Engineering Commons^™

Building Energy Modeling And Studies Of Electric Power Distribution Systems With Distributed Energy Resources, Evan S. Jones

Theses and Dissertations--Electrical and Computer Engineering

There is significant opportunity for savings in energy and investment from improved performance of electric Power Distribution Systems (PDSs) through optimal planning and operation of conventional voltage-controlling devices. Novel multi-step model conversion and optimal capacitor planning (OCP) procedures are proposed for large-scale utility PDSs and are exemplified with an existing utility circuit of approximately 4,000 buses. Simulated optimal control and operation is achieved with a cluster-based approach that utilizes load-forecasting to minimize equipment degradation by intelligently dispersing device setting adjustments over time such that they remain most applicable. Improved performance may also be achieved through smart building technologies and Virtual …

Optimal Design Of Special High Torque Density Electric Machines Based On Electromagnetic Fea, Murat G. Kesgin

Theses and Dissertations--Electrical and Computer Engineering

Electric machines with high torque density are essential for many low-speed direct-drive systems, such as wind turbines, electric vehicles, and industrial automation. Permanent magnet (PM) machines that incorporate a magnetic gearing effect are particularly useful for these applications due to their potential for achieving extremely high torque density. However, when the number of rotor polarities is increased, there is a corresponding need to increase the number of stator slots and coils proportionally. This can result in manufacturing challenges. A new topology of an axial-flux vernier-type machine of MAGNUS type has been presented to address the mentioned limitation. These machines can …

Blockchain And Puf-Based Secure Key Establishment Protocol For Cross-Domain Digital Twins In Industrial Internet Of Things Architecture, Khalid Mahmood, Salman Shamshad, Muhammad Asad Saleem, Rupak Kharel, Ashok Kumar Das, Sachin Shetty, Joel J. P. C. Rodrigues

VMASC Publications

Introduction:: The Industrial Internet of Things (IIoT) is a technology that connects devices to collect data and conduct in-depth analysis to provide value-added services to industries. The integration of the physical and digital domains is crucial for unlocking the full potential of the IIoT, and digital twins can facilitate this integration by providing a virtual representation of real-world entities.

Objectives:: By combining digital twins with the IIoT, industries can simulate, predict, and control physical behaviors, enabling them to achieve broader value and support industry 4.0 and 5.0. Constituents of cooperative IIoT domains tend to interact and collaborate during their complicated …

Adversarial Attacks, Coarse Robustness, And Dataless Neural Networks: Novel Techniques For Improved Classification And Combinatorial Optimization, Ismail Alkhouri

Electronic Theses and Dissertations, 2020-2023

Neural networks (NN) have become a central component in most machine learning systems. However, studies have shown that these models are not robust against adversarial attacks. As such, in this dissertation, we explore four directions. In the first direction, we investigate adversarial attacks on two hierarchical classification (HC) models: the Flat HC (FHC), and the Top-Down HC (TDHC). In particular, we formulate attacks against these models by using convex programming. Through experimental results, it is shown that FHCs are more robust than TDHCs. Second, we formalize a new notion of coarse robustness that is defined with respect to a specified …

Design And Control Of A Dual Active Bridge Converter For Electric Vehicle (Ev) And Photovoltaic (Pv) Applications, Md Safayatullah

Electronic Theses and Dissertations, 2020-2023

With the growing concerns of climate change due to fossil fuel-based electricity generation, solar integration to the grid is swiftly increasing. However, the intermittency of solar power is a major obstacle to harness it efficiently. Energy storage system (ESS) with its declining price over the last few years is a viable solution to address this issue. Another source of greenhouse gas emission is fossil fuel-based transportation system which is likely to be replaced by electric vehicles (EVs) in near future. To match the driving range of EVs with the internal combustion engine-based vehicle, fast and extreme fast charging infrastructure in …

Eece 4280: Electrical/Computer Engineering Design (Syllabus), Madhusudhanan Balasubramanian

Electrical and Computer Engineering Syllabi Archive

Course Description: Implementation of team design project as part of the culminating major design experience that requires application of electrical engineering and/or computer engineering concepts. Oral and written presentations required.

Eece 4279: Professional Development (Syllabus), Madhusudhanan Balasubramanian

Electrical and Computer Engineering Syllabi Archive

Course Description: Design, ethics, standards, participation in professional organizations; preparation for licensing; preparation for senior design project; contemporary issues and the impact of engineering solutions in a global, economic, environmental, and societal context.

Parallel Real Time Rrt*: An Rrt* Based Path Planning Process, David Yackzan

Theses and Dissertations--Mechanical and Aerospace Engineering

This thesis presents a new parallelized real-time path planning process. This process is an extension of the Real-Time Rapidly Exploring Random Trees* (RT-RRT*) algorithm developed by Naderi et al in 2015 [1]. The RT-RRT* algorithm was demonstrated on a simulated two-dimensional dynamic environment while finding paths to a varying target state. We demonstrate that the original algorithm is incapable of running at a sufficient rate for control of a 7-degree-of-freedom (7-DoF) robotic arm while maintaining a path planning tree in 7 dimensions. This limitation is due to the complexity of maintaining a tree in a high-dimensional space and the network …

Generalizable And Adaptable Data-Driven Methods For Overcoming Barriers To Practical Industrial Condition Monitoring, Matthew B. Russell

Theses and Dissertations--Electrical and Computer Engineering

The future of smart manufacturing relies on predictive maintenance systems that intelligently minimize expensive downtime through timely assessment of machine condition. Deep Learning (DL) has achieved excellent performance in industrial condition monitoring experiments, but the constraints of the manufacturing environment prevent many algorithms from being practically deployed on the factory floor. Ubiquitous sensing from online machines generates high velocity data streams that require new techniques for efficient transmission and storage. Despite these ever-increasing data lakes, many applications still lack the data needed for training DL fault diagnosis and wear tracking models since most data is unlabeled and only from nominal …

Unmanned Aircraft Systems For Precision Meteorology: An Analysis Of Gnss Position Measurement Error And Embedded Sensor Development, Karla S. Ladino

Theses and Dissertations--Biosystems and Agricultural Engineering

The overarching objective of this research was to enhance our comprehension of the three-dimensional precision of meteorological measurements obtained using small unmanned aircraft systems (UAS). Two complimentary experiments were conducted to achieve this objective.

The first experiment entailed the development and implementation of a system to determine the global navigation satellite system (GNSS) position accuracy on a UAS platform. This system was utilized to assess the static and dynamic accuracy of L1 and L1/L2 GNSS receivers in real-time kinematic (RTK) and non-RTK fix modes. Adjusted two-sample t-tests revealed significant differences in horizontal and vertical error between RTK and non-RTK receivers …

Examining Direct Load Control Within Demand Response Programs, Maria Bonina Zimath

Honors Undergraduate Theses

The power system is a complex entity with unique plant designs, control systems, and market strategies. For many years, engineers have developed advanced technology to keep the grid efficient and balanced. With the rise of renewable sources, some new technology and programs must be developed to keep the quality of the power system. Unlike traditional power plants, renewable energy is highly dependent on environmental factors, such as sunlight and wind, meaning the generation depends on an unpredictable source of fuel. As the grid moves to more sustainable sources, the power market faces a growing challenge of less control over the …

A Review Of Iot Security And Privacy Using Decentralized Blockchain Techniques, Vinay Gugueoth, Sunitha Safavat, Sachin Shetty, Danda Rawat

Electrical & Computer Engineering Faculty Publications

IoT security is one of the prominent issues that has gained significant attention among the researchers in recent times. The recent advancements in IoT introduces various critical security issues and increases the risk of privacy leakage of IoT data. Implementation of Blockchain can be a potential solution for the security issues in IoT. This review deeply investigates the security threats and issues in IoT which deteriorates the effectiveness of IoT systems. This paper presents a perceptible description of the security threats, Blockchain based solutions, security characteristics and challenges introduced during the integration of Blockchain with IoT. An analysis of different …

Process Optimization And Characterization Of P-Type Copper Indium Oxide And Copper Chromium Oxide Transparent Conducting Thin Films And Its Applications, Fnu Sreeram Sundaresh

Electronic Theses and Dissertations, 2020-2023

Transparent conducting oxides (TCO) are a unique class of compounds that combine the properties of being optically transparent but at the same time are electrically conductive. TCOs are used in a variety of applications such as transparent contacts for solar cells, electrochromic windows, low-e windows, optoelectronic devices, light-emitting diodes, optical displays, UV sensors, defrosting windows, etc. By controlling doping and by adjusting the donor/acceptor levels, the conductivity of TCOs can be tuned from insulating via semiconducting to conducting. Various properties of TCOs such as optical transparency, bandgap, and electrical conductivity can be controlled using the aforementioned process. This concept paved …

Dataset For Effects Of Single-Session Practice Structure On Motor Skill Acquisition And Alpha And Beta Eeg Oscillations, Audrey Porter, Ronald V. Croce, Wayne Smith

Faculty Publications

Although it is known that practicing a motor skill updates the associated internal model, it is still unclear as to how cortical oscillations linked with the motor skill change under differing practice schedules. The current study investigated α- and β-power changes associated with motor skill acquisition. Firstly, we investigated the behavioral effects of practice on motor learning and retention during repetitive (RP) and variable (VP) practice schedules on an anticipation timing task. Secondly, we investigated changes in cortical α (10-13 HZ) and β (15-30 Hz) event-related synchronization and dyssynchronization (ERS/ERD) under RP and VP during early (EP) and late …

Object Detection And Classification In The Visible And Infrared Spectrums, Domenick D. Poster

Graduate Theses, Dissertations, and Problem Reports (ETD)

The over-arching theme of this dissertation is the development of automated detection and/or classification systems for challenging infrared scenarios. The six works presented herein can be categorized into four problem scenarios. In the first scenario, long-distance detection and classification of vehicles in thermal imagery, a custom convolutional network architecture is proposed for small thermal target detection. For the second scenario, thermal face landmark detection and thermal cross-spectral face verification, a publicly-available visible and thermal face dataset is introduced, along with benchmark results for several landmark detection and face verification algorithms. Furthermore, a novel visible-to-thermal transfer learning algorithm for face landmark …

System Analysis Of An Internal Combustion Engine (Ice) – Solid Oxide Fuel Cell (Sofc) Hybrid Cycle, Jose Javier Colon Rodriguez

Graduate Theses, Dissertations, and Problem Reports (ETD)

Due to the intermittent nature of renewable energy and the rigid operation of existing coal plants, the need for flexible power generation technology is eminent. Hybrid energy systems have shown potential for flexible, grid following dynamics while maintaining higher efficiencies. The work below focuses on the performance analysis of a proposed 100 kW pressurized Internal Combustion Engine (ICE) and Solid Oxide Fuel Cell (SOFC) hybrid system. The un-utilized fuel from the SOFC stack provided the chemical energy to operate the engine. A turbocharger was used to deliver the necessary air flow for both the stack and engine. An external reformer …

Ai-Driven Security Constrained Unit Commitment Using Predictive Modeling And Eigen Decomposition, Talha Iqbal

Graduate Theses, Dissertations, and Problem Reports (ETD)

Security Constrained Unit Commitment (SC-UC) is a complex large scale mix integer constrained optimization problem solved by Independent System Operators (ISOs) in the daily planning of the electricity markets. After receiving offers and bids, ISOs have only few hours to clear the day-ahead electricity market. It requires a lot of computational effort and a reasonable time to solve a large-scale SC-UC problem. However, exploiting the fact that a UC problem is solved several times a day with only minor changes in the system data, the computational effort can be reduced by learning from the historical data and identifying the patterns …

Biogeography Based Optimization With Salp Swarm Optimizer Inspired Operator For Solving Non-Linear Continuous Optimization Problems, Vanita Garg, Kusum Deep, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Ali Wagdy Mohamed

Articles

In this paper, a novel attempt is made to incorporate the two effective algorithm strategies, where BBO has a strong exploration and Salp Swarm Algorithm (SSA) is used for exploitation of the search space. The proposed algorithm is tested on IEEE CEC 2014 and statistical, convergence graphs are given. The proposed algorithm is also applied to 10 real life problems and compared with its counterpart algorithm. Results obtained by above experiments have demonstrated the outperformance of the hybrid version of BBO over other algorithms.

Do Games Reduce Math Anxiety? A Meta-Analysis, Pierpaolo Dondio, Viacheslav Filonenko, Mariana Rocha

Articles

In this paper, we meta-analyse the empirical evidence about the effectiveness of game-based interventions to reduce students' level of math anxiety. After performing a search for randomised controlled studies relevant to game-based intervention for math anxiety, 16 experimental studies with a total of 686 participants described in 11 peer-review articles met the selection criteria.A random-effects meta-analysis indicated a small and non-significant reduction of math anxiety (mean effect size ES=-0.32, CI=[-0.64,0.01]). The results were moderated by several factors: non-digital games were more effective, while digital games had a negligible mean effect size of $ES=-0.13$, $CI=[-0.33,0.08]$. The effect size was moderated also …

Wavelet-Based Real-Time Harmonic Phasor Estimation In Complex Signals With Inter-Harmonics And Transient Events, M A Aziz Jahan

Dissertations, Master's Theses and Master's Reports

Addressing the evolving challenges in modern power systems induced by the integration of Inverter Based Resources (IBRs), such as solar inverters, wind turbine converters, electric vehicle charging stations etc is the main goal of this research. The study focuses on the critical task of harmonic phasor estimation in the presence of sub-harmonics, inter-harmonics, time-varying harmonics, DC offset, transient events, and other power quality disturbances. A novel wavelet-based harmonic phasor estimation method is proposed to enhance accuracy, particularly during transient events, ensuring a nuanced understanding of phase angle variations. The research emphasizes the versatility of wavelet analysis for both steady-state and …

Advancing Vehicular Communication Systems: An Evolution From Dsrc To 5g Nr C-V2x Technology For Enhanced Safety, Reliability, And Efficiency In Intelligent Transportation Systems, Mehnaz Tabassum

Dissertations, Master's Theses and Master's Reports

This work focuses on the evolution of connected vehicles communication technologies and performance evaluation of vehicular communication systems, specifically in the context of Cellular Vehicle-to-Everything (C-V2X) technology and the Third Generation Partnership Project (3GPP) specifications. The dissertation also discusses the evolution of vehicle communication systems from Dedicated Short-Range Communication (DSRC) through 5G technologies. It examines the motivation for this shift, which are the growing demand for transportation safety, low latency, high data rate, low energy use, and seamless inter connectivity. The research delves into the greater capabilities and improved performance that 5G offers for direct V2V communications by analyzing the …

Development And Verification Of Automated Fixtures For Functional Testing Of Space Grade Printed Circuit Board Assemblies, Nicholas A. Wylie

Dissertations, Master's Theses and Master's Reports

Orbion Space Technology is a developer and manufacturer of electric propulsion systems for military and commercial spacecraft. Orbion’s products include a Power Processing Unit (PPU) which is utilized for power and control of the satellite propulsion system. These PPUs are complex electro-mechanical assemblies that include multiple Printed Circuit Board Assemblies (PCBA) and are built to IPC standards. To ensure smooth fabrication and to reduce the risk of complications from in-process rework of PCBAs, comprehensive electrical functional testing at the board-level is required before higher- level assembly. Electrical functional testing provides verification of quality, workmanship, and manufacturing defects of the PCBAs. …

Novel Bayesian Neural Networks And Uncertainty Quantification Of Computational Mechanics Models, Ponkrshnan Thiagarajan

Dissertations, Master's Theses and Master's Reports

Computational and data-driven models suffer from a wide range of uncertainties that impact the reliability of such models. Given the exponential proliferation of machine learning models in real-world systems, establishing a degree of confidence in their predictions becomes paramount. Reliability in predictions takes on utmost significance in domains such as autonomous driving, medical image analysis, etc., where human lives are involved, and inaccuracies in predictions could lead to disastrous outcomes. For these reasons, comprehending and quantifying uncertainties in computational and data-driven models is of utmost importance. A number of techniques have been developed to quantify uncertainties in machine learning models. …

Investigating The Effects Of Network Dynamics On Quality Of Delivery Prediction And Monitoring For Video Delivery Networks, Obinna C. Izima

Doctoral

Video streaming over the Internet requires an optimized delivery system given the advances in network architecture, for example, Software Defined Networks. Machine Learning (ML) models have been deployed in an attempt to predict the quality of the video streams. Some of these efforts have considered the prediction of Quality of Delivery (QoD) metrics of the video stream in an effort to measure the quality of the video stream from the network perspective. In most cases, these models have either treated the ML algorithms as black-boxes or failed to capture the network dynamics of the associated video streams.

This PhD investigates …

Series-Fed Omnidirectional Mm-Wave Dipole Array, Neeraj Kumar Maurya, Max Ammann, Patrick Mcevoy

Articles

THE rapid expansion in the millimeter-wave (mm-wave) frequency domain has completely changed the course of wireless communication. One of the most important steps to make smart cities, the Internet-of-Things (IoT), smart homes, and vehicular communication a reality is to use mm-wave frequencies for wireless applications. The rise in the number of wireless appliances has also led to a rise in data traffic [1]. The adoption of mm-wave frequencies enabled several gigahertz of bandwidth, allowing data rate and latency limits to be exceeded. The availability of a broad electromagnetic spectrum and frequency reusability are the most important characteristics of mm-wave deployment …

Implementation And Optimization Of Multi-Resonance And Phase Control Of The Electrical Power Take-Off On A Wec Array For Improved Performance, Madelyn G. Veurink

Dissertations, Master's Theses and Master's Reports

Many governments around the world are pledging to reduce their consumption of fossil fuels as they look to curb the amount of green house gasses they release into the atmosphere. These green house gasses are what scientists blame for global warming and the recent increase in extreme weather events. Producing electricity is one of the largest producers of these gasses but utilizing renewable sources can greatly decrease the amount of green house gasses produced. Common forms of renewable energies are wind and solar and both of these green energies have reached a state of maturation where they are economically viable …

Design Of Next-Generation Neural Interfaces For Decoding The Brain, Yi Qiang

Dartmouth College Ph.D Dissertations

The primary goal of neural interface technology is to establish a connection between the nervous system and the external world by recording and modulating neural signals. Over the past few decades, microelectrode array (MEA) technology has played an essential role in the acquisition of electrophysiological signals, with impressive progress being made towards developing high-density, large-throughput, and ultra-flexible MEAs. However, despite these advancements, there remain long-standing limitations in current neural interfaces. For example, electrophysiology is limited in its ability to distinguish cell types and has limited spatial resolution due to its electrical recording nature. Furthermore, conventional neural MEAs are limited to …

Running Shoe Pedometer, Benjamin Kasper

Williams Honors College, Honors Research Projects

Running shoe pedometer aims to solve the issue of worn out running shoes. It can be difficult to know just how many miles you have run in your shoes and when a new pair is needed. Running in old shoes and worn out shoes is heavily linked to injury. My proposed project is a device that is powered by the compressive forces on the shoes soles that counts the number of steps the wearer takes using a microcontroller. Then, when the shoe reaches milestone that indicate it has been used 75% 90% and 100% of its expected life, it will …

Life Cycle Assessment Of Air Classification As A Sulfur Mitigation Technology In Pine Residue Feedstocks, Ashlee Edmonson

Theses and Dissertations--Biosystems and Agricultural Engineering

Sulfur accumulation during biofuel production is pollutive, toxic to conversion catalysts, and causes the premature breakdown of processing equipment. Air classification is an effective preprocessing technology for ash and sulfur removal from biomass feedstocks. A life cycle assessment (LCA) sought to understand the environmental impacts of implementing air classification as a sulfur-mitigation technique for pine residues. Energy demand and material balance for preprocessing were simulated using SimaPro and the Argonne National Laboratory’s GREET model, specifically focusing on comparing the global warming potential (GWP) of grid electricity versus bioelectricity scenarios. Overall, the grid electricity scenario had a GWP impact over 7 …

Robotic Inspection And Data Analytics To Localize And Visualize The Structural Defects Of Civil Infrastructure, Jinglun Feng

Dissertations and Theses

Ground Penetrating Radar (GPR) serves as a significant nondestructive evaluation (NDE) technique to inspect and survey underground objects (e.g., rebars, utility pipes) in complex urban environments. In addition to GPR, visual-based surface defect detection plays a crucial role in assessing and maintaining civil infrastructure. To facilitate deployment on a robotic platform and enhance inspection capabilities, the integration of GPR and visual-based sensors, such as RGB-D cameras, is crucial to obtain accurate subsurface and surface information. This thesis presents a novel robotic-based inspection system for the efficient collection of NDE data and accurate 3D reconstruction of both subsurface and surface infrastructure …