Digital Commons Network^™

Guest Editorial: Transition Towards Deep Decarbonisation Of Modern Energy Systems, Yujian Ye, Can Wan, Chenghong Gu, Dan Wu, Goran Strbac, Hongjian Sun, Peng Zhang, Rui Bo, Yi Tang, Zhongbei Tian

Electrical and Computer Engineering Faculty Research & Creative Works

No abstract provided.

Enhanced Two-Step Deep-Learning Approach For Electromagnetic-Inverse-Scattering Problems: Frequency Extrapolation And Scatterer Reconstruction, Huan Huan Zhang, He Ming Yao, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

The electromagnetic-inverse-scattering (EMIS) problem is solved by a novel two-step deep-learning (DL) approach in this article. The newly proposed two-step DL approach not only predicts the multifrequency EM scattered field, but also overcomes the limitation of the conventional methods for solving EMIS problems, such as expensive computational cost, strong ill-conditions, and invalidity on high contrast. In the first step, the complex-valued deep residual convolutional neural network (DRCNN) is utilized to predict multifrequency EM scattered fields only using single-frequency EM scattered field information. Based on a new complex-valued deep convolutional encoder-decoder (DCED) structure, the second step utilizes the obtained multifrequency EM …

A Novel Approach For Optimal Sizing Of Stand-Alone Solar Pv Systems With Power Quality Considerations, Aakash Hassan, Octavian Bass, Yasir M. Al-Abdeli, Martin Masek, Mohammad A. S. Masoum

Research outputs 2022 to 2026

Designing reliable and cost-effective solar PV systems with compliance to national and international power quality standards is critical for their economical, efficient, and safe operation. The conventional approaches currently being used to optimally size the solar PV systems generally ignore power quality criteria during the initial design phase. This paper fills this gap by presenting a novel Genetic Algorithm (GA) based strategy to design a stand-alone solar PV system featuring optimal system size with conformance to power quality standards. MATLAB/Simulink environment was used to develop a detailed model of solar PV system, including a robust control mechanism for maximum power …

In-Field Solar Panel Assessment And Fault Diagnosis, Muhammad Elgamal

Theses and Dissertations

Photovoltaic energy is a green energy that suit from small houses to high-power stations spanning large areas. In such large areas, monitoring individual panels can be a tedious task, especially if it was required to identify operational faults of these panels. Photovoltaic 4.0 technology depend on collecting data from each station and feeding them to a central processing system that can analyze operation data and hopefully locate when a fault happens. In such method, it is crucial to be accurate as much as possible and for measuring device to be accurate as well to have a clear judgement. In this …

Electromagnetic Theory And Applications, Nicholas Madamopoulos, George Kliros

Open Educational Resources

This book intends to provide both the fundamentals of Electromagnetics but also some practical applications of the concepts covered. Having taught electromagnetics for several years, the authors feel that many times the field of electromagnetics comes as “old” and often times students do not appreciate the concepts and their importance in everyday applications. The authors intend to accompany the EM concepts with life applications. Hence, students may see the direct impact of the knowledge they acquire through the study of the field of electromagnetics and better appreciate the field.

Preface To Special Issue: Electrocatalysis And Electrosynthesis, Fang-Yi Cheng, Shuang-Yin Wang, Tian-Hua Zhou

Journal of Electrochemistry

No abstract provided.

Recent Advances In Exploring Highly Active & Durable Pgm-Free Oxygen Reduction Catalysts, Yuan Li, Miao-Ying Chen, Bang-An Lu, Jia-Nan Zhang

Journal of Electrochemistry

In order to reduce the considerable usage of expensive but scarce platinum at the cathode in proton exchange membrane fuel cells (PEMFCs), it is necessary to pursue alternatives to platinum. The most promising platinum group metal (PGM)-free catalysts for oxygen reduction reaction (ORR) are atomically dispersed, and nitrogen-coordinated metal site catalysts denoted as M-N-C (M = Fe, Co, or Mn, etc.). Over the last few decades, there have been great advances in these catalysts with high ORR activity and promising initial fuel cell performance approaching traditional Pt/C catalysts. However, the stability of these highly active Fe-N-C catalysts under practical fuel …

Electrochemical Oxidation Of Ethylene On Palladium Electrode, Wei-Xing Wu, Ying Wang

Journal of Electrochemistry

The electrochemical oxidation of C₂H₄ is attracting increasing attention due to its vast potential market. The current electrochemical methods rely on the use of redox mediators, which may produce corrosive intermediates, while direct oxidation is still limited by its low activity and selectivity. Herein, we conducted electrochemical studies to obtain mechanistic insights into the benchmark Pd catalyst. The generated Pd(II) could be the active site for C₂H₄ oxidation. By designing the pulse sequence, we found the ratio of strongly and weakly adsorbed C₂H₄ on Pd to be 0.3:1. The result we …

Supperlattice-Like Structure: Ordered Mass Transfer Endowing High Quality Output Of Fuel Cell, Jian Wang, Wen-Hui Xuan, Qian He, Jing-Xia Jiang, Yuan-Yuan Zhou, Yao Nie, Qiang Liao, Min-Hua Shao, Wei Ding, Zi-Dong Wei

Journal of Electrochemistry

The current or voltage fluctuation in fuel cell operation is harmful to the fuel cell system and power application equipment. Here, we report a technique to eliminate such a fluctuation by the aid of new type of catalysts, superlattice-like mesoporous PtCo catalysts. The current fluctuation in fuel cells catalyzed by two invented catalysts are fixed at as low as 25 mA·cm⁻² with a power of 0.75 W·cm⁻² or 120 mA·cm⁻² with a power of 1.01 W·cm⁻², and no noticeable current decay was detected over 100 h. By contrast, a …

Design Of A Non-Destructive System For Arctic Permafrost Detection Via High Frequency Electromagnetic Induction, Gray Dominic Thurston

Theses and Dissertations

Electromagnetic induction (EMI) sensors have been utilized in the past by the United States Army Corps of Engineers as a method of detecting unexploded ordnance (UXO). Recently, an EMI instrument was constructed that extended the traditional EMI frequency range from 100 kHz to 15 MHz to aid in the detection of nonmetallic ordnance, landmines, and improvised explosive devices. Building on this research, the iFROST mapper project aims to use the same high-frequency (HF) EMI technique to characterize arctic soil and subsurface permafrost deposits. Based on a device used by the US Army for UXO detection, an HF EMI instrument was …

Data-Driven Nonparametric Joint Chance-Constrained Programming For Power Systems Scheduling, Chutian Wu

LSU Doctoral Dissertations

This dissertation is dedicated to implementing data-driven nonparametric joint chance constraints (JCC) to power system optimization problems. Power generated by renewable sources, such as solar farms, is an uncertain parameter. Several approaches solve optimization under uncertainty, including stochastic programming, robust programming, and chance-constrained programming. Uncertain parameters may not belong to any parametric class of probability functions. Thus, methods that consider such uncertainty as a random variable that fits in a known probability density function (PDF) have limitations. This study focuses on chance-constrained programming under nonparametric or data-driven distributionally robust uncertainty settings.

Studies based on chance-constrained programming usually focus on individual …

Introduction To Control Engineering, Xiangyu Meng

E-Textbooks

This is an introductory level textbook for control engineering.

Influence Of Synthesis Conditions On The Physicochemical And Electrocatalytic Properties Of Non-Stoichiometric Ba2sr2la2ti4o12 Perovskites, Ofeliya Kostadinova, Iliyan Popov, Simeon M. Stankov, Hristo Kolev, Tamara Petkov

Karbala International Journal of Modern Science

Present work studies the influence of the pretreatment milling media (deionized water (BLTOS-H) and isopropanol (BLTOS-i)) on the surface characteristics, structure, chemical composition and catalytic activity of non-stoichiometric Ba2Sr2La2Ti4O12 perovskites. The IR spectroscopy and XRD analyses shows a difference in the structure and phase composition of the two materials. X-ray photoelectron spectroscopy detects a Ba2+- and La3+-enriched and Sr2+-depleted surface. The BLTOS-i sample appears to exhibit higher specific surface area (SSA) and pore volume in comparison to BLTOS-H. The electrochemical tests showed that BLTOS-H sample have similar behavior to platinum at current densi-ties up to 10 mA cm-2, while BLTOS-i …

Using Dielectric Scatters To Selectively Excite Embedded Eigenstates In Cavity Resonators, Olugbenga Joshua Gbidi

Theses and Dissertations

Bound states in the continuum (BICs) are waves that remain in the continuous spectrum of radiating waves that carry energy, however, still localized within the spectrum. BICs, also embedded eigenmodes, exhibit high quality factors that have been observed in optical and acoustic waveguides, photonic structures, and other material systems. Presently, there are limited means to select these BICs in terms of the quality factor and their excitation. In this work, we show that a different type of BIC, Quasi-BICs (Q-BICs), in open resonators can have their quality attuned by introducing embedded scatters. Using microwave cavities and dielectric scatters as an …

Perspectives On Design Considerations Inspired By Security And Quantum Technology In Cyberphysical Systems For Process Engineering, Helen Durand, Jihan Abou Halloun, Kip Nieman, Keshav Kasturi Rangan

Chemical Engineering and Materials Science Faculty Research Publications

Advances in computer science have been a driving force for change in process systems engineering for decades. Faster computers, expanded computing resources, simulation software, and improved optimization algorithms have all changed chemical engineers’ abilities to predict, control, and optimize process systems. Two newer areas relevant to computer science that are impacting process systems engineering are cybersecurity and quantum computing. This work reviews some of our group’s recent work in control-theoretic approaches to control system cybersecurity and touches upon the use of quantum computers, with perspectives on the relationships between process design and control when cybersecurity and quantum technologies are of …

Enhanced Fractional Adaptive Processing Paradigm For Power Signal Estimation, Naveed Ishtiaq Chaudhary, Zeshan Aslam Khan, Muhammad Asif Zahoor Raja, Iqra Ishtiaq Chaudhary

Articles

Fractional calculus tools have been exploited to effectively model variety of engineering, physics and applied sciences problems. The concept of fractional derivative has been incorporated in the optimization process of least mean square (LMS) iterative adaptive method. This study exploits the recently introduced enhanced fractional derivative based LMS (EFDLMS) for parameter estimation of power signal formed by the combination of different sinusoids. The EFDLMS addresses the issue of fractional extreme points and provides faster convergence speed. The performance of EFDLMS is evaluated in detail by taking different levels of noise in the composite sinusoidal signal as well as considering various …

A Path Planning Framework For Multi-Agent Robotic Systems Based On Multivariate Skew-Normal Distributions, Peter Estephan

Theses, Dissertations and Capstones

This thesis presents a path planning framework for a very-large-scale robotic (VLSR) system in an known obstacle environment, where the time-varying distributions of agents are applied to represent the multi-agent robotic system (MARS). A novel family of the multivariate skew-normal (MVSN) distributions is proposed based on the Bernoulli random field (BRF) referred to as the Bernoulli-random-field based skew-normal (BRF-SN) distribution. The proposed distributions are applied to model the agents’ distributions in an obstacle-deployed environment, where the obstacle effect is represented by a skew function and separated from the no-obstacle agents’ distributions. First, the obstacle layout is represented by a Hilbert …

High-Sensitivity Vector Bend Sensor Based On A Fiber Directional Coupler Inscribed By A Femtosecond Laser, Ke Tian, Mingyuan Zhang, Chuanzhein Zhao, Huibin Li, Shilong Li, Yuxuan Jiang, Gerald Farrell, Pengfei Wang

Articles

In this Letter, we demonstrate a high-sensitivity vector bend sensor based on a fiber directional coupler. The fiber directional coupler is composed of two parallel waveguides inscribed within a no-core fiber (NCF) by a femtosecond laser. Since the two written waveguides have closely matched refractive indices and geometries, the transmission spectrum of the fiber directional coupler possesses periodic resonant dips. Such a fiber directional coupler exhibits a good bending-dependent spectral shift response due to its asymmetric structure. Experimental results show that bending sensitivities of -97.11 nm/m-1 and 58.22 nm/m-1 are achieved for the 0° and 180° orientations in the curvature …

Gamelan Gong Directivity Dataset, Samuel D. Bellows, Dallin T. Harwood, Kent L. Gee, Micah R. Shepherd

Directivity

No abstract provided.

Power System Dynamic Control And Performance Improvement Based On Reinforcement Learning, Wei Gao

Electronic Theses and Dissertations

This dissertation investigates the feasibility and effectiveness of using Reinforcement Learning (RL) techniques for power system dynamic control, particularly voltage and frequency control. The conventional control strategies used in power systems are complex and time-consuming due to the complicated high-order nonlinearities of the system. RL, which is a type of neural network-based technique, has shown promise in solving these complex problems by fitting any nonlinear system with the proper network structure.

The proposed RL algorithm, called Guided Surrogate Gradient-based Evolution Strategy (GSES) determines the weights of the policy (which generates the action for our control reference signal) without back-propagation process …

Artificial Emotional Intelligence In Socially Assistive Robots, Hojjat Abdollahi

Electronic Theses and Dissertations

Artificial Emotional Intelligence (AEI) bridges the gap between humans and machines by demonstrating empathy and affection towards each other. This is achieved by evaluating the emotional state of human users, adapting the machine’s behavior to them, and hence giving an appropriate response to those emotions. AEI is part of a larger field of studies called Affective Computing. Affective computing is the integration of artificial intelligence, psychology, robotics, biometrics, and many more fields of study. The main component in AEI and affective computing is emotion, and how we can utilize emotion to create a more natural and productive relationship between humans …

A Hybrid Multifunctional Physicochemical Sensor Suite For Continuous Monitoring Of Crop Health, Nafize Ishtiaque Hossain, Shawana Tabassum

Electrical Engineering Faculty Publications and Presentations

This work reports a first-of-its-kind hybrid wearable physicochemical sensor suite that we call PlantFit for simultaneous measurement of two key phytohormones, salicylic acid, and ethylene, along with vapor pressure deficit and radial growth of stem in live plants. The sensors are developed using a low-cost and roll-to-roll screen printing technology. A single integrated flexible patch that contains temperature, humidity, salicylic acid, and ethylene sensors, is installed on the leaves of live plants. The strain sensor with in-built pressure correction capability is wrapped around the plant stem to provide pressure-compensated stem diameter measurements. The sensors provide real-time information on plant health …

Merit Study Of Battery Or Hydrogen Energy Storage For Large Scale, Combined Wind And Solar Electricity Generation, Ashley K. Moore

Browse all Theses and Dissertations

In the past several years, the energy sector has experienced a rapid increase in renewable energy installations due to declining capital costs for wind turbines, solar panels, and batteries. Wind and solar electricity generation are intermittent in nature which must be considered in an economic analysis if a fair comparison is to be made between electricity supplied from renewables and electricity purchased from the grid. Energy storage reduces curtailment of wind and solar and minimizes electricity purchases from the grid by storing excess electricity and deploying the energy at times when demand exceeds the renewable energy supply. The objective of …

Towards Explainable Ai Using Attribution Methods And Image Segmentation, Garrett J. Rocks

Honors Undergraduate Theses

With artificial intelligence (AI) becoming ubiquitous in a broad range of application domains, the opacity of deep learning models remains an obstacle to adaptation within safety-critical systems. Explainable AI (XAI) aims to build trust in AI systems by revealing important inner mechanisms of what has been treated as a black box by human users. This thesis specifically aims to improve the transparency and trustworthiness of deep learning algorithms by combining attribution methods with image segmentation methods. This thesis has the potential to improve the trust and acceptance of AI systems, leading to more responsible and ethical AI applications. An exploratory …

Scheduling Electric Vehicle Charging For Grid Load Balancing, Zhixin Han, Katarina Grolinger, Miriam Capretz, Syed Mir

Electrical and Computer Engineering Publications

In recent years, electric vehicles (EVs) have been widely adopted because of their environmental benefits. However, the increasing volume of EVs poses capacity issues for grid operators as simultaneously charging many EVs may result in grid instabilities. Scheduling EV charging for grid load balancing has a potential to prevent load peaks caused by simultaneous EV charging and contribute to balance of supply and demand. This paper proposes a user-preference-based scheduling approach to minimize costs for the user while balancing grid loads. The EV owners benefit by charging when the electricity cost is lower, but still within the user-defined preferred charging …

Optimal Management And Sizing For Battery Energy Storage Systems For Grid Applications, Abdullah Muslih Alharbi

Electronic Theses and Dissertations

Battery energy storage systems (BESSs) play a dominant role in the reliability, resiliency, economics, and operational flexibility of the power grid. As such, the BESS is a promising and reliable green technology for supporting power grid facilities. However, the integration of BESS technology into power projects can be expensive and challenging, both technologically and in terms of regulation compliance. Thus, it is necessary to examine best practices for fully optimizing BESS sizing, operation, and scheduling in the context of benefiting BESS operators and investors by fully exploiting the valuable economic and technical benefits of BESSs. In this research, we identify …

Utilizing Data Analytics On Single-Phase Ac Arc Flash Testing And Model Development, Po-Chen Chen

Electrical Engineering Dissertations - Archive

Arc flash events could result in injuries, fatalities, and lead to severe medical expenses, equipment replacement cost, and even litigation, fines, and loss of business. Such events could also tremendously traumatize the personnel psychosocially and neurologically. Therefore, it is critical to accurately understand the potential arc flash hazards from all the real applications. Yet, due to the random complex nature of arc flash events and great number of uncertain variables involved, there are challenges to provide mathematical models for equipment designers in determining the arc-flash fault current and the incident energy of various types of events. The early arc flash …

A Partial Discharge Inception Voltage Modeling Approach, Shilpi Mukherjee, Tristan Mark Evans, David Huitink, H. Alan Mantooth

Electrical Engineering Faculty Publications and Presentations

A partial discharge inception voltage modeling approach promoting design-for-reliability considerations in advanced power modules is presented. As power modules are being operated at higher voltages and become more compact to meet power density demands, there is an increased risk of partial discharge, the silent precursor to electrical breakdown that degrades insulation material. The trade-off between voltage class and module compaction must be quantified. This work presents a methodology to model the tradeoff for any substrate and encapsulant material. A surface charge density-based partial discharge inception voltage (PDIV) model was developed to overcome the challenges in electric field-based models. The model …

Three-Port Bi-Directional Dc–Dc Converter With Solar Pv System Fed Bldc Motor Drive Using Fpga, Arun Kumar Udayakumar, Raghavendra Rajan Vijaya Raghavan, Mohamad Abou Houran, Rajvikram Madurai Elavarasan, Anushkannan Nedumaran Kalavathy, Eklas Hossain

Electrical and Computer Engineering Faculty Publications and Presentations

The increased need for renewable energy systems to generate power, store energy, and connect energy storage devices with applications has become a major challenge. Energy storage using batteries is most appropriate for energy sources like solar, wind, etc. A non-isolated three-port DC–DC-converter energy conversion unit is implemented feeding the brushless DCmotor drive. In this paper, a non-isolated three-port converter is designed and simulated for battery energy storage, interfaced with an output drive. Based on the requirements, the power extracted from the solar panel during the daytime is used to charge the batteries through the three-port converter. The proposed three-port converter …

High-Efficieny Ultrafast Mid-Infrared Source For Strong Field Science, Fangjie Zhou

Electronic Theses and Dissertations, 2020-2023

The potential of high-energy sources within the mid-infrared region (3-8 μm) has garnered significant attention for diverse research and industrial applications. Millijoule pulses extending beyond 3 μm can facilitate the production of x-rays with photon energies in the keV range through high harmonic generation (HHG). These high-energy x-ray pulses enable the characterization of electron dynamics within molecules and condensed matter materials. Additionally, the atmospheric transmission window between 3-5 μm allows lasers within this spectral range to deliver energy efficiently to distant targets via optical filaments without divergence, highlighting promising prospects for defense applications. In contrast to laser amplifiers, which are …