Electrical and Computer Engineering Commons^™

The Impact Of Dissolved Organic Matter On Photodegradation Rates, Byproduct Formations, And Degradation Pathways For Two Neonicotinoid Insecticides In Simulated River Waters, Josephus F. Borsuah, Tiffany L. Messer, Daniel D. Snow, Steven D. Comfort, Shannon Bartelt-Hunt

UK CARES Faculty Publications

The influences of dissolved organic matter (DOM) on neonicotinoid photochemical degradation and product formation in natural waters remain unclear, potentially impacting the sustainability of river systems. Therefore, our overall objective was to investigate the photodegradation mechanisms and phototransformation byproducts of two neonicotinoid pesticides, imidacloprid and thiamethoxam, under simulated sunlight at the microcosm scale, to assess the implications of DOM for insecticide degradation in rivers. Direct and indirect photolysis were investigated using twelve water matrices to identify possible reaction pathways with two DOM sources and three quenching agents. Imidacloprid, thiamethoxam, and potential degradants were measured, and reaction pathways identified. The photodegradation …

Design And Optimization Of High-Efficiency Coreless Pcb Stator Axial Flux Pm Machines With Minimal Eddy And Circulating Current Losses, Yaser Chulaee, Greg Heins, Ben Robinson, Ali Mohammadi, Mark Thiele, Dean Patterson, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper proposes a systematic multi-step design procedure for highly efficient printed circuit board (PCB) stator coreless axial flux permanent magnet (AFPM) machines with minimal eddy and circulating current losses. The process begins with initial sizing, providing specific coefficients based on experience with multiple design projects. It continues with the optimization of the machine envelope design using an evolutionary algorithm and computationally efficient 3D finite element analysis (FEA) models. The subsequent step focuses on the detailed design of a PCB stator, aiming to minimize eddy and circulating current losses. Several open circuit loss mitigation techniques are proposed based on analytical …

Artificial Intelligence Enabled Machinery Fault Detection And Diagnosis Using Vibro-Acoustic Signals, Srinivasa Rao Ippili

Theses and Dissertations--Mechanical and Aerospace Engineering

In various industries, the early detection of faults in rotating machinery is crucial to prevent system failures and ensure customer satisfaction. Typically, vibration measurement and diagnosis are employed for fault detection, but this process faces challenges in automation due to the complexity of installing and maintaining accelerometers, particularly in end-of-line quality control or pre-installed machinery health assessments. Acoustic signals, as a form of mechanical wave, offer an alternative for monitoring machinery while in operation. Unlike accelerometers, acoustic transducers are non-contact and easy to set up, enabling real-time data collection without interrupting equipment operation. However, utilizing acoustic signals in manufacturing poses …

Provably Safe Control For Input-Constrained Robotic Systems, Pedram Rabiee

Theses and Dissertations--Mechanical and Aerospace Engineering

This dissertation addresses challenges in control design for safety-critical robotic systems with input constraints. It focuses on developing novel control barrier function (CBF) approaches to ensure safety while optimizing performance. The work is motivated by the limitations of traditional methods in handling nonlinear systems with multiple constraints and actuator limits.

Three main contributions are presented. First, a soft-minimum barrier function is introduced, utilizing finite-time horizon predictions to create control forward invariant subsets of the safe set while respecting actuator constraints. This method is extended to multiple backup controls, which can enlarge the safe operating region.

Second, a technique for composing …

Pulse-Width Modulation Spray System Performance And Development Of A Novel System To Optimize Spray Use Efficacy, Prashanta Pokharel

Theses and Dissertations--Biosystems and Agricultural Engineering

The overarching objective of this research was to enhance our understanding of pulse width modulation (PWM) based nozzle control system and develop an intelligent nozzle control system for agricultural spray applications. This dissertation focused on measuring and analyzing the transient nozzle pressure characteristics and performance under PWM control. Additionally, it explored the development of an innovative multi-degree-of-freedom (DOF) nozzle control system for precise chemical applications in specialty crop systems.

The pressure dynamics of a PWM system were studied by developing an instrumentation system capable of operating a solenoid valve and recording pressure signals. A nozzle body and two manifolds of …

Gas Assisted Electron Beam Patterning Processes, Deepak Kumar

Theses and Dissertations--Electrical and Computer Engineering

Radiolysis is a complex phenomenon in which molecules subjected to ionizing radiation form new chemical species. Electron-beam irradiation has proven to be a versatile approach for significantly altering materials’ properties and forms the basis for electron-beam lithography using both organic and inorganic resists. Electron-beam exposure is normally carried out under high vacuum conditions to reduce contamination and allow for unhindered interaction between the electrons and the resist material. Exposure under an ambient gas at sub-atmospheric pressures has been found to provide a distinct mechanism which can be exploited to circumvent some of the challenges associated with material processing and significantly …

Reinventing Integrated Photonic Devices And Circuits For High Performance Communication And Computing Applications, Venkata Sai Praneeth Karempudi

Theses and Dissertations--Electrical and Computer Engineering

The long-standing technological pillars for computing systems evolution, namely Moore's law and Von Neumann architecture, are breaking down under the pressure of meeting the capacity and energy efficiency demands of computing and communication architectures that are designed to process modern data-centric applications related to Artificial Intelligence (AI), Big Data, and Internet-of-Things (IoT). In response, both industry and academia have turned to 'more-than-Moore' technologies for realizing hardware architectures for communication and computing. Fortunately, Silicon Photonics (SiPh) has emerged as one highly promising ‘more-than-Moore’ technology. Recent progress has enabled SiPh-based interconnects to outperform traditional electrical interconnects, offering advantages like high bandwidth density, …

Design And Control Of Axial Flux Permanent Magnet Coreless Machines With Special Windings, Yaser Chulaee

Theses and Dissertations--Electrical and Computer Engineering

Permanent magnet synchronous machines (PMSMs), particularly those of the axial flux type, are being researched and developed for various applications such as HVAC systems, aviation propulsion, and electric vehicles. The coreless (air-cored) stator axial flux permanent magnet (AFPM) machine topology offers notable advantages over conventional designs by eliminating magnetic cores and their associated losses. These advantages include potentially higher efficiency, zero cogging torque, and reduced audible noise and vibration. Eliminating the magnetic core also allows for more effective cooling systems, as coolants can be in direct contact with the stator windings, potentially improving power density and specific torque.

The absence …

Ultra‐Fast Finite Element Analysis Of Coreless Axial Flux Permanent Magnet Synchronous Machines, Yaser Chulaee, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Large‐scale design optimisation techniques enable the design of high‐performance electric machines. Electromagnetic 3D finite element analysis (FEA) is typically employed in optimisation studies for accurate analysis of axial flux permanent magnet (AFPM) machines, which require extensive computational resources. To reduce the computational burden, a FEA‐based mathematical method relying on the geometric and magnetic symmetry of coreless AFPM machines is proposed to estimate the machine performance indicators using the least number of FEA solutions, thereby significantly lowering the running time. This method is generally applicable to AFPM machines with low saturation effects and cogging torque as exemplified for a printed circuit …

Design And Optimization Of High-Efficiency Coreless Pcb Stator Axial Flux Pm Machines With Minimal Eddy And Circulating Current Losses, Yaser Chulaee, Greg Heins, Ali Mohammadi, Mark Thiele, Dan M. Ionel, Ben Robinson

Electrical and Computer Engineering Graduate Research

This paper proposes a systematic multi-step design procedure for highly efficient printed circuit board (PCB) stator coreless axial flux permanent magnet (AFPM) machines with minimal eddy and circulating current losses. The process begins with initial sizing, providing specific coefficients based on experience with multiple design projects. It continues with the optimization of the machine envelope design using an evolutionary algorithm and computationally efficient 3D finite element analysis (FEA) models. The subsequent step focuses on the detailed design of a PCB stator, aiming to minimize eddy and circulating current losses. Several open circuit loss mitigation techniques are proposed based on analytical …

Design Optimization Of A Direct-Drive Wind Generator With A Reluctance Rotor And A Flux Intensifying Stator Using Different Pm Types, Ali Mohammadi, Oluwaseun A. Badewa, Yaser Chulaee, Donovin D. Lewis, Somasundaram Essakiappan, Madhav Manjrekar

Electrical and Computer Engineering Graduate Research

This paper presents a large-scale multi-objective design optimization for a direct-drive wind turbine generator concept that is based upon an experimentally validated computational model for a small-scale prototype motor of the same type. By integrating an outer reluctance-type rotor and a segmented stator with toroidally wound single-coil modules containing spoke-type PMs, the design optimization aims to minimize losses, active mass, and torque ripple while adhering to a power factor constraint. The AC windings and PMs are positioned in the stator and this concept enhances flux concentration, enabling the use of more affordable high energy non-rare-earth (special type) magnets. The exterior …

Large-Scale Design Optimization Of An Axial-Flux Vernier Machine With Dual Stator And Spoke Pm Rotor For Ev In-Wheel Traction, Ali Mohammadi, Yaser Chulaee, Aaron M. Cramer, Ion G. Boldea, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper presents the optimization study targeting a specific drive cycle for a MAGNUS-type axial-flux permanent magnet vernier machine (AFPMVM). The proposed MAGNUS machine has a novel design with a dual-stator configuration, where only one stator is wound, with a high-polarity spoke permanent magnet (PM) rotor. The machine topology has a 3D flux path, which necessitates the analysis of a large finite element (FE) model. However, due to the computational complexity and time required for such a large FE model, a new approach was developed. This approach involves a computationally efficient finite element analysis (CE-FEA) model combined with a single …

Machine-Learning-Assisted Design Of Deep Eutectic Solvents Based On Uncovered Hydrogen Bond Patterns, Usman Lame Abbas, Yuxuan Zhang, Joseph Tapia, Md Selim, Jin Chen, Jian Shi, Qing Shao

Markey Cancer Center Faculty Publications

Non-ionic deep eutectic solvents (DESs) are non-ionic designer solvents with various applications in catalysis, extraction, carbon capture, and pharmaceuticals. However, discovering new DES candidates is challenging due to a lack of efficient tools that accurately predict DES formation. The search for DES relies heavily on intuition or trial-and-error processes, leading to low success rates or missed opportuni- ties. Recognizing that hydrogen bonds (HBs) play a central role in DES formation, we aim to identify HB features that distinguish DES from non-DES systems and use them to develop machine learning (ML) models to discover new DES systems. We first analyze the …

Investigation Of Delta-Focused Ictal Electrical Source Imaging In Refractory Focal Epilepsy, Jared A. Rybarczyk

Theses and Dissertations--Electrical and Computer Engineering

Refractory focal epilepsy is characterized by the presence of seizures that cannot be controlled via anti-seizure medications. For patients suffering from this form of epilepsy, accurate identification of the seizure onset zone is a crucial step for many modalities of treatment. Electrical source imaging (ESI) allows for estimation of the seizure onset zone from electroencephalography. EEG feature extraction is an important step that can impact the final accuracy of source estimates. This work provides a review of 23 ictal ESI studies and proposes a delta-focused ictal ESI methodology. Our proposed delta-focused ictal ESI is implemented across 33 refractory focal epilepsy …

Electronics Design For Krepe Atmospheric Entry Capsule Avionics, Matt Ruffner

Theses and Dissertations--Electrical and Computer Engineering

This research documents the design, testing, and implementation of sensing, control, and communications subsystems for small atmospheric entry capsules. Atmospheric entry capsules pose a unique electronics design challenge given mission requirements, environmental constraints, and inherent risk involved in space based missions. Previous work on small satellites developed the CubeSat platform as a means of ensuring reliability after university-led small satellite missions experienced failures. The publication of the CubeSat platform allowed researchers to focus on the payload science utilizing a standardized form-factor and reusable electronics. Environmental and operational constraints of CubeSats and atmospheric entry capsules overlap and best-practices associated with building …

Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso

Theses and Dissertations--Electrical and Computer Engineering

The emergence of deep learning models and their success in visual object recognition have fueled the medical imaging community's interest in integrating these algorithms to improve medical diagnosis. However, natural images, which have been the main focus of deep learning models and mammograms, exhibit fundamental differences. First, breast tissue abnormalities are often smaller than salient objects in natural images. Second, breast images have significantly higher resolutions but are generally heavily downsampled to fit these images to deep learning models. Models that handle high-resolution mammograms require many exams and complex architectures. Additionally, spatially resizing mammograms leads to losing discriminative details essential …

Mitigation Of Reflected Overvoltage In Wind-Turbine Generator-Converter Systems With A Smart Coil Concept, Lulu Wei

Theses and Dissertations--Electrical and Computer Engineering

In the recent decade, ultra-fast wide bandgap switching devices such as Silicon Carbide (SiC) Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) have been increasingly utilized in power electronic converters for renewable energy power generation systems due to their advantages of enabling high energy efficiency and high power density. However, the much higher voltage slew rate (i.e., dv/dt) with SiC power converters may induce voltage reflection and reliability concerns in machine-converter systems, especially for medium-voltage systems with long cable connections. In wind-turbine power generation systems, generators are typically located in the nacelles, and medium-voltage power converters are mostly placed at the bottom of the …

Multi-Physics Modeling Of Immersion Cooled Electric Power Apparatuses, Reza Ilka

Theses and Dissertations--Electrical and Computer Engineering

Electric power conversion apparatuses such as electromagnetic transformers and power electronic converters play a backbone role in the global power and energy industries, such as power transmission and distribution, electrified transportation vehicle systems, industry automation, and the like. To investigate the performance (efficiency, reliability, etc.) of such critical power conversion apparatuses, high-fidelity multi-physics modeling becomes critical which involves dedicated coupling among multiple physical domains, including electrical, magnetic, thermal, mechanical, and material engineering. Nevertheless, the majority of the existing models for these power conversion apparatuses focus only on one or two physical domains, and the modeling fidelity needs to be further …

A Novel Processor Architecture Implementing The Stacked Error Diffusion Algorithm And Its Zynq-Based Realization, Qishi Hu

Theses and Dissertations--Electrical and Computer Engineering

Digital halftoning reproduces continuous-tone images using patterns of black and white dots, while multitoning extends this concept by incorporating inks with intermediate intensities. These techniques are extensively utilized in the printing industry to accommodate the limited range of inks available in printers. Stacked error diffusion is a high-quality multitoning algorithm that adheres to the blue-noise dithering standard. This thesis research studies the potential parallelism inherent in the algorithm and introduces the design of a novel processor architecture optimized for efficient execution. The architecture is realized on an FPGA development board featuring a Zynq SoC. Additionally, the hardware prototype can also …

Information-Theoretic Learning Framework Based On Covariance Operators On Reproducing Kernel Hilbert Spaces, Jhoan Keider Hoyos Osorio

Theses and Dissertations--Electrical and Computer Engineering

Information theory provides tools to quantify uncertainty, dependence, and similarity between probability distributions, which are crucial for addressing various machine-learning problems. However, estimating these quantities is challenging because data distributions are usually unknown, and only observations are available for analysis. In this dissertation, we advance the field of information-theoretic learning by developing a comprehensive framework using kernel methods for analyzing probability distributions using reproducing kernel Hilbert spaces (RKHS). By leveraging covariance operators in this representation space, we propose approaches to estimate a set of fundamental information-theoretic quantities, that, because of their resemblance with conventional quantities in information theory, we call …

Optimal Control And Evaluation Of Shipboard Power Systems, Musharrat Sabah

Theses and Dissertations--Electrical and Computer Engineering

Electric warships are involved in complex missions consisting of multiple simultaneous operations. In order to ensure mission success, future ships must be designed in a way that optimizes their performance in the presence of complex mission loads. The focus of this research is an effort to optimally control the performance of shipboard systems during missions involving multiple scenarios or vignettes. The evaluation of the performance of mission-oriented power systems is based on the degree to which these systems deliver power to the loads required to perform the mission at hand. The performance of such systems involves a dynamic interplay between …

High Reliability Motor-Drive Systems For Electric Aircraft Propulsion, Majid Tahmasbi Fard

Theses and Dissertations--Electrical and Computer Engineering

The transition towards electric propulsion in aircraft applications requires significant advancements in enhancing the efficiency and power density of power transmission and distribution systems. Among the critical power components in electric aircraft propulsion systems, power electronic converters hold paramount importance as they provide a pivotal interface between batteries and propulsion motors while providing a high degree of controllability and flexibility to the system. Integrating medium voltage DC (MVDC) and the emerging wide bandgap switching devices into power converters not only amplifies converter performance but also unlocks multifarious system-level benefits, including reduced power losses, weight savings, and the utilization of high-speed …

Overview Of Hil Co-Simulation For Very Large Distribution Systems And Power Electronic Converters With A Dc Fast Charging Ev Benchmark Study On An Ieee Test Feeder, Rosemary E. Alden, Donovin D. Lewis, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Current development towards implementation of the future smart grid includes advanced controller and power hardware-in-the-loop (CHIL/PHIL) testing of new technology. The impact of new loads, distributed energy resources (DER) equipment, and controls spans two fields, both electric distribution power systems modeling, typically completed in the phasor domain, and electromagnetic transient (EMT) analysis across the frequency domain. The co-simulation of distribution power systems and power electronic converter controls is a growing field of research for improved design using real-time HIL capability. Within this paper, over fifty references are reviewed to summarize the current state of HIL technology, specifically with co-simulation in …

Distribution System Optimal Operation Of Smart Homes With Battery And Equivalent Hvac Energy Storage For Virtual Power Plant Controls, Steven B. Poore, Rosemary E. Alden, Evan S. Jones, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Battery energy storage systems (BESS) that can be utilized for demand response (DR) and load shifting are limited in adoption by high capital cost. Large residential loads such as electric water heaters (EWH) and heating, ventilation and air-conditioning (HVAC) may be controlled using distributed energy resource management systems (DERMS) to perform functions like batteries, such as reducing cost and decreasing energy storage capacity requirements when implemented at the aggregate level. Increasing levels of renewable generation further incentivizes shifting loads in time through controls and energy storage to reduce curtailment and carbon footprint. This paper proposes techniques for the optimization and …

Assessment Of Land And Renewable Energy Resource Potential For Regional Power System Integration With Ml Spatio-Temporal Clustering, Rosemary E. Alden, Claire Halloran, Donovin D. Lewis, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Toward the planning and development of future electric power systems with extremely large penetration of renewable resources (DERs), detailed assessment of power and energy potential is needed considering both spatial and temporal data per region. Within this paper, a methodology for spatio-temporal DER capacity potential considering land cover types and weather variation are presented using spatio-temporal data. Additionally, an application of empirical orthogonal functions (EOFs) and max-p unsupervised learning techniques is proposed for DER generation to identify zones of similar output power in space and time. A detailed case study for the example region of Kentucky, USA is completed with …

Fault Tolerant Electric Machine Concept For Aircraft Propulsion With Pm Rotor And Dc Current Stator Dual-Stage Excitation, Donovin D. Lewis, Oluwaseun A. Badewa, Ali Mohammadi, Matin Vatani, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

The development of electrically propelled aircraft requires electric machines that are fault-tolerant, compact, and efficient at multiple operating points. This paper proposes a novel machine topology combining a coreless Halbach PM array axial flux unit and a PM-less synchronous hybrid excited radial flux unit. Both units are coupled on the same shaft to take advantage of the opportunities available in the unique usage profile for aviation. The machines can be used simultaneously for the take off and altitude climbing stage or used individually during the cruising stage. The coreless axial flux PM (CAFPM) motor unit consists of two Halbach array …

Coreless Axial Flux Halbach Array Permanent Magnet Generator Concept For Direct-Drive Wind Turbine, Matin Vatani, Ali Mohammadi, Donovin Lewis, John F. Eastham, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper proposes a concept for a coreless axial flux permanent magnet (CAFPM) generator with a double sided Halbach array rotor for direct-drive offshore wind turbine applications. The application of printed circuit board (PCB) technology is explored as applied to a concentrated winding stator due to its high reliability, repeatability, and fast mass production. A double-sided Halbach array rotor is employed to intensify the airgap flux density and to enable the elimination of the rotor back iron, decreasing the generator’s total active mass. The effect of the Halbach array rotor pole number and magnet-to-magnet (M2M) gap on the airgap flux …

A Comparative Effectiveness Study On Opioid Use Disorder Prediction Using Artificial Intelligence And Existing Risk Models, Sajjad Fouladvand, Jeffery Talbert, Linda Phyliss Dwoskin, Heather M. Bush, Amy L. Meadows, Lars E. Peterson, Yash R. Mishra, Steven K. Roggenkamp, Fei Wang, Ramakanth Kavuluru, Jin Chen

Markey Cancer Center Faculty Publications

Opioid use disorder (OUD) is a leading cause of death in the United States placing a tremendous burden on patients, their families, and health care systems. Artificial intelligence (AI) can be harnessed with available healthcare data to produce automated OUD prediction tools. In this retrospective study, we developed AI based models for OUD prediction and showed that AI can predict OUD more effectively than existing clinical tools including the unweighted opioid risk tool (ORT). Data include 474,208 patients’ data over 10 years; 269,748 were females with an average age of 56.78 years. Cases are prescription opioid users with at least …

V2g Optimization For Dispatchable Residential Load Operation And Minimal Utility Cost, Rosemary E. Alden, Ashutosh Timilsina, Simone Silvestri, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Electric Vehicles (EVs) are gaining popularity among consumers and are expected to play a significant role in the future of transportation. Within this paper, a reverse auction is formulated through an optimization problem to minimize the utility energy cost using Vehicle-to-Grid (V2G) operation, as well as transition residential communities to dispatchable aggregate constant load profiles for demand response (DR). The evolution-ary V2G Auction (eV2GA), including the non-dominated sorting genetic algorithm (NSGA-II), is proposed for the formulated problem. It uses co-simulation with OpenDSS for power flow analysis as part of the objective function to account for physical constraints of infrastructure on …

Electric Water Heater Modeling For Large-Scale Distribution Power Systems Studies With Energy Storage Cta-2045 Based Vpp And Cvr, Rosemary E. Alden, Huangjie Gong, Tim Rooney, Brian Branecky, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

As the smart grid involves more new technologies such as electric vehicles (EVs) and distributed energy resources (DERs), more attention is needed in research to general energy storage (GES) based energy management systems (EMS) that account for all possible load shifting and control strategies, specifically with major appliances that are projected to continue electrification such as the electric water heater (EWH). In this work, a methodology for a modified single-node model of a resistive EWH is proposed with improved internal tank temperature for user comfort modeling and capabilities for conservation voltage reduction (CVR) simulations as well as Energy Star and …