Electrical and Computer Engineering Commons^™

Laser-Based Optical Communications For Spacecraft Information Transfer, Ibrahim Arnous

Discovery Day - Daytona Beach

This course-based, in-progress project explores optical communications as a spacecraft subsystem and examines how light-based systems can be used to transmit information in space. As modern missions demand faster and more efficient data transfer, optical communications have emerged as an important area of interest alongside traditional communication methods. The purpose of this project is to study the role of optical communication in spacecraft design, with attention to its principles, advantages, limitations, and broader relevance to future missions. Using a comparative and research-based approach, the project investigates how these systems function, what engineering challenges they introduce, and why they are becoming …

Visualizing The Invisible: Simulating Electromagnetic Field In 3d Space With Matlab, Aashman Gupta, Eliane Dean, Riley Esperanca, Hailey Grabinski, Jacob Summerhays, Ameya Sute

Discovery Day - Daytona Beach

Electromagnetic field behaviours in free space are defined by Maxwell’s Equations, which couple the temporal and spatial variations of electric and magnetic fields through partial derivatives. These derivatives quantify the rate of change of each field’s vector component with respect to position and time in a 3D lattice, forming the basis for numerical field analysis. This research will develop a mathematical and computational framework using multivariable calculus to model, simulate, and visualize electromagnetic wave propagation in free space using MATLAB. Gradient, divergence, and curl operations are implemented to compute local field variations and energy transfer. The resulting data are used …

The Use Of Machine Learning Models For Predicting The Dielectric Strength Of Gases, Matthew Mileski, Paul W. Groth, Timothy S. Wolfe, Adib J. Samin

Faculty Publications

Technological advancements in high voltage systems have pushed sulfur hexafluoride (SF6) to its operational limits. Furthermore, this gas has other drawbacks including a high liquefaction temperature and a high global warming potential. Therefore, there has been an urgent need to find alternative gases with high dielectric strength (DS). In this work, density functional theory (DFT) is used to calculate molecular descriptors that are fed into an artificial neural network (ANN) and a random forest (RF). These machine learning (ML) models are then used to predict the DS for hundreds of molecules. A finite element model (FEM) is also used to …

Enhancing A Mid-Wave Infrared Fourier Transform Hyperspectral Imager For Explosions, James T. Stofel, Kody A. Wilson, Martin Larivière-Bastien, Anthony L. Franz, Michael L. Dexter

Faculty Publications

Capturing reliable hyperspectral imager data at a meaningful frame rate for explosions and other fast-changing scenes is not possible in the mid-wave infrared region under traditional sensor operating configurations and processing techniques, which typically have frame rates on the order of 0.5–2.0 Hz. To combat these shortcomings, the scene acquisition parameters were tailored for explosions and a new method for processing optical signatures of fast transient scenes with Fourier-transform infrared hyperspectral imagers was developed. For this technique, the instrument was first configured to collect asymmetric interferograms while optimizing the number of measurement points on the short side of the interferogram. …

Modeling And Simulation Of Solar Battery Charge Controller Using Adaptive Particle Swarm Optimization Mppt Algorithm, Mustafa Sacid Endiz, Göksel Gökkus

Mathematical Modelling and Numerical Simulation with Applications

Implementing an effective Maximum Power Point Tracking method is crucial for optimizing solar energy harvesting against environmental fluctuations like solar radiation and temperature. This paper introduces a novel approach for modeling and simulating a solar battery charge controller, using a modified Particle Swarm Optimization algorithm. The power stage of the system is based on a SEPIC converter, which is employed to manage the power conversion and improve the energy transfer to the battery. The developed circuit model is evaluated under various radiation levels at a constant temperature, as well as under different temperature levels at a constant radiation. Simulations are …

Modeling Formation Of Turbulent Sporadic-E Clouds Using Realistic Wind Data, Aaron M. Schinder, Kenneth S. Obenberger, Jorge L. Chau, Juan M. Urco, Matthias Clahsen, Benjamin F. Akers, Daniel J. Emmons

Faculty Publications

A high resolution two-dimensional multi-fluid model of sporadic-E layers was developed and driven with physically realistic mesosphere, lower thermosphere (MLT) winds measured over Albuquerque, New Mexico. The realistic E-region winds are produced by the HYdrodynamic Point-wise Environment Reconstructor (HYPER) model that ingests meteor derived wind observations from a Spread-spectrum Interferometric Multistatic meteor radar Observing Network (SIMONe) system combined with the Navier-Stokes equations to provide high resolution three-dimensional wind fields over time. Sporadic-E dynamics are simulated using both realistic winds from HYPER as well as idealized hyperbolic tangent windshears to compare and contrast. Overall, the model shows greater inhomogeneity and irregularity …

Linear Relationships Of Gibbs Free Energy For Rare Earth Element Oxide, Hydroxide, Chloride, Fluoride, Carbonate, Ferrite, And Zirconate Minerals And Crystalline Solids, Ruiguang Pan, Alexander P. Gysi, Artaches A. Migdisov, Nicole C. Hurtig, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

Rare Earth Elements (REE) are classified as critical minerals and materials essential for the transition from fossil fuels to renewable and clean energy. Accurate thermodynamic properties of REE minerals and other crystalline solids are crucial for geochemical modeling of REE speciation, solubility, and transport in ore deposits and for extraction, chemical processing, and recycling. However, the standard Gibbs free energy of formation (∆Gof,REEX) for these solids vary by 10s kJ mol−1 across different sources from literature. We applied the Sverjensky linear free energy relationship (LFER) to evaluate internal consistency for isostructural REE solid groups and predicted ∆Gof values for solid …

Single Fluorogens And Orientation-Localization Microscopy For Quantifying Chemical And Biomolecular Dynamics At The Nanoscale, Yiyang Chen, Yuanxin Qiu, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Many chemical systems look uniform only because ensemble measurements average over their most interesting molecules. Electron-transfer rates vary across electrode surfaces; lipid membranes contain nanodomains with distinct packing and fluidity; peptide aggregates exhibit local polymorphism; and biomolecular condensates contain transient networks of interactions that are blurred in ensemble images. A central challenge in chemical imaging is not simply to see smaller structures, but to measure chemical variables such as polarity, redox potential, and molecular confinement at the single-molecule level. In this Account, we describe how fluorogens, molecules whose brightness, blinking, spectral shifts, orientation, rotational mobility, and motion are directly shaped …

Ensemble Learning Framework For Predicting Close Proximity Tire–Pavement Noise On Expressways, Woo Young Cho, Jin Hwan Kim, Guk Gon Song, Kyungnam Kim, Youngguk Seo

Faculty Articles

Traffic noise is a critical public health concern affecting millions of highway users and adjacent residents worldwide. In response, many transportation agencies have adopted functional surface materials to reduce noise at the source on pavement, but assessing their effectiveness remains expensive and logistically challenging. Close Proximity (CPX) testing quantifies tire-pavement noise but requires specialized equipment costing $50,000-$126,000 and is limited to existing pavement, preventing proactive noise assessment during pavement design. This study develops machine learning models to predict CPX noise levels from readily available pavement characteristics, eliminating the need for costly tests during design and planning phases. To train and …

From Homogeneous To Heterogeneous Adaptive Bounded-Confidence Opinion Dynamics On Networks, Sally Hafez, Fatma R. Farag, Amira S. N. Tawadros

Northeast Journal of Complex Systems (NEJCS)

Adaptive bounded-confidence models (ABCMs) elucidate the coevolution of agent states and network structure via local interactions and rewiring mechanisms. Traditional formulations assume uniform interaction parameters, leading to distinct regime shifts encompassing fragmentation, polarization, and consensus. A symmetric heterogeneous extension of the adaptive bounded-confidence model is introduced, in which interaction parameters vary according to whether agents belong to the same or different groups. The model retains the original update and rewiring protocols but integrates within-group and between-group confidence bounds alongside tolerance thresholds. Initially, the classic homogeneous model is replicated to establish a reference point. Subsequently, the heterogeneous extension is assessed under …

Automated Battery Management Systems For Electric Vehicles, Woonki Na, Yuanyuan Xie

Mineta Transportation Institute

Electric vehicle (EV) safety, efficiency, and lifetime are strongly influenced by how well battery cells are managed, and as EV adoption accelerates, improving battery performance has become critical to vehicle reliability, cost, and public trust. This report conducts a field study on the core technologies and challenges in Battery Management Systems (BMS), focusing on the classification of BMS circuit topologies (design/structures) and systematically reviewing different topologies of active cell balancing circuits (systems that move energy from stronger battery cells to weaker ones). The study provides a detailed analysis of the working principles, advantages, and disadvantages of various active balancing circuit …

Evaluation Of General Voronoi Diagram Decomposition For Harmonic Fields In Navigation Of Dynamic Environments, Franco Abullarade

Master's Theses

Harmonic potential fields provide provably minimum-free navigation, but any change to the workspace geometry invalidates the field and forces a costly global recomputation, typically restricting them to static environments. This thesis extends the harmonic map framework of Vlantis et al., which maps the free workspace onto a unit disk and uses an atlas of per-region transformations, to dynamic indoor settings. First, we replace their manually annotated room partition with an automatic decomposition based on the Generalized Voronoi Diagram, allowing the atlas to be built from an arbitrary occupancy grid in an automated way. Second, we introduce a localized repair procedure …

Hardware-In-The-Loop Evaluation Of Sensor-Source Selection For Prosthetic Locomotion Intent Recognition, Victoria Asencio-Clemens

Master's Theses

Active lower-limb prostheses use intent-recognition systems to identify a user’s locomotion mode and select an appropriate control strategy, but sensor configurations that perform well offline may be unsuitable for resource-constrained embedded hardware. Existing sensor-selection methods generally prioritize classification accuracy without directly accounting for processing latency, memory usage, or other hardware-dependent requirements. To address this limitation, this thesis develops a hardware-in-the-loop source-selection framework for embedded classification of level walking, ramp ascent, ramp descent, stair ascent, and stair descent using multimodal biomechanical data from transtibial amputee participants. Subject-specific linear support vector machine classifiers were evaluated using trial-held-out validation, and candidate configurations from …

Integrated Power, Energy, And Thermal Management For Autonomous Hybrid Off-Road Vehicles: Multi-Timescale Modeling, Predictive Control, And Resilient Thermal Design, Anirudh Sundar

All Dissertations

Electrification and autonomy are increasingly important for off-road vehicles operating in construction, agriculture, mining, defense, and other demanding environments. These platforms must deliver high tractive power under unstructured terrain, harsh ambient conditions, low-speed operation, and large auxiliary loads. While hybrid and electrified powertrains offer improved efficiency, mobility, and auxiliary power capability, they also introduce significant challenges in managing tightly coupled power, energy, and thermal subsystems. In particular, lithium-ion batteries, power electronics, electric machines, and internal combustion engine-generator systems operate across different temperature limits and timescales, requiring coordinated management to ensure efficiency, durability, and safe operation. This dissertation develops modeling, planning, …

Policy And Regulation In Virtual Power Plants Development, Hemlal Bhattarai, Aziz, Stefan Lachowicz

Research outputs 2022 to 2026

Electricity systems are changing due to the rapid deployment of distributed energy resources (DER), which also presents significant regulatory obstacles to their coordinated integration into energy markets and power grids. However, the majority of current material in publications concentrate on operational optimization and technical architectures, with little systematic synthesis of the legal and policy frameworks governing the deployment of VPP on a broad scale. To provide grid services, improve flexibility and support decarbonization objectives, virtual power plants (VPP) have become a crucial aggregation method. To close this gap, this research critically looks at the institutional roles, market structures, global policy …

Optimization Of A Cryogenic Electrical Characterization System And Its Application To Thermal Admittance Spectroscopy, Angel Efren Garcia

Open Access Theses & Dissertations

Defect characterization in semiconductors relies on locating trap levels through the temperature dependence of carrier emission, which makes the accuracy of the device temperature a limiting factor in every extracted parameter. This work addresses the limitations in the cryogenic electrical characterization system at The University of Texas at El Paso, where Deep-Level Transient Spectroscopy (DLTS) had been established but produced activation energies that disagreed with literature values by as much as 0.33 eV. The discrepancy was traced not to the technique but to the transfer of heat to packaged devices in a probe station designed for on-die measurement. The cryogenic …

Efficient And Scalable Visual Computing For Nanoscale Imaging, Hao Wang

All Dissertations

Nanoscale analysis often relies on instrument-mediated scientific imaging methods to capture visual signals that are difficult to observe, interpret, or quantify through ordinary perception alone. These domains are often characterized by low signal quality, limited annotations, complex morphology, non-natural visual statistics, and strong dependence on physical acquisition processes. This dissertation focuses on efficient visual computing for nanoscale imaging, with an emphasis on the representation, reconstruction, and analysis of high-resolution scientific visual data. In our early work, we relied on rule-based algorithms and conventional machine learning methods for feature extraction. However, these approaches struggle to scale with the increasing complexity and …

Thermal Rating And Prediction Of Roadway-Embedded Power Electronics For Dynamic Wireless Power Transfer, Forrest D. Nichols

All Graduate Theses and Dissertations, Fall 2023 to Present

Electric vehicles can be charged while driving through wireless charging coils buried in the road surface. To avoid running expensive cables from roadside equipment to each charging pad, the electronics that control the power transfer can also be buried in the road. However, burying these circuit boards removes the ability to cool them with fans or flowing air, so the heat generated during operation must escape naturally into the surrounding road material. If the boards get too hot, components fail—a problem that has already been observed in prototype systems.

Predicting how hot each component on a circuit board will get …

Electrical Characterization Of Wide-Bandgap Devices Via Laboratory Measurements, Tcad Simulation, And Analytical Modeling, Sebastian Alessandro Mimbela

Open Access Theses & Dissertations

Gallium nitride (GaN) devices are important for high-power, high-frequency, and harsh-environment applications because of their wide bandgap, high breakdown capability, and electrical performance. This thesis focuses on the electrical characterization of GaN-based devices using laboratory measurements, analytical modeling, and TCAD simulation. Current-voltage (I-V) and capacitance-voltage (C-V) measurements were performed on a GaN Schottky diode. The measured data were analyzed to extract key parameters such as ideality factor, Schottky barrier height, series resistance, donor concentration, built-in potential, depletion width, and maximum electric field. A TCAD process was also developed in Synopsys Sentaurus to recreate the main geometry, layer structure, contacts, and …

Macroscopic Classical And Quantum Models Of Inverse Compton Scattering, Emerson Penn Rogers

Physics Theses & Dissertations

Inverse Compton sources — in which a relativistic electron beam scatters a laser pulse to produce tunable, collimated, high-energy radiation—have emerged as among the most promising compact radiation sources, with applications ranging from nuclear photonics to medical and nanoscale imaging and metrology. The most viable current tabletop configuration couples laser-wakefield acceleration with inverse Compton scattering, producing GeV-scale electron beams over millimeter distances. As laser intensities increase and electron energies grow, the interaction enters the radiation reaction regime, where the energy radiated by the electron becomes a significant fraction of its kinetic energy. Predicting the scattered electron energy spectrum — the …

Enhancing Stem Education With Modeling, Simulation, And Ai Technologies: From Virtual Laboratories To Intelligent Teaching Assistants, Yiyang Li

Electrical & Computer Engineering Theses & Dissertations

Rapid advancements in modeling and simulation (M&S) and artificial intelligence (AI) present new opportunities to enhance various aspects of STEM education, from virtual laboratories that simulate physical lab environments in software to intelligent teaching assistants that provide on-demand, curriculum-aligned instructional support. Virtual laboratories offer a potential solution to the access and scalability challenges of laboratory courses by allowing students to conduct experiments without physical equipment or geographical constraints. AI-powered teaching assistants, particularly those grounded in course-specific materials, can help mitigate the instructional support gap that arises when students work independently in digital learning environments. This dissertation presents three-phase research into …

Experimental Investigation Of The Discharge Modes Of Nanosecond Pulsed Plasmas At Atmospheric Pressure, Md Ziaur Rahman

Electrical & Computer Engineering Theses & Dissertations

The generation of repeatable and stable nanosecond pulsed atmospheric pressure plasmas is important to non-thermal plasma applications in various fields including medicine, material processing, food processing, and plasma ignition for combustion. This dissertation investigates the atmospheric pressure plasma initiation and formation under 10 – 200 ns pulsed power for electrode configurations applicable for transient plasma ignition (TPI) for combustion. The impacts of pulsed power parameters, gas condition, and electrode geometry on the discharge initiation and modes (i.e., streamer, transient spark and spark) are systematically evaluated for applying TPI for combustion. We evaluated the discharge modes driven by both longer and …

Deep Multimodal Sensor Fusion For Autonomous Driving: A Real-World Deployment On Little Blue, Raphael T. Pamie-George

Electrical & Computer Engineering Theses & Dissertations

Accurate perception and control systems are essential for autonomous vehicles to safely interpret and navigate complex environments. Individual sensing modalities such as cameras, LiDAR, and inertial measurement units (IMUs) provide valuable environmental and vehicle state information; however, each sensor exhibits inherent limitations when used independently. Camera performance can degrade under varying lighting conditions, LiDAR measurements may be sparse or affected by environmental noise, and IMU measurements are susceptible to drift over time. Little Blue, a research autonomous vehicle platform from ODU (Old Dominion University), previously relied primarily on camera-based data for neural network training, limiting the system’s ability to exploit …

Parameter Dependent Chen-Fliess Series And Their Nonrecursive Interconnections, Natalie T. Pham

Electrical & Computer Engineering Theses & Dissertations

In control theory, a Chen-Fliess functional series is a weighted sum of iterated integrals constructed from a given set of input functions. Such series can be used to represent nonlinear input-output systems. In applications, they have been employed to characterize interconnected nonlinear systems, to solve system inversion and tracking problems, and to design predictive and adaptive controllers.

Distributed parameter systems exhibit spatial dependence along with temporal dependence. Such systems are typically represented in terms of partial differential equations. In control theory, there appears to be no existing method for representing the input-output map of a distributed system via a Chen-Fliess …

Modulating Linear Frequency Modulated Pulses To Send Communications Data In A Bistatic Sar Scenario, Jarren T. Worthen

All Graduate Theses and Dissertations, Fall 2023 to Present

Synthetic aperture radar (SAR) is the technology that enables the creation of images using radar waves, allowing images to be formed regardless of weather. In bistatic SAR a radar platform uses a radar pulse from a separate platform to form an image. It is important that these radar systems are able to communicate with each other. Rather than wasting energy and space flying with a separate communication system, the radar systems could use the already existing SAR system to send data between each other while still forming SAR images. The work of this thesis is to show how very simple …

Modeling Power Distribution Architectures And Maintaining Constant Power With Misalignment In Dynamic Wireless Charging Systems For Electric Vehicles, Mayank Chawla

All Graduate Theses and Dissertations, Fall 2023 to Present

With increasing demand for wireless power transfer systems from phone charging and medical devices, in-motion wireless charging of electric vehicles offers a unique advantage of charging the vehicle while in motion on an electrified roadway. Compared to the stationary or wired charging, electric vehicle users can significantly save time and cost with a reduction in the battery size. However, with large-scale infrastructure required for a wireless charging roadway and the driver’s ability to align with the electrified roadway, come significant challenges for the practical implementation of in-motion wireless charging systems.This dissertation aims to solve some of the problems associated with …

Auction-Consensus Algorithms For Decentralized Task Allocation In Multi-Robot Systems, Jose Alberto Rodriguez

Theses and Dissertations

This thesis investigates methods for improving decentralized multi-robot task allocation (MRTA) through enhancements to auction-consensus coordination. The first contribution of this work introduces the Auction-Consensus Algorithm with Loss Mechanism (ACALM), a deterministic extension that incorporates loss-aware bidding. Through dynamic loss propagation, agents rebid in a manner that better reflects global coordination impact under the Single-Task Robot, Single-Robot Task, Instantaneous Assignment (ST-SR-IA) assumptions. The second contribution replaces handcrafted bidding rules with learned neural bidding policies trained under a centralized training with decentralized execution framework. Using reinforcement learning, agents learn cooperative bidding strategies that improve allocation quality under the Multi-Task Robot, Single-Robot …

Synergizing Crowd Collaboration: Enhancing Crowdsourcing Matching Via Integration Of Matching Theory And Coalition Games, Rowan Aengus Kinney

Electrical and Computer Engineering ETDs

This paper tackles the challenges inherent in crowdsourcing dynamics by introducing the CROWDMATCH mechanism. Aimed at enabling crowdworkers to strategically select suitable crowdsourcers while contributing information to crowdsourcing tasks, CROWDMATCH considers incentives, information availability and cost, and the decisions of fellow crowdworkers to model the utility functions for both the crowdworkers and the crowdsourcers. Specifically, the paper presents an initial Approximate CROWDMATCH mechanism grounded in matching theory principles, eliminating externalities from crowdworkers’ decisions and enabling each entity to maximize its utility. Subsequently, the Accurate CROWDMATCH mechanism is introduced, being initiated by the outcome of the Approximate CROWDMATCH mechanism, and employing …

Development Of Dynamic Proof-Mass Configurations For Broadband Piezoelectric Energy Harvesting, Nico E. Galarza

Electrical and Computer Engineering ETDs

The purpose of this thesis is to investigate and develop dynamic proof-mass configurations for broadband piezoelectric energy harvesting. Conventional piezoelectric energy harvesters are typically limited by narrow operating bandwidths, restricting their performance under variable-frequency excitation. This research presents the design, fabrication, and experimental evaluation of multiple proof-mass concepts intended to increase the usable frequency range of cantilever-based piezoelectric energy harvesters. Several dynamic mass configurations were developed using additive manufacturing techniques and integrated with commercially available piezoelectric cantilevers. Experimental testing was conducted under controlled vibration conditions to characterize voltage response, resonant behavior, and bandwidth performance. The results demonstrate that dynamic proof-masses …

Enhanced Computational Modeling Of Photoionization And Streamer Formation, Anahita Alibalazadeh

Electrical and Computer Engineering ETDs

Photoionization is a key mechanism governing the formation and propagation of streamer discharges in air by generating electron-ion pairs ahead of the streamer front. Accurate and computationally efficient modeling of this non-local process is essential for reliable plasma simulations. However, the widely used Zheleznyak photoionization model relies on empirical assumptions and requires computationally expensive domain-wide integration.

This dissertation advances photoionization modeling in three ways. First, the classical integral model is enhanced by incorporating experimentally measured vacuum ultraviolet (VUV) emission spectra together with photoabsorption and photoionization cross-section data, enabling direct calculation of the photoionization source term as a function of pressure …