Digital Commons Network^™

Reaction Wheel Based Rocket Active Spin Stabilization, Tanuj Vemuri

Electrical Engineering

Cal Poly Space Systems is the high-powered and experimental rocketry club at Cal Poly SLO. They aim to design, test, and launch fully integrated launch vehicles. In order to create efficient and reliable vehicles, stabilization systems must be implemented. One parameter that can be actively stabilized is the vehicle’s roll. The roll of the vehicle can have noticeably effects on vehicle performance, as uncontrolled roll leads to decreased system stability in flight. Un-controlled roll can also have negative impacts on the quality of onboard video, which is used for post-flight analysis and marketing.

Reaction wheels are a popular method for …

Bearing Health Detector, Natalie N. Tokhmakhian, Alexander J. Davis

Electrical Engineering

Bearings, a common component in rotating machinery, are essential components of modern rotating machines; thus, monitoring their health is crucial when reducing downtime and boosting production efficiency. The Bearing Health Detector (BHD), a hand-held device, captures and processes the sound of a machine under test in real time and estimates the level of wear and tear by comparing the sound to previous tests. The BHD encompasses audiences involved with roller bearings in rotating machinery and is designed to provide the diagnosis of wear through the universal detection of good, satisfactory, and very poor with the following color scheme: green, yellow, …

Neural Compression Inference Accelerator: A Cost And Energy-Effective Alternative To Conventional Machine Learning Inference Methods, Matthew Wallace

Master's Theses

Recent developments in machine learning and artificial intelligence have sparked an influx of workloads that require specialized computer hardware for cloud services. The hardware running machine learning models predominantly consists of graphics processing units (GPUs) and tensor processing units (TPUs). However, these com- ponents are expensive for cloud services to purchase, costly for customers to rent, prone to price spikes, and energy-intensive. In this research we show that both cloud services and customers would benefit from utilizing field programmable gate arrays (FPGAs) to alleviate the aforementioned challenges. An FPGA can be configured as a machine learning accelerator, operating similarly to …

Co-Simulation Of Electric Power Distribution Systems And Buildings Including Ultra-Fast Hvac Models And Optimal Der Control, Evan S. Jones, Rosemary E. Alden, Huangjie Gong, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Smart homes and virtual power plant (VPP) controls are growing fields of research with potential for improved electric power grid operation. A novel testbed for co-simulation of electric power distribution systems and distributed energy resources (DERs), is employed to evaluate VPP scenarios and propose an optimization procedure. DERs of specific interest include behind-the-meter (BTM) solar photovoltaic (PV) systems as well as heating, ventilation, and air-conditioning (HVAC) systems. Simulation of HVAC systems is enabled by a machine learning procedure that produces ultra-fast models for electric power and indoor temperature of associated buildings that are up to 133 times faster than typical …

Analog Circuits For Computing, Nicole Christine Pickett, Lauren Cathy Sueko Chun, Dillon Ryan Nguyen

Electrical Engineering

This project entails designing, simulating, and verifying analog circuits that can perform essential computing functions for power systems applications. The project aims to remedy critical challenges associated with handling calculations digitally, namely, time and power. This project's scope includes creating a library of circuits in SPICE that can be used to model and simulate complex mathematical equations. From these SPICE models, the circuit can be constructed physically, where the solution can be generated in less time using less power than doing the computation digitally. The performance and efficiency of analog computing will be measured and compared to conventional digital methods.

Detecting Alzheimer's Disease Using Artificial Neural Networks, Sally Lee, Mia Keegan

Electrical Engineering

This project aims to use artificial neural networks (ANN) in order to detect Alzheimer’s disease. More specifically, convolutional neural networks (CNN) will be utilized as this is the most common ANN and has been used in many different image processing applications. The purpose of using artificial neural networks as a detect method is so that an intelligent way for image and signal analysis can be used. A software that implements CNN will be developed so that users in medical settings can utilize this software to detect Alzheimer’s in patients. The input for this software will be the patient’s MRI scans. …

Variable Frequency Motor Drive Application, Jason G. Milne, Nick Mark

Electrical Engineering

This project entails the development of an electrical engineering undergraduate lab module focusing on utilizing a variable frequency drive (VFD) controlled with a programmable logic controller (PLC) — the Modicon M580. The variable frequency drive is a device that is able to automatically change the frequency of an object through automation without having to physically change the device that is being controlled (ex: fans, pumps, motors, etc.). This project will guide students to understand the software for programming and controlling the PLC within a 3 hour laboratory experiment. Throughout the lab, the students will learn how to implement the PLC …

Cardio Trainer, Levi Rash, Cristian Rodriguez

Electrical Engineering

The Cardio Trainer Device is a wearable device that guides the user through a physical exercise based on the user’s heartbeat measurements. Users interface with the device via a wearable band. The band determines the heartbeat of the user in real time and, using that reading, gives the user verbal instructions to optimize their workout. These verbal instructions then serve to control the physical exertion of the user and are delivered through an audio device. Users input personal physical metrics to the Cardio Trainer Device that tailor the performance of the device in a manner of ways: rate of instruction, …

Wideband Parameter Estimation Of Overhead Transmission Lines From Terminal Measurements, Fahad J. Alqahtani

Dissertations

The accurate and efficient determination of electrical parameters of transmission lines is essential when performing computer-aided analyses of power systems, including power-flow, state estimation, short-circuit, transient stability, power quality, and electromagnetic transients.

In this dissertation, a novel technique for wideband parameter estimation of frequency-dependent single-phase, three-phase transposed, and three-phase untransposed overhead lines, is proposed. The proposed technique utilizes terminal measurements of transient voltages and currents and is based on an analytical approach to solve the frequency domain 2-port nodal model of the line for the series impedance and shunt conductance per unit length as a function of the frequency. The …

Participation Of Electric Vehicle Aggregators In Wholesale Electricity Markets: Recent Works And Future Directions, Saeed Salimi Amiri, Fazlur Rahman Bin Karim, Pedro Cesar Lopes Gerum

Electrical and Computer Engineering Faculty Publications

Electric Vehicles are key to reducing carbon emissions while bringing a revolution to the transportation sector. With the massive increase of EVs in road networks and the growing demand for charging services, the electric power grid faces enormous system reliability and operation stability challenges. Demand and supply disparities create inconsistency in the smooth delivery of electrical power. As a potential solution, EVs and their charging infrastructure can be aggregated to prevent the unwanted effects on power systems and also facilitate ancillary services to the power grid. When not need for transportation purposes, EVs can leverage their batteries for power grid …

Emitter Selection Optimization For Passive Synthetic Aperture Radar, Mu Kim

Theses and Dissertations

Widely distributed modern communication networks provide excellent opportunities to share the spectrum for passive radar systems, of which emitter selection is a major consideration factor. This research introduces emitter selection problem space, which consists of three SAR processing domains, namely, Data Collection, Image and Mission Performance Domains. Quantitative links between these domains are critical to formulate an optimal emitter selection problem in the Data Collection Domain and/or Image Domain, which satisfies given mission requirements in Mission Performance Domain. This research examines the properties of the SAR processing domains to develop performance metrics in the Data Collection and Image Domains, whose …

Exploring The Potential Of Pavegen’S Kinetic Energy Generating Floor For Sustainable Energy Solutions: A Proposal For Cal Poly Slo, Brandon J. Cuneo

Construction Management

This paper proposes the installation of Pavegen's kinetic energy generating floors at Cal Poly’s campus as a sustainable energy solution. Pavegen has developed a pioneering technology that converts footsteps into clean and renewable energy. The versatility of these floors is demonstrated through successful implementations in various settings, such as transportation hubs and public spaces, generating power from foot traffic. Collaborations with Schneider Electric, installation at Dupont Circle, and integration at Heathrow Airport showcase the potential for sustainable urban infrastructure. This paper outlines research conducted on Pavegen and similar solutions, including communication with company representatives and examining proposed installation locations at …

Novel Approach For Non-Invasive Prediction Of Body Shape And Habitus, Emma Young

Electronic Theses and Dissertations

While marker-based motion capture remains the gold standard in measuring human movement, accuracy is influenced by soft-tissue artifacts, particularly for subjects with high body mass index (BMI) where markers are not placed close to the underlying bone. Obesity influences joint loads and motion patterns, and BMI may not be sufficient to capture the distribution of a subject’s weight or to differentiate differences between subjects. Subjects in need of a joint replacement are more likely to have mobility issues or pain, which prevents exercise. Obesity also increases the likelihood of needing a total joint replacement. Accurate movement data for subjects with …

Time-Domain Shielding Effectiveness Analysis Based On Dgtd Method Accelerated By Local Time-Stepping And Parallel Techniques, Zheng Lang Jia, Huan Huan Zhang, Da Zhi Ding, Lei Zhao, Qiang Ren, Li (Lijun) Jun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

The discontinuous Galerkin time-domain (DGTD) method accelerated by local time-stepping (LTS) and parallel techniques is employed to analyze the time-domain shielding effectiveness (TDSE) of metallic enclosures. The detailed formulations and implementation procedures of the DGTD method and LTS and parallel techniques are introduced. Numerical results validate the correctness of the proposed method. Moreover, the influence of various design parameters of the metallic enclosure, including aperture dimensions, wall thickness, spacing of aperture arrays, etc., on the TDSE are analyzed by the proposed method. Some rules are given for the design of the enclosure with rectangular apertures from the perspective of TDSE. …

Neuroevolution Application To Collaborative And Heuristics-Based Connected And Autonomous Vehicle Cohort Simulation At Uncontrolled Intersection, Frederic Jacquelin, Jungyun Bae, Bo Chen, Darrell Robinette

Michigan Tech Publications

Artificial intelligence is gaining tremendous attractiveness and showing great success in solving various problems, such as simplifying optimal control derivation. This work focuses on the application of Neuroevolution to the control of Connected and Autonomous Vehicle (CAV) cohorts operating at uncontrolled intersections. The proposed method implementation’s simplicity, thanks to the inclusion of heuristics and effective real-time performance are demonstrated. The resulting architecture achieves nearly ideal operating conditions in keeping the average speeds close to the speed limit. It achieves twice as high mean speed throughput as a controlled intersection, hence enabling lower travel time and mitigating energy inefficiencies from stop-and-go …

A Magneto-Thermally Controllable Microstrip-Patch Antenna For Low Rcs Applications, Sallam Mohammad Al Hendi

Theses

This research focuses on the development of a novel technique for reducing the Radar Cross Section (RCS) of a microstrip antenna operating in the terahertz spectral regime. This can be accomplished by loading the antenna with Indium Antimonide (InSb); a thermally-magnetically controllable semi-conductor. The low-RCS feature of the antenna implies that it becomes hardly detectable by detecting radars; a desired feature in stealthy applications. For an optimal operation beside low RCS, the other antenna parameters (e.g., radiated power, gain, standing-wave ratio, and reflection coefficient) must be within tolerable ranges. Thus, a study on the effects of the temperature and the …

P-Doped Ru-Pt Alloy Catalyst Toward High Performance Alkaline Hydrogen Evolution Reaction, Rong-Qin Huang, Wei-Ping Liao, Meng-Xuan Yan, Shi Liu, Yuan-Ming Li, Xiong-Wu Kang

Journal of Electrochemistry

Electrocatalytic water splitting represents grand promise for hydrogen fuel in modern energy equipment, and the design and fabrication of higher performance catalysts are at the central. Herein, we report the sequential phosphorus (P)-doping into ruthenium (Ru) nanoparticles (Ru-P/C) by thermal annealing of Ru nanoparticles in phosphine (PH₃) atmosphere and deposition of extremely low concentration of platinum (Pt) to obtain P-doped Ru-Pt alloy catalyst supported on carbon nanotubes (CNTs), which is denoted as (Ru-P)#Pt/C. The data by X-ray diffraction spectroscopy and transmission electron microscopy show that the Ru nanoparticles existed in the form of hexagonal close-packed (hcp) phase with …

Deep Euteceic Solvents-Assisted Synthesis Of Novel Network Nanostructures For Accelerating Formic Acid Electrooxidation, Jun-Ming Zhang, Xiao-Jie Zhang, Yao Chen, Ying-Jian Fan, You-Jun Fan, Jian-Feng Jia

Journal of Electrochemistry

Deep eutectic solvents (DESs) have been reported as a type of solvent for the controllable synthesis of metal nanostructures. Interestingly, flower-like palladium (Pd) nanoparticles composed of staggered nanosheets and nanospheres are spontaneously transformed into three-dimensional (3D) network nanostructures in choline chloride-urea DESs using ascorbic acid as a reducing agent. Systematic studies have been carried out to explore the formation mechanism, in which DESs itself acts as a solvent and soft template for the formation of 3D flower-like network nanostructures (FNNs). The amounts of hexadecyl trimethyl ammonium bromide and sodium hydroxide also play a crucial role in the anisotropic growth and …

Fe Nanoparticles Encapsulated In N-Doped Porous Carbon For Efficient Oxygen Reduction In Alkaline Media, Chun-Yan Li, Rui Zhang, Xiao-Jie Ba, Xiao-Le Jiang, Yao-Yue Yang

Journal of Electrochemistry

Rational design and synthesis of non-precious-metal catalyst plays an important role in improving the activity and stability for oxygen reduction reaction (ORR) but remains a major challenge. In this work, we used a facile approach to synthesize iron nanoparticles encapsulated in nitrogen-doped porous carbon materials (Fe@N-C) from functionalized metal-organic frameworks (MOFs, MET-6). Embedding Fe nanoparticles into the carbon skeleton increases the graphitization degree and the proportion of graphitic N as well as promotes the formation of mesopores in the catalyst. The Fe@N-C-30 catalyst showed the excellent ORR activity in alkaline solutions (E₀ = 0.97 V vs. RHE, E_{1/2 …}

Cardiorespiratory Monitoring Data To Predict Respiratory Outcomes In Extremely Preterm Infants, Namasivayam Ambalavanan, Debra E. Weese-Mayer, Anna Maria Hibbs, Nelson Claure, Premananda Indic, Additional Authors, Prematurity-Related Ventilatory Control (Pre-Vent) Investigators

Electrical Engineering Faculty Publications and Presentations

Rationale: Immature control of breathing is associated with apnea, periodic breathing, intermittent hypoxemia, and bradycardia in extremely preterm infants. However, it is not clear if such events independently predict worse respiratory outcome. Objectives: To determine if analysis of cardiorespiratory monitoring data can predict unfavorable respiratory outcomes at 40 weeks postmenstrual age (PMA) and other outcomes, such as bronchopulmonary dysplasia at 36 weeks PMA. Methods: The Prematurity-related Ventilatory Control (PreVent) study was an observational multicenter prospective cohort study including infants born at 29 weeks of gestation with continuous cardiorespiratory monitoring. The primary outcome was either "favorable" (alive and previously discharged or …

Probabilistic Assessment Of Power Systems Resilience Under Natural Disasters, Enas M. Hegazy, Abdelfattah A. Eladl, Magdi M. El-Saadawi

Mansoura Engineering Journal

Extreme weather can have a substantial influence on a power system's operational resilience since they are high-impact, low-probability (HILP) events. Therefore, Power systems must be resilient to HILP incidents in addition to being reliable against widely spread and credible threats. Despite the rarity of such events, the severity of their potential impact necessitates the development of appropriate resilience assessment tools to capture their implications and enhance the resilience of energy infrastructure systems. In this paper, a probabilistic strategy is proposed to assess and evaluate the operational resilience of power distribution networks against the impacts of HILP events depending on value-at-risk …

Learning–Assisted Constraint Filtering To Enhance Power System Optimization Performance, Fouad Hasan

LSU Doctoral Dissertations

Machine learning (ML) is a powerful tool that provides meaningful insights for operators to make fast and efficient decisions by analyzing data from power systems. ML techniques have great potential to assist in solving optimization problems within a shorter time frame and with less computational burden. AC optimal power flow (ACOPF), dynamic economic dispatch (D-ED), and security-constrained unit commitment (SCUC) are the three energy management optimization functions studied in this dissertation. ACOPF is solved every 5~15 minutes. Because of the nonconvex and complex nature of ACOPF, solving this problem for large systems is computationally expensive and time-consuming. Classification and regression …

Renewable Energy Educational Delivery System, Ryan Integlia

Florida Conference on Recent Advances in Robotics

Technology advancing rapidly and affecting our daily lives in more ways than ever before, it is clear that technology is now a driving force in our world. STEM disciplines are one of the key driving forces behind human progress, as their efforts have provided us with new levels of comfort and security. Every facet of engineering contributes to enhancing almost every aspect of our lives. As technology continues to evolve, the demand for skilled engineers will only increase. Therefore, it is essential that STEM education system adapts to the needs of today's digitized, diversified, and rapidly changing society through an …

Clean Energy At The Crossroads Of America: An Integrated Resource Plan For Northern Indiana Public Service Company, Llc (Nipsco), Saad Z. Khan, Shend Boshnjaku

Master's Projects and Capstones

This paper outlines an Integrated Resource Plan (IRP) for the Indiana electric utility company, NIPSCO, looking forward to the year 2050 and evaluating different pathways to net zero emissions from the power generation sector. It is a plan for the future, identifying the most cost-effective and reliable mix of resources to meet the energy needs of NIPSCO's customers and reaching decarbonization goals by mid-century.

Towards Optimal Operation And Control Of Emerging Electric Distribution Networks, Jimiao Zhang

Theses and Dissertations

The growing integration of power-electronics converters enabled components causes low inertia in the evolving electric distribution networks, which also suffer from uncertainties due to renewable energy sources, electric demands, and anomalies caused by physical or cyber attacks, etc. These issues are addressed in this dissertation. First, a virtual synchronous generator (VSG) solution is provided for solar photovoltaics (PVs) to address the issues of low inertia and system uncertainties. Furthermore, for a campus AC microgrid, coordinated control of the PV-VSG and a combined heat and power (CHP) unit is proposed and validated. Second, for islanded AC microgrids composed of SGs and …

A Novel Graph Neural Network-Based Framework For Automatic Modulation Classification In Mobile Environments, Pejman Ghasemzadeh

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

Automatic modulation classification (AMC) refers to a signal processing procedure through which the modulation type and order of an observed signal are identified without any prior information about the communications setup. AMC has been recognized as one of the essential measures in various communications research fields such as intelligent modem design, spectrum sensing and management, and threat detection. The research literature in AMC is limited to accounting only for the noise that affects the received signal, which makes their models applicable for stationary environments. However, a more practical and real-world application of AMC can be found in mobile environments where …

A Graph-Based Approach For Adaptive Serious Games, Nidhi G. Patel

Theses and Dissertations

Traditional education systems are based on the one-size-fits-all approach, which lacks personalization, engagement, and flexibility necessary to meet the diverse needs and learning styles of students. This encouraged researchers to focus on exploring automated, personalized instructional systems to enhance students’ learning experiences. Motivated by this remark, this thesis proposes a personalized instructional system using a graph method to enhance a player’s learning process by preventing frustration and avoiding a monotonous experience. Our system uses a directional graph, called an action graph, for representing solutions to in-game problems based on possible player actions. Through our proposed algorithm, a serious game integrated …

Method Of Evanescently Coupling Whispering Gallery Mode Optical Resonators Using Liquids, Hengky Chandrahalim, Kyle T. Bodily

AFIT Patents

The present invention relates to evanescently coupling whispering gallery mode optical resonators having a liquid coupling as well as methods of making and using same. The aforementioned evanescently coupling whispering gallery mode optical resonators having a liquid couplings provide increased tunability and sensing selectivity over current same. The aforementioned. Applicants’ method of making evanescent-wave coupled optical resonators can be achieved while having coupling gap dimensions that can be fabricated using standard photolithography. Thus economic, rapid, and mass production of coupled WGM resonators-based lasers, sensors, and signal processors for a broad range of applications can be realized.

Stability Impacts Of Sandia Frequency Shift Anti-Islanding On A Grid-Connected Inverter, Daniel Mendoza

Electrical and Computer Engineering Master's Theses

Most renewable energy generation connected to the distribution level of the electric grid is connected through an inverter. To prevent an unintentional islanding condition, these inverters employ a variety of anti-islanding protection schemes. The Sandia Frequency Shift (SFS) method of anti-islanding protection is considered to be the most effective scheme built into grid-connected inverters. Much of what makes it so effective is the postive feedback loop that it creates when the inverter’s connection to the bulk power system is lost. However, this same positive feedback can have negative impacts on the stability of the inverter even when it is connected …

Long-Term Human Video Activity Quantification In Collaborative Learning Environments, Venkatesh Jatla

Electrical and Computer Engineering ETDs

Research on video activity detection has mainly focused on identifying well-defined human activities in short video segments, often requiring large-parameter systems and extensive training datasets. This dissertation introduces a low-parameter, modular system with rapid inference capabilities, capable of being trained on limited datasets without transfer learning from large-parameter systems. The system accurately detects specific activities and associates them with students in real-life classroom videos. Additionally, an interactive web-based application is developed to visualize human activity maps over long classroom videos.

Long-term video activity detection in classrooms presents challenges, such as multiple simultaneous activities, rapid transitions, long-term occlusions, duration exceeding 15 …