The review finishes with a discussion of the …

Size And Shape Dependence Of Hydrogen-Induced Phase Transformation And Sorption Hysteresis In Palladium Nanoparticles, Xingsheng Sun, Rong Jin

Chemical and Materials Engineering Faculty Publications

Phase transitions of metals in hydrogen (H) environments are critically import- ant for applications in energy storage, catalysis, and sensing. Nanostructured metallic particles can lead to faster charging and discharging kinetics, increased lifespan, and enhanced catalytic activities. However, establishing a direct causal link between nanoparticle structure and function remains challenging. In this work, we establish a computational framework to explore the atomic config- uration of a metal-hydrogen system when in equilibrium with a H environ- ment. This approach combines Diffusive Molecular Dynamics with an itera- tion strategy, aiming to minimize the system’s free energy and ensure uniform chemical potential across …

Engineering The Coherent Phonon Transport In Polar Ferromagnetic Oxide Superlattices, In Hyeok Choi, Seung Gyo Jeong, Do-Gyeom Jeong, Ambrose Seo, Woo Seok Choi, Jong Seok Lee

Chemical and Materials Engineering Faculty Publications

Artificial superlattices composed of perovskite oxides serves as an essential platform for engineering coherent phonon transport by redefining the lattice periodicity, which strongly influences the lattice-coupled phase transitions in charge and spin degrees of freedom. However, previous methods of manipulating phonons have been limited to controlling the periodicity of superlattice, rather than utilizing complex mutual interactions that are prominent in transition metal oxides. In this study on oxide superlattices composed of ferromagnetic metallic SrRuO3 and quantum paraelectric SrTiO3 , phonon modulation by controlling the geometry of superlattice in atomic-scale precision is realized, demonstrating the coherent phonon engineering using structural and …

Accurate Synthesis Of Dysarthric Speech For Asr Data Augmentation, Mohammad Soleymanpour, Michael T. Johnson, Rahim Soleymanpour, Jeffrey Berry

Electrical and Computer Engineering Faculty Publications

Dysarthria is a motor speech disorder often characterized by reduced speech intelligibility through slow, uncoordinated control of speech production muscles. Automatic Speech recognition (ASR) systems can help dysarthric talkers communicate more effectively. However, robust dysarthria-specific ASR requires a significant amount of training speech, which is not readily available for dysarthric talkers. This paper presents a new dysarthric speech synthesis method for the purpose of ASR training data augmentation. Differences in prosodic and acoustic characteristics of dysarthric spontaneous speech at varying severity levels are important components for dysarthric speech modeling, synthesis, and augmentation. For dysarthric speech synthesis, a modified neural multi-talker …