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Full-Text Articles in Entire DC Network
Investigation Of Insertion Loss In Inkjet-Printed Coplanar Waveguide Based On Drying Temperature, Jun Ho Yu, Sung Min Sim, Jin Woo Choi, Sang Ho Lee, Jung Mu Kim
Investigation Of Insertion Loss In Inkjet-Printed Coplanar Waveguide Based On Drying Temperature, Jun Ho Yu, Sung Min Sim, Jin Woo Choi, Sang Ho Lee, Jung Mu Kim
Michigan Tech Publications
In this study, we propose an optimized inkjet printing process to improve the insertion loss of inkjet-printed coplanar waveguide (CPW) transmission lines. The process involves varying the drying temperature and adjusting the number of printing steps to investigate their effects on the electrical characteristics of the printed CPW. The relationships between surface roughness, surface cavities, morphological changes, and insertion loss are studied by conducting atomic force microscopy analysis and by examining the insertion loss up to 3 GHz. The printed CPW that underwent low-temperature drying after the first printing and high-temperature drying after the second printing before sintering showed improved …
Regulating Lithium Metal Nucleation And Growth For Dendrite Suppression: From Liquid-Electrolyte To Solid-State Batteries, Ao Du, Juan Zhang, Pan Xu, Ya-Jie Li, Kang-Yu Yi, Zhen-Zhen Shen, Hui-Lin Ge, Guang-Wen Zhang, Chao-Hui Zhang, Yu-Hao Wang, Chen-Zi Zhao, Meng-Yang Xu, Yu-Lin Jie, Rui Wen, Shu-Hong Jiao, Si-Qi Shi, Qiang Zhang, Chun-Peng Yang, Yu-Guo Guo
Regulating Lithium Metal Nucleation And Growth For Dendrite Suppression: From Liquid-Electrolyte To Solid-State Batteries, Ao Du, Juan Zhang, Pan Xu, Ya-Jie Li, Kang-Yu Yi, Zhen-Zhen Shen, Hui-Lin Ge, Guang-Wen Zhang, Chao-Hui Zhang, Yu-Hao Wang, Chen-Zi Zhao, Meng-Yang Xu, Yu-Lin Jie, Rui Wen, Shu-Hong Jiao, Si-Qi Shi, Qiang Zhang, Chun-Peng Yang, Yu-Guo Guo
Journal of Electrochemistry
Lithium metal anodes, with a theoretical capacity of up to 3860 mAh·g−1, are regarded as the cornerstone for developing next-generation high-energy-density batteries. However, several key challenges hinder their practical applications, including dendrite formation, unstable solid electrolyte interphase (SEI), side reactions with electrolytes, and associated safety risks. This review systematically explores the mechanisms of lithium nucleation, growth, and stripping in both liquid and solid-state battery systems, analyzing critical theoretical concepts like heterogeneous nucleation thermodynamics, surface diffusion kinetics, space charge effects, and SEI-induced nucleation, which are crucial for understanding the genesis of dendrite growth. Additionally, the review discusses the electrochemical-mechanical …
Evolving Towards Efficient Technologies In Power Systems: The Paradigm Of Energy Internet Survey, Dina Emad, Omar Abdel-Rahim, Tanemasa Asano, Sobhy M. Abdelkader
Evolving Towards Efficient Technologies In Power Systems: The Paradigm Of Energy Internet Survey, Dina Emad, Omar Abdel-Rahim, Tanemasa Asano, Sobhy M. Abdelkader
Mansoura Engineering Journal
The Energy Internet represents a significant advancement in the modernization and automation of electricity systems, offering a framework for future smart grids where all electrical devices are interconnected through energy routers. This system integrates advanced power electronics, information technology, and smart control technologies, enabling the accommodation of diverse energy sources and storage devices. With its bidirectional energy flow and sharing capabilities, the Energy Internet holds great promise for the future. However, several challenges must be addressed to fully realize this potential. This review provides an overview of the Energy Internet framework and explores key challenges, particularly those related to energy …
A Feature-Free Deep Learning Approach For Midair Hand Gesture Recognition From Surface Electromyogram (Semg) Data, Yasir Altaf, Abdul Wahid, Mudasir Manzoor Kirmani
A Feature-Free Deep Learning Approach For Midair Hand Gesture Recognition From Surface Electromyogram (Semg) Data, Yasir Altaf, Abdul Wahid, Mudasir Manzoor Kirmani
Turkish Journal of Electrical Engineering and Computer Sciences
Midair hand gesture recognition plays a crucial role in applications such as sign language recognition and human-computer interaction, particularly for supporting individuals with partial or complete hearing loss. However, recognizing gestures in midair remains challenging due to the rapid and complex nature of hand movements. To address this, noninvasive techniques like surface electromyography (sEMG)—which captures muscle activity through sensors placed on the skin—have gained attention. sEMG provides rich time-series data that reflect both spatial and temporal muscle dynamics. In this study, we propose a deep learning architecture that combines convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to classify …
Integrated Log Spectrogram Convolutional Neural Network (Ils-Cnn) For Robust Spoken Digit Recognition, Awais Ahmed
Integrated Log Spectrogram Convolutional Neural Network (Ils-Cnn) For Robust Spoken Digit Recognition, Awais Ahmed
Turkish Journal of Electrical Engineering and Computer Sciences
Spoken digit recognition (SDR), a type of supervised automatic speech recognition, is essential for various human-machine interaction applications, including banking operations, dialing systems, price extraction, and airline reservation systems. However, designing an effective SDR system presents several challenges, such as developing labeled audio data, selecting appropriate feature extraction methods, and creating high-performance models. To overcome these challenges, a novel approach for robust spoken digit recognition using an integrated log spectrogram convolutional neural network (ILS-CNN) has been proposed. The proposed work presents an efficient SDR method by taking advantage of a log spectrogram layer directly within the neural network to enhance …
Railway Track Condition Monitoring Based On Sensor Data And Artificial Neural Networks, Ivan Kots, Alina Isaeva, Mark Denisenko, Alexander Sinyukin, Andrey Kovalev
Railway Track Condition Monitoring Based On Sensor Data And Artificial Neural Networks, Ivan Kots, Alina Isaeva, Mark Denisenko, Alexander Sinyukin, Andrey Kovalev
Turkish Journal of Electrical Engineering and Computer Sciences
Monitoring the condition of engineering objects is one of the urgent tasks of industry, construction, and transport infrastructure. This article describes a system for condition monitoring and diagnostics of rail tracks in real time. Compared with other similar studies, the proposed system has the advantages of compactness, usability, scalability and versatility of application. The proposed monitoring system is based on an Nvidia Jetson Nano embedded computing board and also includes inertial sensor modules, a microphone, a geolocation module, communication modules, an SSD storage device, and a battery. The prototype of the diagnostic module is a portable device that can be …
Modeling And Simulation Of Dynamic Energy Management Systems For Smart Buildings, Onur Özel, Ali̇ Rifat Boynueğri̇, Hayri̇ Yi̇ği̇t, Burak Tekgün
Modeling And Simulation Of Dynamic Energy Management Systems For Smart Buildings, Onur Özel, Ali̇ Rifat Boynueğri̇, Hayri̇ Yi̇ği̇t, Burak Tekgün
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents a dynamic energy management system tailored for smart residential buildings, integrating thermal and electrical models to achieve both natural gas and electricity bill cost reduction. By harnessing wind and solar energy sources, the system aims to meet the diverse energy needs of modern homes. Through load shifting and thermal storage strategies, known as power-to-heat (P2H) approaches, the system ensures efficient renewable energy utilization while maintaining resident comfort. Validation of the proposed system was conducted using real-world data from the Yıldız Technical University Smart Home Laboratory, demonstrating its practical applicability and effectiveness. Results indicate significant reductions in both …
Grey Wolf Optimization Of Pi Controller For Power Management In Wind Farms: A Novel Approach, Anis Feddaoui, Lotfi Farah, Abdelouahab Benretem, Mohammed Abdeldjalil Djehaf
Grey Wolf Optimization Of Pi Controller For Power Management In Wind Farms: A Novel Approach, Anis Feddaoui, Lotfi Farah, Abdelouahab Benretem, Mohammed Abdeldjalil Djehaf
Turkish Journal of Electrical Engineering and Computer Sciences
This study proposes a novel power management strategy for wind farms using a grey wolf optimization (GWO)-based PI controller. The method aims to enhance active and reactive power control in systems employing dou bly fed induction generators. Three control strategies are evaluated—namely, a classical frequency-domain PI controller, an Artificial Neural Network (ANN)-based controller, and the proposed GWO-based PI controller—the last of which represents the main contribution. The classical PI and ANN controllers are included strictly for comparative bench marking. MATLAB simulations demonstrate that the GWO-beased PI controller offers superior dynamic performance, particularly in settling time and overshoot reduction. A power …
Performance Analysis Of Ris-Empowered Ofdm-Im Communications Under Weibull Fading And Joint Tx/Rx I/Q Imbalance, Büşra Ceni̇kli̇oğlu, İbrahi̇m Develi̇, Ayşe Eli̇f Canbi̇len
Performance Analysis Of Ris-Empowered Ofdm-Im Communications Under Weibull Fading And Joint Tx/Rx I/Q Imbalance, Büşra Ceni̇kli̇oğlu, İbrahi̇m Develi̇, Ayşe Eli̇f Canbi̇len
Turkish Journal of Electrical Engineering and Computer Sciences
A modernist technique, reconfigurable intelligent surface (RIS) provides outstanding signal reflection and amplification, making it highly valuable for upcoming communication systems. Besides, a major contributor is index modulation (IM), attaining superior spectral and energy efficiency, and achieving hardware sufficiency. The primary and novel contribution of this work is the derivation of a highly accurate, closed-form approximate expression for the average bit error rate (ABER) of an orthogonal frequency division multiplexing (OFDM)-IM system operating in the complex and challenging environment characterized by joint transmitter/receiver (Tx/Rx) in-phase and quadrature phase imbalance (IQI) and Weibull fading. This essential analytical achievement is facilitated by …
Fpga-Based Takagi-Sugeno Fuzzy Controller For Quadrotor Uav Stabilization And Trajectory Tracking, Hocine Khati, Mohamed Amine Nehmar, Arezki Fekik, Mohand Achour Touat, Hand Talem, Rabah Mellah
Fpga-Based Takagi-Sugeno Fuzzy Controller For Quadrotor Uav Stabilization And Trajectory Tracking, Hocine Khati, Mohamed Amine Nehmar, Arezki Fekik, Mohand Achour Touat, Hand Talem, Rabah Mellah
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents the implementation of a fuzzy logic–based control system on a field-programmable gate array (FPGA) for a quadrotor autonomous aerial vehicle (UAV). The objective is to design and integrate six Takagi–Sugeno fuzzy controllers to regulate roll, pitch, and yaw angles, along with longitudinal, latitudinal, and altitude movements, thereby stabilizing the UAV and enabling it to follow a desired trajectory. Due to the computational complexity of the six controllers, achieving the desired performance requires considerable processing time, which can adversely affect the quadrotor’s mission. Owing to their high processing power and operating frequency, FPGAs enable the control algorithm to …
Ai-Driven Optimization Of Wind Energy Distribution In Texas Using Multi-Agent Reinforcement Learning, Waleed Amer, Owolabi Oluwadamilola, Bassey Ogbonnaya
Ai-Driven Optimization Of Wind Energy Distribution In Texas Using Multi-Agent Reinforcement Learning, Waleed Amer, Owolabi Oluwadamilola, Bassey Ogbonnaya
SMU Data Science Review
Abstract. The integration of large-scale wind power into modern electrical grids presents persistent challenges due to variability, curtailment, and compliance with operational constraints. This study proposes a multi-agent reinforcement learning (MARL) framework for optimizing wind energy distribution within the Texas power grid. The system employs three specialized agents—managing wind curtailment, storage utilization, and load adjustments—to collaboratively balance supply and demand under dynamic grid conditions. Using historical operational data from the Electric Reliability Council of Texas (ERCOT), the framework was trained and evaluated on a range of scenarios encompassing both typical and extreme operating conditions. Results demonstrate substantial performance improvements compared …
Energy Management Of Battery Supercapacitor Hybrid Storage In Electric Vehicles With Solar Integration: Review, Islam Sayed, Yousef Mahmoud
Energy Management Of Battery Supercapacitor Hybrid Storage In Electric Vehicles With Solar Integration: Review, Islam Sayed, Yousef Mahmoud
Faculty Articles
Hybrid energy storage systems (HESS) integrating batteries and supercapacitors offer a promising solution to overcome the limitations of battery-only architectures in electric vehicles (EVs). By leveraging the high energy density of batteries and the high power density of supercapacitors, HESS can enhance power delivery, improve energy efficiency, and extend battery lifespan. The effectiveness of HESS, however, is largely determined by the energy management system (EMS) that coordinates power flow under dynamic driving conditions. Unlike existing reviews, this work addresses common gaps in the literature, including the lack of industrial energy storage component examples, limited coverage of recently developed EMS strategies, …
Field Canals Improvement Projects Duration Prediction: A Comparative Analysis Of Machine Learning Models, Hania Ghouse, Ukaegbu Chinonso Ishmael, Edgar Dario Obando-Paredes, Hashem Shafik Shakir, Ali Al-Bayaty
Field Canals Improvement Projects Duration Prediction: A Comparative Analysis Of Machine Learning Models, Hania Ghouse, Ukaegbu Chinonso Ishmael, Edgar Dario Obando-Paredes, Hashem Shafik Shakir, Ali Al-Bayaty
Electrical and Computer Engineering Faculty Publications and Presentations
There are several essential elements in project construction management to be studied appropriately, and priority to these elements, such as cost and duration, is predominantly interesting to be investigated. In this research, the duration of field canal improvement projects (DFCIP) was predicted using two relatively new machine learning (ML) models - the Multivariate Adaptive Regression Spline (MARS) and Extreme Learning Machine (ELM). The targeted DFCIP was calculated using other dependent parameters, such as the length of the pipe, years of construction, the geographical zone of the network, the supplied area with water, and finally the actual cost of the field …
High Frequency Dc-Dc Converter Design Optimization, Modeling And Control Based-Wbg Technology., Salah Ahmed Abdullah Eltief
High Frequency Dc-Dc Converter Design Optimization, Modeling And Control Based-Wbg Technology., Salah Ahmed Abdullah Eltief
Electronic Theses and Dissertations
The performance of DC-DC power converters is a cornerstone of modern electric vehicle (EV) powertrains, directly governing overall system efficiency, size, cost, and reliability. This dissertation presents a comprehensive performance analysis and optimization of DC-DC converter topologies to determine the most suitable design for high voltage EV applications. The evaluation rigorously compares efficiency, power losses, and physical size under a range of harsh operating conditions. A primary objective is to leverage Wide Bandgap (WBG) semiconductors, specifically Silicon Carbide (SiC), to push the performance boundaries of power conversion. While SiC devices are known for their superior material properties, a clear understanding …
Microgrid Black Start Challenges: The Role Of Grid-Forming Inverters, Gab-Su Seo, Wenzong Wang, Behrooz Mirafzal
Microgrid Black Start Challenges: The Role Of Grid-Forming Inverters, Gab-Su Seo, Wenzong Wang, Behrooz Mirafzal
Faculty Publications
Grid-forming (GFM) inverters are becoming increasingly important for future power systems, particularly in establishing and restarting microgrids after blackouts. The use of GFM inverters enables microgrids to operate independently of utility power and provide key advantages over synchronous generators in black start scenarios, including rapid startup and stable voltage and frequency support for critical loads. However, inverter-driven black start introduces unique challenges and operational considerations. This article examines key challenges and solutions, emphasizing inverter design, control strategies, and microgrid system requirements. Drawing on analysis, simulation, and experimental results, this article highlights the central role of GFM inverters in ensuring reliable …
Cybersecurity Risks Of Freight Rail As Critical Infrastructure, Kira Sun
Cybersecurity Risks Of Freight Rail As Critical Infrastructure, Kira Sun
Discovery Undergraduate Interdisciplinary Research Internship
Our project implements simulated train engineers to operate model train engines on a hybrid twin of a freight rail system. We can then use the model and simulate cyber-security attacks to demonstrate the risks and effects of the attacks. Using existing model train hardware and an Arduino running open-source software, DCC-EX and JMRI, we can control the train engines and various track components and sensors. We program each engine to make safe decisions about what speed and direction to take, using information provided by the various sensors and light signals around the track. When attacks occur, the engines can have …
Towards Robust Autonomous Systems: Handling Multi-Modal Uncertainties In Gps-Denied Environments, Vivya Kalidindi
Towards Robust Autonomous Systems: Handling Multi-Modal Uncertainties In Gps-Denied Environments, Vivya Kalidindi
Doctoral Dissertations
This dissertation focuses on designing a robust and uncertainty-aware framework for autonomous systems operating in GPS-denied environments, such as indoor infrastructures, underground tunnels, and lunar surfaces. The proposed framework addresses the challenges posed by multi-modal uncertainties, including sensor noise, distributional shifts under adverse conditions, and conflicting decision-making preferences. These challenges compromise the reliability and adaptability of autonomous platforms. To overcome these challenges, the proposed framework adopts a layered architecture that integrates advanced methodologies across the sensing, perception, and decision-making layers. At the sensing layer, an Edge-Kalman Filter combined with a density ratio-based update mechanism is employed to reduce aleatoric uncertainty …
Inverse Design For Generating Initial Conditions In Scientific Simulations, Leslie Horace, Christin Whitton, Vanessa Job, William Jones, Nathan A. Debardeleben
Inverse Design For Generating Initial Conditions In Scientific Simulations, Leslie Horace, Christin Whitton, Vanessa Job, William Jones, Nathan A. Debardeleben
Computing Sciences
We propose a conditional normalizing flow (CNF) surrogate model to solve generative, many-to-one inverse problems in scientific simulations governed by partial differential equations (PDEs) with time-evolving interactions between heterogeneous materials. We present two case studies: electrostatic potential and heat diffusion, which serve as proxy simulations for generating diverse sets of initial conditions that can reproduce an observed output state (transient or steady). Finally, we provide a comprehensive overview of the synthetic datasets, the model specification, each stage of the experimental workflow, evaluation of training performance, and uncertainty quantification for the generated samples.
Exploratory Study Of Semiconductor Nanomembranes In Em Applications, Grant D. Heileman
Exploratory Study Of Semiconductor Nanomembranes In Em Applications, Grant D. Heileman
Electrical and Computer Engineering ETDs
Antenna systems are a cornerstone of modern technologies, playing an increasingly vital role in their advancement. As demand for compact, high-performance, and adaptable communication platforms grows reconfigurable antenna technologies are becoming essential. This research explores a novel front-end reconfigurable antenna system (FERAS) architecture that leverages the mechanical flexibility and photoconductive behavior of semiconductor nanomembrane (SNM) devices. By exploiting the emergent properties of ultra-thin silicon (Si) or gallium arsenide (GaAs) nanomaterials and optically exciting these samples using vertical-cavity surface-emitting laser (VCSEL) arrays, this study develops lightweight, low-cost, deployable antenna structures for satellite communications, remote sensing, GPS, and radar. Despite their significant …
User Interface And Watchstation Improvements Required For Multi-Vehicle Usv Operations, Val Schmidt, Joshua Bergeron
User Interface And Watchstation Improvements Required For Multi-Vehicle Usv Operations, Val Schmidt, Joshua Bergeron
Faculty Publications
In October 2024, the University of New Hampshire and NOAA’s Uncrewed Systems Office embarked on a mapping mission in the Gulf of Maine, simultaneously operating two DriX Un-crewed Surface Vehicles. Goals of the project were focused on testing hypotheses related to concepts of operation, including the safety of operations, cognitive loading of operators, management of vehicle endurance, vehicle logistics, maintenance and field support, refueling and a host of others.
Experience With The Stem For Success Internship, Ujwal S. Thirunagari
Experience With The Stem For Success Internship, Ujwal S. Thirunagari
STEM Month
In this article, I discuss my experience working with the STEM for Success team. I detail some of the challenges I faced in completing the CRT and LED sections, how I addressed these challenges, and the widely applicable skills that I learned.
Microstrip Antenna Design Based On Ai And Machine Learning, Waleed Mohamed Sha Moulavi
Microstrip Antenna Design Based On Ai And Machine Learning, Waleed Mohamed Sha Moulavi
Thesis/ Dissertation Defenses
Microstrip patch antennas (MPAs) rely on precise impedance matching for efficient power transfer between the antenna and feed line. This is often achieved using a number of different techniques, one of which is the quarter-wavelength transformer (QWT). However, optimizing the width of the QWT presents significant computational and analytical challenges due to the unknown antenna impedance and the absence of explicit design relationships. This thesis aims to overcome these limitations by developing and comparatively evaluating artificial intelligence (AI) models for QWT width optimization. Methods involved Random Forest (RF) and a novel Probabilistic Deep Neural Network (PDNN) on a custom dataset …
Modeling Social Isolation: A Data-Driven Index Function Design And Implementation, Jeremis N. Morales Morales, Carmen Caiseda, Phyllis Muniu, Joshua Atsu, Folashade B. Agusto
Modeling Social Isolation: A Data-Driven Index Function Design And Implementation, Jeremis N. Morales Morales, Carmen Caiseda, Phyllis Muniu, Joshua Atsu, Folashade B. Agusto
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
A Fully Automated Drilling Machine For Printed Circuit Boards With Superior Path Optimization, Mohamed Mammdouh, Ahmed Khaled, Reem Mahmoud, Osama Desouki, Sameh O. Abdellatif
A Fully Automated Drilling Machine For Printed Circuit Boards With Superior Path Optimization, Mohamed Mammdouh, Ahmed Khaled, Reem Mahmoud, Osama Desouki, Sameh O. Abdellatif
Electrical Engineering
This paper addresses a critical challenge in Printed Circuit Board (PCB) manufacturing by proposing an AI-driven, fully automated drilling machine that employs sophisticated path-planning techniques. Current methodologies often fail to adequately assess designs with varying hole sizes, diverse component placements, and complex geometries, leading to compromised precision and increased manufacturing times. Our innovative approach leverages advanced algorithms to intelligently analyze PCB designs and optimize drilling paths, significantly reducing production time and minimizing errors. By automating the drilling process, we enhance overall productivity while ensuring precise hole placement, essential for maintaining high-quality circuit boards. Utilizing KiCAD EDA software, we automate the …
“How Can Ai Data Centers In The U.S. Meet Projected Electricity Demands By 2030?, Aiden M. Matano
“How Can Ai Data Centers In The U.S. Meet Projected Electricity Demands By 2030?, Aiden M. Matano
Sustainable Supply Chain Management
The rapid expansion of artificial intelligence is driving a sharp increase in U.S. electricity demand, with AI-driven data centers emerging as a central contributor through 2030. This paper asks how U.S. AI data centers can meet projected electricity needs while simultaneously reducing carbon emissions. Using a supply-chain and systems perspective, it analyzes the full energy chain of AI data centers: upstream electricity supply and grid deliverability, midstream facility design and grid interaction, and downstream operational practices, waste management, and disclosure. Drawing on recent projections from the International Energy Agency, Lawrence Berkeley National Laboratory, and U.S. federal guidance, the paper shows …
Design Considerations For Conversational Agents To Assess The Social-Emotional Well-Being Of Young Children In Low-Income South African Communities, Lucretia A. Williams, Elizabeth A. Ankrah, Catherine E. Draper, Caylee J. Cook, Franceli L. Cibrian, Jesus A. Beltran, Kimberley D. Lakes, Gillian R. Hayes
Design Considerations For Conversational Agents To Assess The Social-Emotional Well-Being Of Young Children In Low-Income South African Communities, Lucretia A. Williams, Elizabeth A. Ankrah, Catherine E. Draper, Caylee J. Cook, Franceli L. Cibrian, Jesus A. Beltran, Kimberley D. Lakes, Gillian R. Hayes
Engineering Faculty Articles and Research
A variety of digital technologies have been used to support early childhood development (ECD) programs in low-income South African communities. Even though technology has provided opportunities to increase access to health interventions, the lack of trust and socio-economic constraints under which these tools would need to work pose complex challenges. We examine home visitors’ work processes, experiences, and preferences of a conversational agent to support their work of administering social-emotional well-being assessments to young children ages 0-5. Analysis of the results of focus groups with 51 home visitors indicates the need for designing conversational agents that support ECD in the …
Localized Nuclear Utility For Erau Environmental Improvement, Timothy Schroeder, Jacob Blanton, Christopher Anderson
Localized Nuclear Utility For Erau Environmental Improvement, Timothy Schroeder, Jacob Blanton, Christopher Anderson
Sustainability Conference
The reliance of Embry Riddle Aeronautical University (ERAU) on energy supplied by Florida Power & Light (FPL), which currently draws large amounts of power from fossil fuel sources, is continuously suboptimal both environmentally and financially. This study proposes assessing the feasibility of deploying a campus scale nuclear reactor tailored to ERAU’s power consumption profile. This serves as a path toward reducing greenhouse gas emissions and limiting dependence on external fossil fuel generation. The methods used are primarily literature review(s), and numerical analysis on comparable use cases. The literature reviews focused on design theory and yield of nuclear reactors on a …
Advancing Power System Reliability And Security With Efficient And Resilient Graph Neural Network Frameworks, Seyed Hamed Haghshenas
Advancing Power System Reliability And Security With Efficient And Resilient Graph Neural Network Frameworks, Seyed Hamed Haghshenas
USF Tampa Graduate Theses and Dissertations
Enhancing the reliability and security of smart grids is critical for ensuring their seamless operation and resilience against disruptions. The increasing integration of distributed energy resources, advanced measurement devices, and cyber-physical elements introduces both opportunities and challenges for grid management. While these advancements provide enhanced visibility and operational control, they also expose the grid to vulnerabilities from cyber-physical stresses, such as cyber-attacks, equipment failures, and fluctuating power demands. Traditional methods for reliability assessment and threat detection often rely on model-based approaches that struggle to adapt to the complexity and dynamic nature of modern smart grids. These limitations necessitate novel data-driven …
Harnessing Electrochemical Hydrogen Evolution In Α-Fe2o3/2h–Mos2 Heterojunction: A Theoretical And Experimental Study On Electronic Modulation And Basal Plane Activation, Mohamed Sayed, Ossama Metwalli, Sameh O. Abdellatif, Kai Yin, Mohamed Saber, Ahmed Khalil, Hossam Abdelwahan
Harnessing Electrochemical Hydrogen Evolution In Α-Fe2o3/2h–Mos2 Heterojunction: A Theoretical And Experimental Study On Electronic Modulation And Basal Plane Activation, Mohamed Sayed, Ossama Metwalli, Sameh O. Abdellatif, Kai Yin, Mohamed Saber, Ahmed Khalil, Hossam Abdelwahan
Electrical Engineering
Hydrogen production through water electrolysis is a promising method for storing renewable energy and reducing greenhouse gas emissions. However, the efficiency and stability of hydrogen production electrodes remain challenging issues. In this study, we present a rationally designed α-Fe2O3/2H–MoS2 heterojunction that unlocks the electrocatalytic potential of the inert basal plane of the semiconducting 2H–MoS2 phase. The heterostructure, synthesized via a facile hydrothermal method, features α-Fe2O3 nanocubes anchored onto flowerlike 2H–MoS2 nanosheets. The electrochemical performance of the α-Fe2O3/2H–MoS2 heterojunction electrode was evaluated by linear sweep voltammetry, Tafel polarization, and electrochemical impedance spectroscopy. The results showed that the α-Fe2O3/2H–MoS2 electrode exhibited lower …
Photochemical And Electrochemical Assessment Of Uio-66-Nh₂/G-C₃N₄ Thin-Film Heterostructures As Potential Candidates For Hydrogen Evolution: An Experimental Study Augmented By Dft Insights, Nour Abouseada, Maryam Galal, Sameh O. Abdellatif, Khaled Kirah
Photochemical And Electrochemical Assessment Of Uio-66-Nh₂/G-C₃N₄ Thin-Film Heterostructures As Potential Candidates For Hydrogen Evolution: An Experimental Study Augmented By Dft Insights, Nour Abouseada, Maryam Galal, Sameh O. Abdellatif, Khaled Kirah
Electrical Engineering
The global shift towards carbon-neutral energy systems has catalyzed an intensified focus on sustainable hydrogen production, with photo and electrochemical water splitting emerging as a particularly promising pathway. This study elucidates the design, simulation, and synthesis of advanced photo and electrocatalytic materials tailored for the hydrogen evolution reaction (HER), concentrating on heterostructures formed by zirconium-based metal-organic frameworks (MOFs)— specifically, UiO-66 and its amine-functionalized derivative, UiO-66-NH₂—in conjunction with graphitic carbon nitride (g-C₃N₄). Employing density functional theory (DFT) simulations, we pre-screened the electronic properties of the MOFs, revealing that amine functionalization significantly narrows the bandgap and optimizes band alignment, thereby enhancing photocatalytic …