Digital Commons Network^™

Multi-Phase Wireless Power Transfer With High Power Density Inductive Coils For Electric Drone Charging, Lucas A. Gastineau, Donovin D. Lewis, Omer Onar, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Wireless charging of unmanned ground vehicles and aircraft has been proposed to increase charging reliability and security, allow for autonomous functionality, and either reduce battery size or increase continuous flight time. This paper proposes a three-phase Litz wire primary and a two-phase PCB secondary for high secondary-side power density considering misalignment tolerances, surface and volumetric power density, and coil sizing. Electromagnetic 3D finite element analysis (FEA) simulations are conducted to study variation in mutual inductance and coupling coefficient with different secondary coil sizes and number of turns, horizontal and vertical misalignment between the primary and secondary, and a combination of …

Nonlinear Design Scaling Of Electric Machines Based On Hybrid De And Meta-Modeling Application To Synchronous Motors With Combined Pm Stator And Reluctance Rotor Excitation, Oluwaseun A. Badewa, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper presents an innovative method for nonlinear scaling of electric machines by integrating machine learning (ML)-based meta-modeling with a differential evolution (DE) algorithm. The technique is applied to high-performance combined-excitation synchronous electric motors which exhibit highly nonlinear characteristics, making performance scaling challenging. The proposed approach employs an ML meta-model trained on data obtained from finite element analysis (FEA), utilizing an experimentally validated model for nonlinear scaling and performance prediction at different power ratings. The accuracy of the meta-model in capturing the nonlinear relationships between design parameters and motor performance is first assessed using metrics such as R-squared (R2) and …

Design Optimization And Scaling Of Coreless Afpm Machines Using Hybrid Fea-Based Differential Evolution And Machine Learning, Matin Vatani, David R. Stewart, Donovin D. Lewis, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper presents a machine learning (ML) based design framework for the fast and accurate optimization of coreless axial flux permanent magnet (AFPM) machines. Although the absence of magnetic cores eliminates material nonlinearity, the design process remains highly nonlinear due to the complex influence of geometric parameters. To overcome the computational challenges of finite element analysis (FEA)-based optimization, a series of multi-objective differential evolution (MODE) optimizations were conducted across various machine sizes at constant power output. The resulting design data was used to train an artificial neural network (ANN), enabling rapid prediction of machine performance without the need for repeated …

Coreless Axial Flux Permanent Magnet Machines With Concentrated Coils And Various Pole/Coil Combinations, Matin Vatani, Spencer M. Goode-Kulchar, John F. Eastham, Xiaoze Pei, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper comprehensively analyzes coreless stator axial flux permanent magnet (AFPM) machines by investigating rotor magnetic fields, stator winding factors, and 2D/3D finite element analysis (FEA) simulations. The torque production theory in coreless AFPM machines is studied with detailed derivations for flux density and current density. The impact of rotor permanent magnet (PM) width is examined for both surface-mounted and Halbach array configurations, followed by a discussion of its influence on the air-gap harmonic spectrum. The effect of stator coil side width is analyzed through a detailed winding factor study across various pole-to-coil ratios and a discussion on the trade-off …

Voltage And Reactive Power Combined Control Of Utility Devices And Smart Inverters On A Distribution Grid With Solar Pv, Steven B. Poore, Rosemary E. Alden, Evan S. Jones, Thomas Morstyn, Aron Patrick, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

With adoption of distributed energy resources (DERs) expected in future grids, voltage regulation methods need to be reevaluated and improved to ensure their effectiveness under the high volatility of renewable generation. A multi-timescale cluster-based method is proposed to optimize and disperse operation of voltage controlling utility devices including capacitor banks (CBs) and load tap changers (LTCs) while allowing faster response time with customer-owned smart inverters (SIs) in-between switching operations. The proposed method is tested on a digital twin (DT) of a very large utility distribution grid with 2,018 nodes and 8.65MW peak load to evaluate its effectiveness in future grid …

Torque-Speed Characteristic Estimation Based On Gaussian Processes And Adaptive Sampling Strategy For Permanent Magnet Synchronous Machines, Marcelo D. Silva, Pedram Asef, Oluwaseun A. Badewa, Rosemary E. Alden, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Internal Permanent Magnet Synchronous Machines (IPMs) are widely used and typically optimized to meet specific performance requirements. Parameters such as base speed, maximum torque, and maximum speed commonly define the torque- speed characteristic of a given design. This study introduces a novel machine learning approach for statistically estimating the torque-speed characteristics of IPMs using Gaussian Process Regression (GPR), which models predictions as random variables. By leveraging uncertainty quantification, the study explores sampling strategies that enable the construction of a high-precision meta-model with minimal error and uncertainty. The proposed adaptive sampling strategy, combined with GPR, accurately estimates torque-speed characteristics and associated …

Degradation Minimization Of Utility-Scale Li-Ion Bess Through Operational Optimization Employing An Equivalent Circuit Model, Kwabena A. Kyeremeh, Grant M. Fischer, Donovin D. Lewis, Aron Patrick, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

The increasing deployment of utility-scale battery energy storage systems (BESS) necessitates effective strategies for supporting grid services while minimizing degradation that may compromise system longevity. High charge/discharge rates (C-rate) and imbalanced operation of multi-unit BESS configurations may accelerate degradation. This paper proposes a degradation-aware operational optimization based on Model Predictive Control (MPC) for coordinating multiple BESS units under physical and operational constraints. The multi-objective optimization model imposes penalties on C-rate magnitude, operational state-of-charge (SoC) disparity, and battery internal resistance modeled using an equivalent circuit model. A case study conducted for a fleet of BESS units over a one-week load profile …

Csc36000 - Modern Distributed Computing Assignment, Saptarashmi Bandyopadhyay

Open Educational Resources

This assignment covers standard performance metrics for Distributed Systems and the basics of Multiprocessing for CSC36000 - Modern Distributed Computing at the City College of New York CUNY. It is an interactive coding assignment intended to be executed in a Python notebook.

Data Center Developments For Flexible Generation Dispatch, Advanced Infrastructure, And Ultra-Fast Digital Twins, Grant M. Fischer, Rosemary E. Alden, Donovin D. Lewis, Aron Patrick, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

The rapid advancement and widespread integration of artificial intelligence (AI) is driving demand for unprecedented deployment of power-intensive computational infrastructure, including multi-megawatt data centers with the potential for facilities with gigawatt-scale capacity in the near future. In this paper, load growth projections for the US are reviewed, and an example energy dispatch solution considering a mixed energy portfolio with flexible, renewable, distributed, and load-based generation is employed. The brief technology review included in the paper covers aspects of electric power, cooling, and computational infrastructures. The concept of a data center digital twin for transient load, grid interaction, and hybrid energy …

Developing A Low-Temperature Pathway For The Synthesis Of Two-Dimensional Ws2 Nanosheets, Akhil Potdar

Holster Scholar Projects

Since their discovery in 2004, two-dimensional (2D) materials have attracted great attention due to their unique mechanical, electrical, and chemical properties. However, their integration into devices is limited by the high temperatures required for crystalline growth, which prevents the use of flexible and biocompatible substrates like polymers for biomedical and next-generation electronic devices. This project aims to therefore develop a low-temperature synthesis process for two-dimensional tungsten disulfide (WS₂), a material particularly promising due to its tunable bandgap and biocompatibility. We propose that by first depositing an intermediate tungsten oxide film (WOx) via Hollow Cathode Plasma-Assisted Atomic Layer Deposition (HCP-ALD) and …

Foundations For Multi-Bit-Per-Cell Phase Change Memory Modeling Gst Crossbar Arrays, Sashah Wilson-Thompson

Holster Scholar Projects

This project builds a simulation foundation for selective cell heating in a phase-change memory (PCM) crossbar using Ge2Sb2Te5 (GST) as the active material. Using COMSOL Multiphysics® a 3D modeling software, couples Electric Currents, Electric Circuits, Heat Transfer in Solids, and Electromagnetic Heating for the simulation. A parameterized Tungsten (W)/GST-Amorphous/GST-Crystalline(phases) /W embedded in Silica Dioxide (SiO2) and surrounded in Silica Nitride (Si3N4) is validated at the single-cell level and scaled to small GST crossbars A terminal voltage (V_active/V_inactive, or 0 V if unselected) is applied through MOSFET and diode selector elements at the ends of each word line and bit line. …

Spectral Modeling Of Electromagnetic Radiation From Power Converters, Regan A. Varner

Theses and Dissertations

Switching power converters are increasingly utilized in contemporary electronics. They are becoming more compact and operate at higher frequencies, which contributes to radiated electromagnetic interference (EMI). This EMI is important to quantify for electromagnetic compatibility of the converters with other nearby systems. In this thesis, analytical models have been developed for both ideal and non-ideal switching waveforms, employing piecewise functions to describe time-domain waveforms, with their corresponding frequency spectra derived and compared to empirical spectra. The results demonstrate that the comparisons with measured frequency data exhibit agreement with the analytical models up to approximately 25 MHz. Additionally, our analysis indicates …

Towards Robust Bmocz Schemes For Non-Coherent Wireless Communication, Anthony Joseph Perre

Theses and Dissertations

Non-coherent communication has emerged as a promising approach to address several challenges at the physical layer. A particular scheme called binary modulation on conjugate-reciprocal zeros (BMOCZ) uses the zeros (i.e, roots) of a polynomial to convey information bits. In this thesis, we strive to improve the reliability of BMOCZ in various scenarios. In particular, we utilize machine learning (ML) methods to determine the parameters for BMOCZ and improve upon the decoding performance. Moreover, we introduce a smooshed BMOCZ variant to combat typical impairments encountered within wireless communications, including timing offsets (TOs) for noncoherent orthogonal frequency division multiplexing (OFDM). Through numerical …

Ge0.95sn0.05 On Si Avalanche Photodiode With Spectral Response Cutoff At 2.14 Μm, Justin Michael Rudie, Xiaoxin Wang, Rajesh Kumar, Grey Abernathy, Sylvester Amoah, Steven Akwabli, Hryhorii Stanchu, Perry C. Grant, Bao-Hua Li, Wei Du, Jifeng Liu, Shui-Qing Yu

Electrical Engineering and Computer Science Faculty Publications and Presentations

GeSn-based avalanche photodiode operating in shortwave infrared wavelength was demonstrated in this work. A separate absorption and charge multiplication structure was employed to take advantage of long wavelength absorption in GeSn and low impact ionization ratio of Si. Due to lattice mismatch between Si and GeSn that would degrade GeSn material quality if with direct growth, a 240-nm-thick Ge buffer was utilized, which simultaneously allows for the transporting photo generated electrons from the GeSn absorber to Si multiplication layer. Spectral response showed the cutoff wavelength beyond 2.1 mu m at room temperature. Dark current and capacitance-voltage measurements indicated a punch-through …

Insect-Foundation: A Foundation Model And Large Multimodal Dataset For Vision-Language Insect Understanding, Thanh-Dat Truong, Hoang-Quan Nguyen, Xuan-Bac Nguyen, Ashley Dowling, Xin Li, Khoa Luu

Electrical Engineering and Computer Science Faculty Publications and Presentations

Multimodal conversational generative AI has shown impressive capabilities in various vision and language understanding through learning massive text-image data. However, current conversational models still lack knowledge about visual insects since they are often trained on the general knowledge of vision-language data. Meanwhile, understanding insects is a fundamental problem in precision agriculture, helping to promote sustainable development in agriculture. Therefore, this paper proposes a novel multimodal conversational model, Insect-LLaVA, to promote visual understanding in insect-domain knowledge. In particular, we first introduce a new large-scale Multimodal Insect Dataset with Visual Insect Instruction Data that enables the capability of learning the multimodal foundation …

Resilience Engineering Via Bifurcation And Ecological Network Analysis: Demonstrated In An Electric Power Case Study, Rogelio Gracia Otalvaro

Doctoral Dissertations and Master's Theses

Modern systems are increasingly complex, interconnected cyber-physical systems that combine digital controls with physical infrastructure. This integration, along with the constant introduction of new technologies and actors into the network, enables reliable operation but introduces vulnerabilities to unexpected and varied disruptions and cascading failures, making resilience a critical concern. Traditional risk management and resilience assessment methods often struggle with the nonlinearity and dynamic behavior of these systems. This dissertation proposes a novel approach combining Bifurcation Analysis (BA) and Ecological Network Analysis (ENA) to enhance the understanding and improvement of system resilience. BA, a mathematical method from dynamical systems theory, is …

A Risk-Averse Data-Driven Distributionally Robust Optimization Method For Transmission Power Systems Under Uncertainty, Mehrdad Ghahramani, Daryoush Habibi, Asma Aziz

Research outputs 2022 to 2026

The increasing penetration of renewable energy sources and the consequent rise in forecast uncertainty have underscored the need for robust operational strategies in transmission power systems. This paper introduces a risk-averse, data-driven distributionally robust optimization framework that integrates unit commitment and power flow constraints to enhance both reliability and operational security. Leveraging advanced forecasting techniques implemented via gradient boosting and enriched with cyclical and lag-based time features, the proposed methodology forecasts renewable generation and demand profiles. Uncertainty is quantified through a quantile-based analysis of forecasting residuals, which forms the basis for constructing data-driven ambiguity sets using Wasserstein balls. The framework …

Construction, Optimization, And Characterization Of An Undergraduate Cold Cathode Table-Top Electron Accelerator For Radiation Physics Education, Caitlin Balmer, Mason Skeath, Mehran M. Zaini, Peter Zencak, Erin M. Craig

Journal of the Symposium of University Research and Creative Expression

Project Mentor(s): Mehran Zaini, PhD; Peter Zencak

Rising cancer cases spurred advancements in radiation therapy modalities, including electron accelerators. In this report, descriptive and diagnostic analysis was utilized to develop and characterize a functional, low energy cold cathode table-top electron accelerator for radiation physics experimentation in Central Washington University’s (CWU) undergraduate radiation lab. The device features a tungsten cathode (TC), brass anode, and copper Faraday Cup (FC) in a vacuum, enclosed by blue-tinted polyvinyl chloride (PVC). TC electron emission was facilitated by applied electric fields from input voltages of 1000 V to 5000 V. FC collected electron current in the …

Bridging Materials And Energy Storage Mechanisms In Zn-I2 Batteries, Rong-Qi Liu, Wen-Shuo Shang, Jin-Tao Zhang

Journal of Electrochemistry

Zinc-iodine (Zn-I₂) batteries have emerged as a compelling candidate for large-scale energy storage, driven by the growing demand for safe, cost-effective, and sustainable alternatives to conventional systems. Benefiting from the inherent advantages of aqueous electrolytes and zinc metal anodes, including high ionic conductivity, low flammability, natural abundance, and high volumetric capacity, Zn-I₂ batteries offer significant potential for grid-level deployment. This review provides a comprehensive overview of recent progress in three critical domains: positive-electrode engineering, zinc anode stabilization, and in situ characterization methods. On the cathode side, anchoring iodine to conductive matrices effectively mitigates polyiodide shuttling and enhances …

Significantly Enhanced Oxygen Reduction Reaction Activity In Co-N-C Catalysts Through Synergistic Boron Doping, Chang Lan, Jing-Sen Bai, Xin Guan, Shuo Wang, Nan-Shu Zhang, Yu-Qing Cheng, Jin-Jing Tao, Yu-Yi Chu, Mei-Ling Xiao, Chang-Peng Liu, Wei Xing

Journal of Electrochemistry

The weak adsorption energy of oxygen-containing intermediates on Co center leads to a considerable performance disparity between Co-N-C and costly Pt benchmark in catalyzing oxygen reduction reaction (ORR). In this work, we strategically engineer the active site structure of Co-N-C via B substitution, which is accomplished by the pyrolysis of ammonium borate. During this process, the in-situ generated NH₃ gas plays a critical role in creating surface defects and boron atoms substituting nitrogen atoms in the carbon structure. The well-designed CoB₁N₃ active site endows Co with higher charge density and stronger adsorption energy toward oxygen species, …

Series Reports From Professor Wei’S Group Of Chongqing University: Advancements In Electrochemical Energy Conversions (2/4): Report 2: High-Performance Water Splitting Electrocatalysts, Ling Zhang, Wang-Yang Wu, Qiu-Yue Hu, Shi-Dan Yang, Li Li, Rui-Jin Liao, Zi-Dong Wei

Journal of Electrochemistry

The unavailability of high-performance and cost-effective electrocatalysts has impeded the large-scale deployment of alkaline water electrolyzers. Professor Zidong Wei’s group has focused on resolving critical challenges in industrial alkaline electrolysis, particularly elucidating hydrogen and oxygen evolution reaction (HER/OER) mechanisms while addressing the persistent activity-stability trade-off. This review summarizes their decade-long progress in developing advanced electrodes, analyzing the origins of sluggish alkaline HER kinetics and OER stability limitations. Professor Wei proposes a unifying “12345 Principle” as an optimization framework. For HER electrocatalysts, they have identified that metal/metal oxide interfaces create synergistic “chimney effect” and “local electric field enhancement effect”, enhancing selective …

Local Electric Fields Coupled With Cl− Fixation Strategy For Improving Seawater Oxygen Reduction Reaction Performance, Yu-Rong Liu, Miao Zhang, Yan-Hui Yu, Ya-Lin Liu, Jing Li, Xiao-Dong Shi, Zhen-Ye Kang, Dao-Xiong Wu, Peng Rao, Ying Liang, Xin-Long Tian

Journal of Electrochemistry

Development of robust electrocatalyst for oxygen reduction reaction (ORR) in a seawater electrolyte is the key to realize seawater electrolyte-based zinc-air batteries (SZABs). Herein, constructing a local electric field coupled with chloride ions (Cl⁻) fixation strategy in dual single-atom catalysts (DSACs) was proposed, and the resultant catalyst delivered considerable ORR performance in a seawater electrolyte, with a high half-wave potential (E_1/2) of 0.868 V and a good maximum power density (Pmax) of 182 mW·cm⁻² in the assembled SZABs, much higher than those of the Pt/C catalyst (E_1/2: 0.846 V; Pmax: 150 mW·cm^{−2 …}

Pendant Micro-Droplet Evaporation Fabricates Fiber-Optic Mof Gas Sensor In Seconds, Abhishek Prakash Hungund, Bohong Zhang, Narasimman Subramaniyam, Thomas Spudich, Ryan O'Malley, Farhan Mumtaz, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

The development of photonic-based gas sensors using metal–organic frameworks (MOFs) and other microporous solids is often a multistep, complex process, typically involving MOF synthesis, purification, and attachment of microcrystals to an optical fiber end face. This study introduces a one-step method that integrates MOF synthesis and sensor head fabrication directly onto the fiber end face, forming an extrinsic Fabry–Perot interferometer (EFPI) with a thin film of MOF microcrystals. The resulting film, only 3–10-μm-thick, enhances sensor response by enabling rapid gas detection within seconds. Utilizing a pendant micro-droplet evaporation technique, this method forms a microporous MOF layer in situ, allowing unreacted …

Experimental Study Of Energy Conversion Efficiency Improvement Of Photovoltaic (Pv) Module Using Hybrid Cooling System, Olufisayo O. Babalola, Olatunji W. Olademeji, Joseph B. Samson

Al-Bahir

The elevation of the photovoltaic module operating temperature resulting in diminution of its energy conversion efficiency is one of the key limitations to its application. A decrease of power delivered performance by 0.4-0.5% per 1 rise over its Standard Test Condition (STC) accounted for the overheating of the PV module. This study evaluates the energy conversion efficiency improvement of a PV module using hybrid cooling system. An hourly segmented hybrid cooling system made up of aluminum fins as passive cooling segment and helical structured copper tubules for water conduction as active cooling segment helps to improve the energy conversion efficiency …

Robust Fault Detection And Classification In Power Systems Via Physics-Informed And Data-Driven Learning, Biswash Basnet, Varsha Sen

Graduate Student Scholarship

Electrical faults in power transmission systems can severely affect grid stability, equipment safety, and operational reliability. Traditional protection schemes, particularly distance relays, depend on apparent impedance computation that changes with error, creating a risk of misclassification. The results from relay overreach, underreach, or complete maloperation due to CT/PT saturation lead to developing problems in high impedance situations. These limitations highlight the need for adaptive, data-driven alternatives. This paper proposes an intelligent fault detection and classification model based on supervised machine learning techniques that overcome these challenges. The system’s robustness was validated under different training sizes and Gaussian noise levels, demonstrating …

An Event-Based Time-Incremented Snn Architecture Supporting Energy-Efficient Device Classification, David L. Weathers, Michael A. Temple, Brett J. Borghetti

Faculty Publications

Recent advances in Radio Frequency (RF)-based device classification have shown promise in enabling secure and efficient wireless communications. However, the energy efficiency and low-latency processing capabilities of neuromorphic computing have yet to be fully leveraged in this domain. This paper is a first step toward enabling an end-to-end neuromorphic system for RF device classification, specifically supporting development of a neuromorphic classifier that enforces temporal causality without requiring non-neuromorphic classifier pre-training. This Spiking Neural Network (SNN) classifier streamlines the development of an end-to-end neuromorphic device classification system, further expanding the energy efficiency gains of neuromorphic processing to the realm of RF …

Enhancement Of The Received Signal Strength In Smart Grid Communication Systems, Doaa Talaat Elsherbiny, Mona Mohamed Shokair Prof., Mohamed Shalaby, Salah Elden Khamis, Sameh A. Napoleon

Journal of Engineering Research

Smart grids are networks that contain intelligence from the generation stage to the distribution stage. These grids can actually have excellent power efficiency and automated control thanks to intelligence. Within smart grids, the communication mechanism is a crucial area of study. There should be a dependable communication system in the smart grid. A comprehensive mathematical model for a communication system within smart grids is derived in this work. Additionally, the simulation findings validate the mathematical model that was derived. Additionally, experiments are being conducted to apply polar convolutional parallel code PCPC to enhance the performance of the suggested communication system. …

Design And Performance Analysis Of A Frequency-Reconfigurable Rectangular Patch Antenna With Dual-Slot Defected Ground Structure For Gsm Band, Sara Abdelbaset, Ashraf Khalaf, Amr Hussien, Ahmed A. Kabeel

Journal of Engineering Research

In this paper, an innovative frequency-tunable rectangular patch antenna is presented, featuring interlaced circular and U-shaped narrow slots, combined with a rectangular-shaped defected ground structure (DGS). This design is specifically developed to produce radiation patterns similar to those of traditional dipole antennas. The integration of the rectangular DGS with three RF varactor diodes, along with two equivalent microstrip conductors, enables a tunable operating frequency band that ranges from 1.08 GHz to 1.7 GHz, achieving a total bandwidth of 0.62 GHz. The DC biasing network connected to the three RF varactor diodes is utilized to finely tune and adjust the resonance …

Developing Workflows For Passive Acoustic Detection Of Bedload Transport, Quinn Morgan

Dissertations and Theses

Bedload transport is defined as the amount of sediment, including gravel and rocks, traveling down stream. Monitoring bedload transport is important for river safety, hydrological studies and conservation efforts. Existing methods of directly measuring bedload transport (or bedload flux) involve lowering a collection device into a river and measuring the sediment collected; which can be expensive and time consuming. Hydroacoustic sensors, such as hydrophones, have had success tracking bedload flux remotely. This works by measuring the relatively high frequency of sediment impacts to map onto total bedload transported. No perfected method for detection of sediment generated noise (SGN) currently exists. …

Underwater Acoustic Integrated Sensing And Communication: A Spatio-Temporal Freshness For Intelligent Resource Prioritization, Ananya Hazarika, Mehdi Rahmati

Electrical and Computer Engineering Faculty Publications

Underwater acoustic communication faces significant challenges including limited bandwidth, high propagation delays, severe multipath fading, and stringent energy constraints. While integrated sensing and communication (ISAC) has shown promise in radio frequency systems, its adaptation to underwater environments remains challenging due to the unique acoustic channel characteristics and the inadequacy of traditional delay-based performance metrics that fail to capture the spatio-temporal value of information in dynamic underwater scenarios. This paper presents a comprehensive underwater ISAC framework centered on a novel Spatio-Temporal Information-Theoretic Freshness metric that fundamentally transforms resource allocation from delay minimization to value maximization. Unlike conventional approaches that treat all …