Digital Commons Network^™

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 …

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 …

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 …

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 …

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 …

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 …

Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury

Dissertations

The environmental benefits of electric vehicle (EV) adoption depend on more than replacing internal combustion engine vehicles with electric powertrains. EV adoption reshapes electricity demand, interacts with regional generation mixes, and influences travel behavior and congestion, creating a coupled transportation-energy system in which vehicle and power-plant emissions must be evaluated together. This dissertation develops machine-learning frameworks for predicting energy consumption and emissions from vehicles and power grids under rising EV adoption. The first component forecasts grid emissions from EV charging. Using simulation data from NREL's Cambium database, a Prophet-based time-series framework predicts carbon dioxide, nitrous oxide, and methane emission rates …

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 …

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 …

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 …

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 …

Simulations Of Atmospheric Pressure Streamer Discharges: Mechanisms Of Streamer Propagation And Related Physics, Dejan Nikic

Electrical and Computer Engineering ETDs

Gas discharge simulations are performed with particular focus on photoionization process in a positive streamer discharge. The effects of this process are investigated by isolating the change in photoionization mean free path (MFP) and keeping the additional processes constant. Furthermore, comparison are made between various effects of simulation parameters, such as initial conditions, geometry extent, simula- tion particle count etc. All of these simulations are performed using a modern Direct Simulation Monte Carlo Particle-in-Cell (DSMC-PIC) code developed by Sandia Na- tional Laboratories. Large scale simulations including 1 cm and 5 cm electrode gaps are performed under standard atmospheric condition air. …

Computationally Tractable Methods For Constrained Optimal Control And Reachability Analysis Of Nonlinear Stochastic Dynamical Systems, Karthik Sivaramakrishnan

Electrical and Computer Engineering ETDs

Autonomous systems operating in uncertain environments require methods that can rigorously quantify safety, predict future behavior, and compute optimal decisions tractably. The unifying challenge is reasoning about uncertainty propagation in constrained dynamical systems. Motivated by autonomous spacecraft inspection, this dissertation develops model-based and data-driven methods for stochastic optimal control and stochastic reachability. First, it studies optimal on-orbit inspection of an uncertain tumbling spacecraft in both single-agent and multi-agent settings, and derives computationally efficient reformulations for exploring trade-offs among sensing, trajectory deviation, and fuel use. Second, it develops a probabilistically safe penalty-based reinforcement learning method that preserves gradient information during training …

Dynamic Reconstruction Engineering Of Anti-Corrosion Ni-Based Anodes For Alkaline Seawater Electrolysis, Yi-Gang Zhang, Wen-Wen Xu, Tian-Yu Zhang, Zhi-Yi Lu

Journal of Electrochemistry

Green hydrogen production via alkaline seawater electrolysis offers an environmentally sustainable and potentially cost-effective route to address both energy and climate challenges. Achieving long-term anode stability under complex ionic environments and industrial current densities remains a central bottleneck. Specifically, Ni-based anodes exhibit intense surface reconstruction during the oxygen evolution reaction, necessitating dynamic anti-corrosion strategies. This mini review systematically summarizes reconstruction engineering approaches to develop anti-corrosion Ni-based anodes of alkaline seawater electrolysis across increasingly complex ionic environments from simulated seawater to real seawater: (i) Cl^– dominated; (ii) Cl^– with co-existing oxyanions, and (iii) Cl^–  with co-existing Br^{– …}

Preparation And Performance Study Of In-Situ Self-Assembled Biphasic Smmn2O5-Nimn2O4 Composite Cathode, Neng-Chu Xia, Yu Zhou, Qin Wang, Jia-You Zhang, Chun Yu, Yang Zhang, Wan-Bing Guan, Jian-Xin Wang

Journal of Electrochemistry

Mullite-structured oxides exhibit excellent oxygen reduction reaction activity, possess a low thermal expansion coefficient due to their unique crystal structure, and can eliminate the need for a barrier layer and simplify the preparation process as they contain no alkaline earth elements. Thus, they hold great promise as novel cathode materials for solid oxide fuel cells. In this work, a mullite-spinel-structured SmMn₂O₅-NiMn₂O₄ (SMO-NMO) composite cathode was one-step synthesized via a solid-liquid composite route, and its in-situ self-assembly enabled good compatibility with the electrolyte without any barrier layer. Characterization results showed that the SMO:NMO = …

3d Electromagnetic Simulations Of A 1.6 Cell S-Band Photoinjector: Emittance Studies For Electron Microscopy, Trudy Bolin

Electrical and Computer Engineering ETDs

Modern beam-based materials research demands electron sources with increasingly precise time resolution, high brightness, and stability. For example, there are various instruments across the U.S. dedicated to ultrafast electron diffraction (UED), but fewer are dedicated to ultrafast electron microscopy (UEM), which demands beam stability. Modeling femtosecond electron bunches with ultra-low emittance < 50 nm-rad inside a 1.6-cell S-band (2856 MHz) rf photoinjector with full 3D electromagnetic simulations can require high-performance computing (HPC) environments due to the scale disparity between the macroscopic cavity geometry and the femtosecond-scale bunch kinematics. To enable optimization in a desktop computing environment, this work presents a streamlined 3D electromagnetic Particle-in-Cell (PIC) simulation framework optimized for 400-femtosecond bunch regimes. The covariance method was employed to study emittance properties for electron bunch counts ranging from thousands to millions and has successfully resolved highly transient, pure rf phase-space rotations, such as a localized energy-spread minimum occurring at the gun exit iris. To overcome the computational cost of these simulations, a machine-learning-based Bayesian optimization approach was deployed to construct multi-objective Pareto fronts from sparse datasets. Because the simulation software is scalable from desktop to HPC facilities, the framework is ready for experiments at the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory (LBNL).

Real-Time Waveform Synthesis For Rfsoc-Based Quantum Control Systems, Tiamike I. Dudley

Electrical and Computer Engineering ETDs

RFSoCs are gaining adoption in many labs for quantum control systems thanks to their compactness and affordability. Making full use of the many components on an RFSoC evaluation board is a challenging engineering problem that must be solved to realize scalable control systems. In this dissertation, I evaluate the performance of various RFSoC components in the context of quantum information science. I present two custom FPGA engines that accelerate and parallelize arbitrary waveform generation. The first engine can be instantiated many times to power low-speed DACs for ion-shuttling trap electrodes. The second engine synthesizes CPMG-XY8n dynamical decoupling pulse sequences on …

Modeling For You: A Personalized Approach To Residential Energy Simulation And Distributional Reinforcement Learning, Nestor Gabriel Pereira

Electrical and Computer Engineering ETDs

The growing complexity and uncertainty of residential energy use, driven by electric

vehicles and renewable technologies, demand more intelligent and robust

management systems. Traditional methods often fail when faced with unpredictable

electricity prices and user behavior. This dissertation addresses this gap by presenting

a novel personalized framework combining detailed household energy modeling with

a risk-aware reinforcement learning agent for appliance scheduling.

The first contribution is a probabilistic, bottom-up simulation model that captures

the interdependent behaviors of occupants, appliances, and electric vehicles to

generate realistic, high-fidelity load profiles. The second contribution is a lightweight,

tabular Distributional Q-Learning (D-QL) algorithm that schedules …

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 …

Development Of Proposed Airworthiness Certification Criteria For Interference-Tolerant Radio Altimeter Systems, Matheus B. Furstenberger

Student Works

Radio altimeters provide height-above-ground information to flight deck displays and multiple safety-critical aircraft systems, however legacy certification standards were not developed for high-power terrestrial wireless services operating in adjacent C-Band spectrum. This study addressed the absence of a consolidated airworthiness certification framework for interference-tolerant radio altimeter systems installed on Title 14 Code of Federal Regulations Part 25 transport category airplanes. An archival research synthesis was conducted using publicly available regulations, proposed and final rules, technical standard orders, advisory circulars, airworthiness directives, industry standards, spectrum-management documents, technical studies, and stakeholder comments. Qualitative content analysis and source triangulation were used to identify …

Sustainable Consumer Behavior Modeling: A Complex-Systems Approach To Neuromarketing, Preethi Nanjundan, Nupoor Sanjay Bhute, Ragini Topre, Lijo Thomas

Northeast Journal of Complex Systems (NEJCS)

This study examines the application of complex-systems modeling to neuromarketing data for gaining deeper insights into the mechanisms underlying sustainable consumer behavior. It investigates how neural and biometric responses, interpreted through a systems-based perspective, can uncover dynamic interactions, feedback mechanisms, and emergent behavioral patterns influencing sustainable purchase decisions. The research explores the impact of sustainability-oriented marketing stimuli on long-term behavioral intentions by emphasizing the interconnected roles of cognitive processing, emotional engagement, implicit associations, and collective consumer dynamics. Through simulation-based modeling and structural analysis, the study demonstrates how subconscious neural responses and affective mechanisms mediate the relationship between marketing interventions, consumer …

Policy Reflections On Promoting Strategic Oriented Basic Research In China: Insights From The U. S. Department Of Energy’S Basic Research Funding System, You Yu, Yun Liu, Wenneng Zhou

Bulletin of Chinese Academy of Sciences (Chinese Version)

Strategy-oriented basic research is a key pathway to driving major original breakthroughs at the frontiers of science, serving national strategic needs, and securing a leading position in global science and technology. It is also a vital pillar for achieving high-level self-reliance and self-strengthening in science and technology and enhancing the capacity for original innovation. Faced with the urgent need to build a science and technology powerhouse and achieve breakthroughs in key core technologies, China has gradually improved its organizational framework for advancing strategy-oriented basic research and has established a solid foundation for policy support and resource allocation. Nevertheless, when measured …

Provocable Forgiveness In Noisy Brand--Consumer Systems:An Agent-Based Study Of Repeated Interaction, Tahere Ahmadiyan, Hamidreza Navidi, Behbod Keshavarzi

Northeast Journal of Complex Systems (NEJCS)

Repeated brand--consumer exchange is often treated as a managerial problem of loyalty, recovery, and trust. It can also be read as a small complex system: many local decisions about cooperation, retaliation, and forgiveness accumulate into market-level selection. This study uses that perspective to examine which relational rules survive when communication is imperfect. Eight canonical Iterated Prisoner's Dilemma strategies are translated into marketing archetypes and evaluated through round-robin tournaments, a six-level noise sweep, proportional-fitness ecological dynamics, and finite-population Moran invasion tests. The tournament leaderboard is calculated without same-strategy self-play, so that reported payoffs reflect inter-archetype competition rather than homogeneous self-coordination. At …

Efficient Edge Implementation Of Midasnet For Real-Time Depth Estimation In Indoor Robotics, Muhammed Yasi̇n Adiyaman, İsmai̇l Fai̇k Başkaya

Turkish Journal of Electrical Engineering and Computer Sciences

Real-time depth estimation is crucial in many vision-related tasks, including autonomous driving, 3D reconstruction, robotics, and simultaneous localization and mapping. In recent years, many methods have been proposed to solve depth maps from images by utilizing different modality setups like monocular vision, binocular vision, or sensor fusion. However, for real-time deployment on edge devices, complex methods are not suitable due to latency constraints and limited computation capacity. For edge implementation, models should be simple, minimal in size, and hardware-friendly. Considering these factors, we implemented MiDaSNet, which works on the simplest setup of monocular vision and utilizes hardware-friendly convolutional neural network-based …

Evolutionary Neural Architecture Search: A Survey, Ferda Nur Özçeli̇k, Mehmet Önder Efe

Turkish Journal of Electrical Engineering and Computer Sciences

Deep Neural Networks (DNNs) have achieved remarkable success across diverse machine learning applications, yet designing effective architectures remains a laborious, expert-driven process. Neural Architecture Search (NAS) was introduced to automate this process, with Evolutionary NAS (ENAS) emerging as one of the most effective and widely adopted NAS paradigms. This survey provides a comprehensive and systematic review of 164 ENAS studies published between 2020 and 2024, categorized according to the specific evolutionary algorithm employed as the search strategy. Unlike prior surveys—which either treat evolutionary methods at a high level or focus on general NAS pipelines—this study is, to the best of …