Engineering Commons^™

Integration Of Neural Network And Distance Relay To Improve The Fault Localization On Transmission Lines, Linh Tran

Turkish Journal of Electrical Engineering and Computer Sciences

Power transmission lines are integral and very important components of power systems. Because of the length of these lines and the complexity of the power grids, the lines may encounter various incidents such as lightning strike, shortage, and breakage. When an incident or a fault occurs, a fast process of identification, localization, and isolation of the fault is desired. An accurate fault localization would have a great impact in reducing the restoration time of the system. One of the most popular solutions for fault detection and localization is the distance relays using the impedance-based algorithms. However, these relays are still …

Quadratic Programming Based Partitioning For Block Cimmino With Correct Value Representation, Zuhal Taş, Fahreddi̇n Şükrü Torun

Turkish Journal of Electrical Engineering and Computer Sciences

The block Cimmino method is successfully used for the parallel solution of large linear systems of equations due to its amenability to parallel processing. Since the convergence rate of block Cimmino depends on the orthogonality between the row blocks, advanced partitioning methods are used for faster convergence. In this work, we propose a new partitioning method that is superior to the state-of-the-art partitioning method, GRIP, in several ways. Firstly, our proposed method exploits the Mongoose partitioning library which can outperform the state-of-the-art methods by combining the advantages of classical combinatoric methods and continuous quadratic programming formulations. Secondly, the proposed method …

Unbiased Federated Learning In Energy Harvesting Error-Prone Channels, Zeynep Çakir, Eli̇f Tuğçe Ceran Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

Federated learning (FL) is a communication-efficient and privacy-preserving learning technique for collaborative training of machine learning models on vast amounts of data produced and stored locally on the distributed users. This paper investigates unbiased FL methods that achieve a similar convergence as state-of-the-art methods in scenarios with various constraints like an error-prone channel or intermittent energy availability. For this purpose, we propose FL algorithms that jointly design unbiased user scheduling and gradient weighting according to each user's distinct energy and channel profile. In addition, we exploit a prevalent metric called the age of information (AoI), which quantifies the staleness of …

Efficient Modelling Of Random Access Memory Cell: An Approach Using Qca Nanocomputing, Ali Newaz Bahar, Angshuman Khan

Turkish Journal of Electrical Engineering and Computer Sciences

Quantum-dot cellular automata (QCA) is innovative and potentially fruitful nanotechnology that provides a solution for transistor-based circuits with enhanced switching frequency, large-scale integration, and low power consumption. The random-access memory (RAM) cell is a fundamental component that is designed to operate quickly and effectively since memory is a core part of the semiconductor industry, thus the QCA family. The RAM cell design in this work is based on a multiplexer structure and is implemented without using coplanar crossovers of QCA technology. QCADesigner-2.0.3, a standard QCA layout design and verification tool, is used in the simulation and validation processes for the …

An Analytical Solution Of Fractional Order Pi Controller Design For Stable/Unstable/Integrating Processes With Time Delay, Erdal Çökmez, İbrahi̇m Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

This paper aims to put forward an analytical solution for tuning parameters of a fractional order PI (FOPI) controller for stable, unstable, and integrating processes with time delay. Following this purpose, the analytical weighted geometrical center (AWGC) method has been extended to the design of fractional order PI controllers. To apply AWGC, the stability equations of the closed-loop system are written in terms of process and fractional order PI controller parameters. With the proposed method, the centroid can be calculated analytically, and the controller parameters can be easily calculated without the need of repetitive drawings of the stability boundary regions. …

More Wifi For Everyone: Increasing Spectral Efficiency In Wifi6 Networks Using A Distributed Obss/Pd Mechanism, Ali̇ Karakoç, Hüseyi̇n Bi̇rkan Yilmaz, Mehmet Şükrü Kuran

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a distributed algorithm that determines effective Overlapping Basic Service Set/Preamble Detection (OBSS/PD) threshold levels in each WiFi6 device to maximize the total throughput by increasing the spectral efficiency. Within WiFi6 standard, OBSS/PD mechanism is introduced to increase the overall efficiency of WiFi networks by tuning the receiver sensitivity as well as the transmission power. In a nutshell, the proposed algorithm, RACEBOT, tunes the hearing (i.e. reception) and speaking (i.e. transmission) parameters of each WiFi device individually for the betterment of the WiFi experience of all WiFi networks in a neighborhood. WiFi experience is not only …

Control And Design Of A Passive Solar Lumber Drying Kiln, Peter Chardavoyne

Honors Scholar Theses

The passive solar lumber drying kiln design, developed by EE Senior Design Team 2317 is presented, tested, and discussed. The design incorporates solar power and a custom control system to dry 12’ lumber boards inside a shipping container much faster than air-drying methods, which can take up to a year for thorough drying, though this can be extended due to the unpredictability of weather events and conditions. This work presents the design as in the final report provided by the team, but provides a more detailed explanation and analysis of the microcontroller system, testing methods and outcomes, alternate solutions and …

Analyzing The Influence Of Stale Data On Autonomous Intelligent Transportation Systems, August St. Louis

All Theses

Intelligent transportation has been at the forefront of recent technological advancement. Individuals have developed a number of algorithms intended to automate and improve essential intelligent transportation functions. New developments include the incorporation of vehicle platooning and path planning algorithms within a number of use cases. Data perturbation can affect both algorithms significantly. We define data perturbation as any natural or unnatural phenomenon that causes the data to be skewed in any way. Perturbations within either system can cause its respective algorithm to operate with stale or incorrect data. This can significantly affect performance. This paper conducts a fault injection campaign …

Considerations Of The Impacts And System-Level Mitigation Of Electric Vehicle Charging On The Integrated Resource Planning Process, Grant Wollam

All Theses

Electric vehicles (EV) are growing in popularity and therefore adoption rate. Best estimates predict a 6.2% EV adoption rate by 2035 in the southeastern United States. With this level of EV adoption, utility planners must begin to consider the impact that EVs will have on the power grid. This paper aims to help predict these EV impacts on the power grid. Specifically, an urban-commercial feeder is analyzed in detail to provide worst-case and most-likely results of varying levels of EV impact. Results show that a 26.2% peak increase is the most likely result for this feeder in 2035.

Mitigation techniques …

Optimal Offering Strategy Of Genco With Joint Participation In Ftr Auction And Day-Ahead Market Considering Virtual Bidding, Hossein Mehdipourpicha, Rui Bo, Siyuan Wang

Electrical and Computer Engineering Faculty Research & Creative Works

Nodal price separations in Day-Ahead (DA) market caused by transmission congestion create congestion charges/surplus that are reallocated to the market participants through the financial transmission right (FTR) auction. From a market participant's viewpoint, these two markets are interrelated because the revenue of market participant in FTR auction is determined based on the day-ahead locational marginal prices. Furthermore, virtual transactions which are designed to improve price convergence between the day-ahead and real-time markets can directly impact day-ahead prices. This impact through virtual transactions may be utilized by a market participant to increase its FTR value and improve its overall strategy in …

A Machine Learning Specklegram Wavemeter (Maswave) Based On A Short Section Of Multimode Fiber As The Dispersive Element, Ogbole C. Inalegwu, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Wavemeters are very important for precise and accurate measurements of both pulses and continuous-wave optical sources. Conventional wavemeters employ gratings, prisms, and other wavelength-sensitive devices in their design. Here, we report a simple and low-cost wavemeter based on a section of multimode fiber (MMF). The concept is to correlate the multimodal interference pattern (i.e., speckle patterns or specklegrams) at the end face of an MMF with the wavelength of the input light source. Through a series of experiments, specklegrams from the end face of an MMF as captured by a CCD camera (acting as a low-cost interrogation unit) were analyzed …

Comparison Of Facial Emotion Recognition Models Using Deep Learning, Arsany Hanin

LSU New Orleans Theses and Dissertations

Facial emotion recognition is a widely studied area with applications in diverse domains such as human-computer interaction, affective computing, and social robotics. This thesis aims to improve the accuracy of facial emotion recognition models by incorporating a second neural network trained on original probabilities and probability transformation, while also comparing the performance of different techniques. The thesis begins with a thorough review of available datasets and technologies used for data collection, highlighting the challenges associated with these datasets. A detailed analysis of various facial emotion detection models, including the baseline model and its different architectures, is presented. The thesis also …

Analysis Of An Isolated Bidirectional Ćuk Converter, Yeny Hau Chen

Graduate Theses and Dissertations

The objective of this thesis is to perform an analysis of the isolated bidirectional Ćuk dc-dc converter topology and demonstrate the advantages and operation of this configuration through simulations using MATLAB/SimulinkTM and measurements collected from a 1.5-kW prototype tested at the Engineering Research Center (ENRC) laboratory of the University of Arkansas. The idea of integrating an active-clamp snubber circuit on each side of the converter, proposed by Dr. Sudip Mazumder from the University of Illinois, Chicago, limits the additional voltage stresses on the components due to the energy from the transformer’s leakage inductance. This is studied in this thesis to …

Machine Learning For A Vernier-Effect-Based Optical Fiber Sensor, Chen Zhu, Osamah Alsalman, Wassana Naku

Electrical and Computer Engineering Faculty Research & Creative Works

In recent years, the optical Vernier effect has been demonstrated as an effective tool to improve the sensitivity of optical fiber interferometer-based sensors, potentially facilitating a new generation of highly sensitive fiber sensing systems. Previous work has mainly focused on the physical implementation of Vernier-effect-based sensors using different combinations of interferometers, while the signal demodulation aspect has been neglected. However, accurate and reliable extraction of useful information from the sensing signal is critically important and determines the overall performance of the sensing system. In this Letter, we, for the first time, propose and demonstrate that machine learning (ML) can be …

Modbus Rtu For Embedded Cyber Secure Inverter Controller, Brady Mcbride

Graduate Theses and Dissertations

The Modbus communication protocol is a widely adopted communication standard in industrial control systems. This communication protocol is known for being reliable and straightforward to implement while being versatile in terms of its operating parameters while supporting multiple formats over various hardware infrastructures and architectures. Many intelligent devices such as Programmable Logic Controllers (PLCs), Human-Machine Interfaces (HMIs), Internet-of-Things (IoT), and various Operational Technologies (OT) utilize Modbus for their communication systems. These types of systems must communicate with each other through a standardized and central communication process. To support the integration of these modular systems, a Field-Programmable Gate Array (FPGA) can …

Simultaneous And Multiplexed Measurement Of Curvature And Strain Based On Optical Fiber Fabry-Perot Interferometric Sensors, Chen Zhu, Hongkun Zheng, Osamah Alsalman, Wassana Naku, Lingmei Ma

Electrical and Computer Engineering Faculty Research & Creative Works

Optical fiber sensors that have a compact size and the capability for multi-parameter sensing are desired in various applications. This article reports a miniaturized optical fiber Fabry-Perot interferometric sensor with a length of hundreds of µm that is able to simultaneously measure variations of curvature, temperature, and strain. The sensor is easy to fabricate, requiring only the fusion splicing of a short section of the silica capillary tube between two single-mode fibers (SMFs). The combined mechanism of the Fabry-Perot interference occurred in the two interfaces between the capillary and the SMFs, and the Anti resonant guidance induced by the capillary …

Analysis And Application Of Finite Element And High-Order Finite Difference Methods For Maxwell’S Equations In Complex Media, Li Zhu

UNLV Theses, Dissertations, Professional Papers, and Capstones

The Perfectly Matched Layer (PML) technique is an effective tool introduced by B´erenger [13] to reduce the unbounded wave propagation problem to a bounded domain problem. This dissertation focuses on two different PML models and their applications to wave propagation problems with Maxwell’s equation in complex media. We investigate these models using two popular numerical methods: the Finite Difference Method (FDM) in Chapters 2 and 3, and the Finite Element Method (FEM) in Chapters 4 and 5.In Chapter 2, we focus on analyzing the stability of a PML developed by B’ecache et al. [10] for simulating wave propagation in the …

Analyzing Energy Use From Arkansas Public School Buildings, Oscar Morton

Biological and Agricultural Engineering Undergraduate Honors Theses

Energy is a key global resource in society and greenhouse gas (GHG) emissions related to the consumption of energy have detrimental effects on the planet. With energy consumption increasing, exponential population growth, and diminishing natural resources necessary for energy production, the relevance of energy efficiency is dramatically increasing. In this project, I analyzed energy usage data from a set of public school buildings from one school district in northwest Arkansas from 2018, before targeted energy efficiency practices were implemented, through 2022 to see if energy usage changed over this short period. The objectives of analyzing energy data were to determine …

Analysis And Implementation Of A New High-Buck Dc-Dc Converter With Interleaved Output Inductors And Soft Switching Capability, Sajad Ghabeli Sani, Mohamad Reza Banaei, Seyed Hossein Hosseini

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes an innovative structure for DC-DC converters with high buck gain by using a lower number of elements. The converter provides highly efficient output power and an extended output voltage range. In addition, the distribution of output current between two inductors and the soft-switching capability of the power switches have made the converter suitable for applications that require high output current. All power switches accomplish the ZVZCS (zero-voltage and zero-current switching) condition with the aid of a small auxiliary inductor (Lx), which charges and discharges parallel capacitors of main switches to provide soft-switching conditions. Thus, the switching losses …

An Efficient Deep Learning Architecture For Turkish Lira Recognition And Counterfeit Detection, Burak İyi̇kesi̇ci̇, Ergun Erçelebi̇

Turkish Journal of Electrical Engineering and Computer Sciences

Banknote counterfeiting is a common practice worldwide. Due to the recent developments in technology, banknote imitation has become easier than before. There are different kinds of algorithms developed for the detection of counterfeit banknotes for different countries in the literature. The earlier algorithms utilized classical image processing techniques where the implementations of machine learning and deep learning algorithms appeared with the developments in the artificial intelligence field as well as the computer hardware. In this study, a novel convolutional neural networks-based deep learning algorithm has been developed that detects counterfeit Turkish Lira banknotes and their denominations using the banknote images …

Simulating Dielectric Barrier Plasma Actuators With Varying Geometries, Cass Wiederkehr

Mechanical Engineering Undergraduate Honors Theses

The idea of Ionic Wind Propulsion has long been a topic of research for whether or not it can be used as a practical power source for flight. MIT researchers proved in 2018 that a plane with zero moving parts powered by Ionic Wind Propulsion was possible, and sustained flight could work with an internal power supply. However, due to the thin wire electrodes required to generate the ion cloud that made such propulsion possible, large amounts of drag rendered the plane extremely inefficient and impractical. Dielectric Barrier Discharge Devices (DBDs) are being investigated as to whether they can serve …

Modeling And Visualization Of Competing Escalation Dynamics: A Multilayer Multiagent Network Approach, Josh Allen

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Recent advances in military technology, such as hypersonic missiles, which can travel at more than five times the speed of sound and descend quickly into the atmosphere, give world nuclear superpowers a new edge. These advances up the game for nuclear superpowers with an extremely rapid, intense burst of military striking capability to secure upfront gains before encountering potentially overwhelming military confrontation. However, this so-called fait accompli has not been systematically studied by the United States in the perspective of the escalation philosophies of nuclear power competitors, or the mathematical modeling and visualization of multi-modal escalation dynamics. This gap may …

State Estimation And Data Fusion With Data-Driven Communication, Xiaolei Bian

LSU New Orleans Theses and Dissertations

This dissertation focuses on the systemic design of proper estimation as well as fusion techniques and data-driven communication schemes to infer the state of a dynamic discrete-time linear system over a wireless network. The goal is to effectively extract and share key information over networks to enhance estimates of system states. Such co-design research is drawn by the need to leverage limited resources (communication bandwidth, energy and computational power) for a multitude of data and data sources in networked systems.

We first build the overarching structure by synthesizing communication and estimator/fuser, and research the collective behaviors of the system.

In …

A Nonlinear-Model-Based High-Bandwidth Current Sensor Design For Switching Current Measurement Of Wide Bandgap Devices, Xia Du, Liyang Du, Yuxiang Chen, Yuqui Wei, Andrea Stratta, H. Alan Mantooth

Electrical Engineering Faculty Publications and Presentations

With the growing adoption of wide bandgap devices in power electronic applications, current sensor design for switching current measurement has become more important. The demands for high accuracy, high bandwidth, low cost, compact size, and galvanic isolation pose significant design challenges. The conventional modeling approach for bandwidth analysis of current transformer sensors assumes that the magnetizing inductance remains constant, which does not always hold true in high-frequency operations. This can result in inaccurate bandwidth estimation and affect the overall performance of the current sensor. To address this limitation, this paper provides a comprehensive analysis of nonlinear modeling and bandwidth, considering …

Photovoltaics, Batteries, And Silicon Carbide Power Electronics Based Infrastructure For Sustainable Power Networks, Prahaladh Paniyil

All Dissertations

The consequences of climate change have emphasized the need for a power network that is centered around clean, green, and renewable sources of energy. Currently, Photovoltaics (PV) and wind turbines are the only two modes of technology that can convert renewable energy of the sun and wind respectively into large-scale power for the electricity network. This dissertation aims at providing a novel solution to implement these sources of power (majorly PV) coupled with Lithium-ion battery storage in an efficient and sustainable approach. Such a power network can enable efficiency, reliability, low-cost, and sustainability with minimum impact to the environment.

The …

The Study Of Corrosion On Additive-Manufactured Metals., Braydan Daniels

Electronic Theses and Dissertations

The purpose of this study was to investigate and compare the corrosion mechanisms between wrought and additive-manufactured (3D-printed) copper and stainless steel. The experimental procedure consisted of measuring the open circuit potential, electrochemical impedance spectroscopy, linear sweep voltammetry, Tafel analysis, surface topology, and scanning electron microscopy for each metal within salt water, tap water, sulfuric acid, and synthetic body fluid (excluding copper in synthetic body fluid).

Overall, printed stainless steel was more corrosion-resistant than wrought stainless steel in tap water and synthetic body fluid based on OCP, LSV, and surface topology results. Additionally, printed copper was more corrosion-resistant than wrought …

Measurements Of Magnetic Field Penetration Of Materials For Superconducting Radiofrequency Cavities, Iresha Harshani Senevirathne

Physics Theses & Dissertations

Superconducting Radio Frequency (SRF) cavities used in particle accelerators are typically formed from or coated with superconducting materials. Currently high purity niobium is the material of choice for SRF cavities which have been optimized to operate near their theoretical field limits. This brings about the need for significant R&D efforts to develop next generation superconducting materials which could outperform Nb and keep up with the demands of new accelerator facilities. To achieve high quality factors and accelerating gradients, the cavity material should be able to remain in the superconducting Meissner state under high RF magnetic field without penetration of quantized …

Entropy Aided Rf-Dna Fingerprint Learning From Gabor-Based Images, Mohamed Alfatih Taha

Masters Theses and Doctoral Dissertations

The number of devices connected to the internet have been increasing and shape Internet of Things (IoT). The security of IoT is an issue due to the use of weak or no encryption. Specific Emitter Identification (SEI) was introduced to overcome this issue by introduce RF-DNA fingerprinting exploring the PHY layer features. Recently, The SEI performance improved by the usage of the signal’s Time Frequency (TF) representation and accelerated using the Deep learning (DL) Convolutional Neural Network (CNN). While the classification accuracy has been improved from using raw signals learning the amount of data generated is large and computationally expensive. …

Formation Control Of Multiple Quadrotors, Miguel Alejandro Garcia

Theses and Dissertations

This thesis studies formation control of multiple quadrotors under different conditions. Two controller design approaches are proposed. In the first approach, it is assumed that the dynamics of each quadrotor is unknown and there is disturbance. With the aid of distributed estimation and the universal approximation property of neural networks, distributed tracking controllers are proposed. Simulation shows the effectiveness of the proposed controllers. In the second approach, it is assumed that the inertia parameters are unknown. With the aid of distributed estimation, online data estimation, and optimal control theory, distributed sub-optimal tracking controllers are proposed. Simulation results show the effectiveness …

Graphene-Conductive Ink Coated Laser Engraved Kapton Electrochemical Biosensor For The Detection Of Dopamine And Immune Sensing, Dipannita Ghosh

Theses and Dissertations

Novel and flexible disposable laser-engraved Kapton (LEK) electrodes modified with graphene conductive inks have been developed for dopamine and Interleukin-6 (IL-6) detection. The LEK sensors exhibit high reproducibility (RSD=0.76%, N=5) and stability (RSD=4.39%, N=15)after multiple bendings, and thus make the sensors ideal for wearable and stretchable bioelectronics applications. We have developed graphene conductive ink- PEDOT:PSS (G-PEDOT:PSS) and polyaniline (G-PANI) based electrode coatings for working electrode modification to improve the sensitivity (41.41 times higher for screen printed electrode with G-PEDPT:PSS ink modification),and limit of detection (LOD) . We have further compared the performance of the fabricated electrodes with commercially available screen-printed …