Engineering Commons^™

Study On The Application Of Smart Electric Meters For Secondary Voltage Protection, Jayaditya Sisodia

Master's Theses

The purpose of our research is to utilize PG&E’s Smart Meters installed across California to protect the Secondary Voltage delivered to the meter. This means detecting electrical faults between the utility’s distribution transformer and the installed Smart Meter. Our goal is to propose and implement various solutions through additional devices and protocols to detect and prevent these faults, communicate them with the meter, and forward fault information to the utility. A device will be designed to be installed on the transformer, detect faults, shut off power transmission, and communicate to the meter via fiber optic cable. Research will then be …

Open Source Asic Design Curriculum, Francisco Wilken

Master's Theses

The ever-growing importance of Application-Specific Integrated Circuits (ASICs) in a high-compute world necessitates that college graduates entering the workforce are well prepared to design them. This thesis details the design of novel ASIC curriculum, using open source tools to teach at the undergraduate level. By moving to a higher level of abstraction than classical transistor-focused coursework, chip design material can be made accessible earlier in an undergraduate degree. Additionally, open source tools provide a powerful, free, and portable platform for students to create their own designs, solving assignments focused on industry readiness. Finally, this thesis studies the results and challenges …

Remote Monitoring And Control Of Protection Relays Via Programmable Logic Controller, Rio Mcgown-Kauffman

Master's Theses

The purpose of this study is to explore the ability of a programmable logic controller (PLC) to wirelessly monitor and control power protection relays. The technologies surrounding power protection and industrial automation are ever evolving and have developed significantly in recent history. Industrial power applications call for consistent condition monitoring and status updates for various high-importance components. The high-importance components have power protection schemes that are managed by digital relays to trip circuit breakers in fault or unsafe operating conditions. The smart relays have a wide range of capabilities, including communications. Cal Poly assembled a collection of relays from Schweitzer …

Hands-Free Balance Protocol And Development Of An Iphone App For Self-Assessment, Jacob Matties

Master's Theses

For many clinical populations, the measurement of balance is a critical task. Previous studies have agreed that smartphone IMUs provide a valid measure of balance that can be significantly correlated with force plate measurements and is sensitive enough to distinguish between various balance poses, but many balance assessment protocols require uncommon equipment or the use of hands during assessment. These limit accessibility of balance assessment. To eliminate the need for hands or any additional equipment, this study assessed the use of a smartphone recording the root mean square of 3D acceleration magnitude. The goal of the study was to determine …

Modeling And Efficiency Analysis Of Hybrid Ac/Dc And Conventional Ac House Electrical Systems For Net-Zero Energy Homes, Tyler Bury

Master's Theses

This thesis presents the design, simulation, and comparative efficiency analysis of hybrid AC/DC residential homes versus conventional AC homes for Net Zero Energy Homes (NZEH). Motivated by the increasing prevalence of DC-native technologies such as solar photovoltaics, battery storage, and DC-powered electronics, this work evaluates whether hybrid AC/DC distribution can offer measurable efficiency benefits over traditional systems. Twelve detailed house models were developed—six employing a hybrid AC/DC architecture and six based on conventional AC systems, each supplying a combination of AC and DC residential loads. Simulations were conducted using MATLAB/Simulink to model steady-state efficiency under various loading conditions. Grid configurations …

Development Of A Versatile Switching Mode Inverter Laboratory Module, Zachariah Lee Mustar

Master's Theses

DC-AC converters, or inverters, are complex devices that play an essential role in photovoltaic, energy storage, and microgrid systems. Therefore, they constitute a class of power electronics that any power-focused electrical engineering student should be familiar with. This thesis presents the development and testing of a single device that power electronics students will use in a laboratory setting to experiment with each of the four different switching techniques employed in inverters: a simple square wave (SSWI), modified square wave (MSWI), bipolar PWM, and unipolar PWM. The module was built with a physically modifiable control stage and a power stage constituting …

Cislunar Orbital Debris Removal Feasibility Analysis Using Nrho To Dro Transfers At Varying Solar Angles, Peter C. Lie

Master's Theses

The resurgence of lunar exploration necessitates the expansion of space situational awareness into cislunar space. The current tracking technologies for cislunar objects are insufficient to determine vacant orbital regimes for human spaceflight. Orbital debris generated in the cislunar environment often evolves along complex and chaotic trajectories due to the influence of multi-body dynamics. Current research into methods of removing orbital debris from space is limited to debris in Earth orbits. For cislunar orbits, debris disposal options are slowly gaining research, mostly centered on hypothetical solutions for active missions. Lunar impact and escape to heliocentric space are low-cost options, but serve …

Discovering The Effective Actions Of Upstanders And Tackling Implicit Bias In The Workplace: Findings From A Workshop, Jacob H. Defreeuw

Construction Management

This project focused on exploring how both university students and construction industry professionals recognize and respond to opportunities to act as upstanders in workplace settings, particularly in support of underrepresented groups. The research aimed to bridge the gap between current industry practices surrounding implicit bias and the practical realities of advocating for inclusiveness on construction sites and in office environments. To achieve this, surveys were distributed to industry professionals, an in-depth literature review of modern upstander and implicit bias training strategies was performed, and a student-centered workshop was held at the Cal Poly Women in Construction Symposium. The workshop featured …

Optimized Electrocoagulation Pre-Treatment For Fouling Reduction During Nanofiltration Of Lake Water Containing Microcystin-Lr, Thomas Mckean, Chidambaram Tharmaraiselvan, Sarah Do, S. Ranil Wickramasinghe

Chemical Engineering Faculty Publications and Presentations

Microcystin-LR (MCLR) is a toxin produced by harmful algal blooms that is emerging as a threat to drinking and recreational water systems worldwide. Nanofiltration (NF) is an effective technique for purifying contaminated water sources; however, membrane fouling caused by coexisting organic matter limits the practicality of the process. This research studies the use of an electrocoagulation (EC) pretreatment to limit fouling during the NF process. Water for this study was taken from Lake Fayetteville, a local body of water where MCLR concentrations have been recorded to be >15 µg/L. EC was performed using polyaluminum chloride as a background electrolyte at …

Experimental Evaluation Of Novel Nano Polymer Hybrid Enhanced Oil Recovery In Carbonate Reservoir, Altamish Ahmed Pakeer

Theses

Innovative enhanced oil recovery (EOR) strategies are needed to unlock additional reserves in heterogeneous, oil-wet carbonate reservoirs. This study evaluates hybrid nano-polymer flooding by integrating silica nanoparticles (SiO₂) and single-walled carbon nanotubes (CNT) with novel HPAM polymers (Sav10 and Sav10 VHM) to optimize wettability alteration, rheological parameters, and recovery mechanisms.

A comprehensive experimental approach was employed, where rheological tests assessed viscosity enhancement under varying shear conditions, and wettability alteration was quantified via contact angle measurements using HPAM-SiO₂, HPAM-CNT, Sav10 VHM-SiO₂, and Sav10 VHM-CNT systems. Core floods were performed in three consecutive phases; waterflooding (baseline), standalone nanoparticle flooding, and hybrid nano-polymer …

Investigation And Prediction Of Excessive Water Production In Bottom Water-Drive Naturally Fractured Reservoirs Using Machine And Deep Learning, Sami Abderraouf Belkhir

Theses

Naturally Fractured Reservoirs (NFRs) are characterized by dual-porosity and dual-permeability systems, posing significant challenges in managing water production due to highly conductive fracture networks that facilitate rapid water migration from bottom aquifers, often bypassing oil stored in the matrix, thus resulting in early water breakthrough and water channeling phenomena. The main objective of this thesis is to develop and validate deep learning and machine learning models to predict water production, water breakthrough time (tbt), and ultimate water cut (WCult) in NFRs, thereby enabling more effective reservoir management strategies. This work also aims to evaluate the sensitivity of water behavior to …

Data-Driven Machine Learning Applications For Predictive Modeling Of Petrochemical And Ecofriendly Systems, Noora Saleh Al Mansoori

Theses

Traditional experimental approaches in industrial processes, such as Fourier Transform Infrared Spectroscopy (FTIR) spectroscopy, thermogravimetric analysis (TGA), and well-drilling operations, are often constrained by time, cost, and operational limitations. This research explores the application of data-driven Machine Learning (ML)-based predictive modeling to improve efficiency and reduce dependency on resource-intensive experimentation. The study develops ML models for three distinct processes: FTIR intensity prediction of bitumen thermal cracking products, thermal degradation of Medium-Density Fibreboard (MDF) using TGA data, and Rate of Penetration (ROP) prediction in petrochemical industry. Six algorithms: Linear Regression (LinReg), Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), Gradient …

Hunting, Feiyang Zhuang

Masters Theses

This writing is about fragility and revelation of technological systems. It considers how brokenness, delay, and opacity are not flaws but openings—opportunities to reimagine our relationship to technology as something grounded, sensory, and continuous with the natural and material world.

Colloidal Quantum Dots: A Path Toward Making Mid-Wave Infrared Sensing A Ubiquitous Technology, Mohammad Mostafa Al Mahfuz

Dissertations

Reducing the size, weight, power consumption, and cost (SWaP-C) of infrared detectors could make infrared sensing more widely accessible. In the critical mid-wavelength infrared (MWIR) spectral range of 3-5 gm, commercially available detectors are limited by the high costs associated with epitaxial growth and hybridization, as well as the need for cryogenic cooling. These factors restrict their use to defense and space applications.

Colloidal quantum dots present a promising material for overcoming these challenges, with wafer-scale monolithic integration and Auger suppression being the key material capabilities to minimize the sensor's SWaP-C. Infrared sensors based on colloidal quantum dots have been …

Childhood Neuroanatomical Markers Of Familial And Nonfamilial Attention-Deficit/Hyperactivity Disorder, Rahman Baboli

Dissertations

Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent neurodevelopmental disorder, characterized by developmentally inappropriate levels of inattention, hyperactivity, and impulsivity. Children with family history of ADHD are at an elevated risk of having ADHD as well as a higher risk of persistent ADHD into adulthood, reflecting a source of etiological heterogeneity in ADHD. This heterogeneity in terms of both biological and environmental risk factors may explain differences in neural correlates, outcomes, cognitive, behavioral as well as developmental trajectories. It is therefore critical to understand the influence of having, or not having positive family risk factors on the neuroanatomical structures of the …

Machine Learning And Optimization For Intelligent Decision-Making, Elson Cibaku

Dissertations

This dissertation presents a series of innovative machine learning and optimization model designs that address complex operational challenges across logistics and power systems. By integrating advanced neural architectures with robust optimization techniques, the work delivers scalable solutions designed to improve efficiency, reliability, and decision-making in dynamic and real-world environments. The first study introduces a two-stage approach to effective vaccine distribution. This framework tackles the capacitated vehicle routing problem by combining adaptive clustering techniques with reinforcement learning and a simulated annealing pickup policy. Through extensive computational experiments, the approach demonstrates substantial improvements in routing efficiency, reducing both computational time and logistical …

Model-Based Reinforcement Learning And Deep Learning For Power Converter Circuit Design Automation, Shaoze Fan

Dissertations

This dissertation presents a comprehensive automated framework for power converter design, leveraging reinforcement learning (RL) and graph-transformer networks (GTN) to address critical inefficiencies in traditional manual topology optimization. Motivated by the combinatorial increase of circuit design spaces and the computational cost of iterative simulations, this work develops a robust framework for generating energy-efficient topologies requiring rapid and reliable circuit design.

The framework integrates three key components: (1) an upper-confidence-bound-tree-based (UCT-based) RL model for circuit topology space exploration, (2) parallelized UCT algorithms to accelerate exploration processes, (3) a Graph-Transformer-based Network enabling fast circuit performance evaluation. Experimental validation demonstrates the whole framework …

The Interplay Of Accommodation And Oculomotor Vergence Within Young Adults With Binocularly Normal Vision And Typically-Occurring Convergence Insufficiency, Sebastian Fine

Dissertations

Concerted binocular coordination evoking oculomotor and refractive responses to visual stimuli are essential to daily function. Oculomotor dysfunctions can inhibit binocular responses to visually-near stimuli and have high comorbidities to accommodative dysfunctions. Three visual cues for inward (convergent) and outward (divergent) oculomotor movements, when presented concertedly create natural-viewing conditions: disparity- the binocular difference in light cast onto the fovea due to differing ocular perspectives, blur- the acuity of a visual target which stimulates accommodation, and proximal- the perceived distance of a visual stimuli based on size.

This study aims to quantitatively investigate oculomotor vergence and accommodation performances between individuals with …

Modulation Of Cerebellar Cells By Transcranial Ac Stimulation In Anesthetized Rats, Qi Kang

Dissertations

Noninvasive brain stimulation (NIBS) is increasingly utilized in clinical trials for the treatment of neurological disorders. Each NIBS technique offers distinct advantages. Transcranial electrical stimulation (tES) is easy to apply and requires only simple equipment, while transcranial magnetic stimulation (TMS) can penetrate deeper than tES into the brain and it is more focal. Transcranial focused ultrasound stimulation (FUS) is superior to both in terms of penetration and focal stimulation. This study focuses on the modulation of the cerebellum, traditionally believed to be associated with motor coordination but increasingly recognized for its role in cognition and emotion as well. While tES …

Adversarial Robustness In Advanced Machine Learning Models Integrating Graph Neural Networks And Large Language Models, Mahmoud Nazzal

Dissertations

Artificial intelligence (AI) has achieved remarkable performances across various domains. In most real-world applications, data often takes relational forms, such as graphs and networks, or sequential forms, such as text and time series. As AI evolves, specialized models have emerged to handle these structures; Graph Neural Networks (GNNs) for relational mining and Large Language Models (LLMs) for sequential understanding. Despite their success, these models face challenges in security, robustness, and interpretability. GNNs excel in relational reasoning but are vulnerable to adversarial manipulation and lack interpretability, while LLMs are strong in linguistic reasoning and generalization yet struggle with relational data and …

An Inquiry Into The Physics Of Mixing And Floc Filtration, Andrew P. Pennock

Dissertations

Flocculation and clarification are two essential processes to deliver safe water at a reasonable cost to consumers. There are two major thrusts to the research presented in this dissertation. The first is to better characterize the physics and mixing parameters used for the design of hydraulic flocculators in the context of drinking water treatment plants. The second major thrust is to investigate floc filtration as a mechanism for the removal of primary particles during floc blanket clarification.

The intensity of mixing in environmental and chemical engineering applications is often characterized by the Camp and Stein velocity gradient. This parameter has …

Next-Generation Extended Reality Systems With Real-Time Edge Artificial Intelligence And Mobile Computing, Pedro H. Regalado

Dissertations

Mixed reality (MR) and augmented reality (AR) systems are reshaping digital experiences by seamlessly integrating physical and virtual environments. This dissertation presents a comprehensive framework for next-generation immersive systems, combining advances in real-time data processing, multi-user synchronization, and secure communication. The core contributions are structured around three interconnected systems: MediVerse, TeleAvatar, and MultiAvatarLink, each addressing critical challenges in mobile MR.

MediVerse is a secure and scalable framework for real-time health and performance monitoring, integrating intelligent IoT sensors, wearable technologies, and MR interfaces. It supports multi-camera fusion, adaptive compression, and real-time three-dimensional (3D) point cloud generation, enhancing data accuracy and responsiveness …

Linear Mixed Model For The Surface Roughness Prediction In Hard Turning Operation, Prithbey Raj Dey, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

Surface machining using hard turning is an intricate operation due to the influence of multiple machining parameters, their non-linear interactions, and the inherent variability introduced by different experimental trials. This study proposes a Linear Mixed Model (LMM) for predicting surface roughness, effectively addressing the challenges in traditional linear models, posed by the influencing factors, non-linearity, and interactions. The LMM incorporates variability from both fixed effects, such as cutting parameters (feed rate, depth of cut, and cutting speed), and random effects arising from tool wear across experimental runs. As a result, it provides a more comprehensive understanding of how these factors …

The Prospect Of Geospatial Analysis In The Prediction Of Surface Quality In Machining, Prithbey Raj Dey, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

This research underscores the prospect of geospatial analysis in machining operations to enhance precise prediction and robustness, offering a comprehensive framework of spatial modeling for advanced manufacturing processes. Geospatial analysis not only provides accurate predictions but also estimates the uncertainty associated with these predictions, offering valuable insights for process optimization. The surface quality in the machining processes is expressed by the estimation of the average surface roughness. While machining parameters are extensively analyzed for their influence on surface quality, the roughness profile parameters are inadequately explored. This work integrates these underexplored parameters into geospatial predictive models and evaluates their impact …

A System Of Systems (Sos) Meta-Architecture Approach To Design Digital Platform-Based Domestic Worker Distribution System, Prithbey Raj Dey, Cihan H. Dagli, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

In this research, a System of Systems (SoS) meta-architecture is conceptualized to design a digital platform-based system framework for the distribution of domestic workers to boost the crowd-sourced economy. While an Object Process Methodology (OPM) is used to articulate the relationships between the objects and functions, a Design Structure Matrix (DSM) has been applied to address the interactions between individual components to categorize them into subsystems to create the SoS architecture. This SoS architecture incorporates several Key Performance Attributes (KPAs) and Key Performance Parameters (KPPs) to systematically evaluate the meta-architectures. The Analytical Hierarchical Process (AHP), Pugh’s Evaluation Matrix, and Technique …

Blockchain-Based Ai-Assisted Cyber-Physical Systems For Robust And Reliable Machining Processes, Prithbey Raj Dey, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

This study demonstrates the prospects of Blockchain-based Cyber-Physical Systems (CPS) to establish a scalable framework for designing a secured, automated, and traceable modeling in machining processes. Machining operations like turning, being inherently complex, rely on different types of explanatory parameters such as feed rate, depth of cut, cutting speed, tools, and environmental factors. All of these variables significantly influence key response variables like surface quality, tool wear, cutting forces, and energy consumption. The proposed Blockchain-based framework, designed using the Object-Process Methodology (OPM) systems modeling language, enables the reliable exchange of comparative data streams within a unified data analytics platform. By …

Nebraska Balanced Mix Design - Phase Ii, Farzad Yazdipanah, Mahdieh Khedmati, Jamilla Teixeira, Hamzeh Haghshenas

Nebraska Department of Transportation: Research Reports

This study aimed to propose a performance-based framework to evaluate highly recycled asphalt mixtures containing polymer-modified binders for potential use in a balanced mix design (BMD) specification in the state of Nebraska. For that, loose and compacted mixtures were directly collected from plant and field projects within a benchmarking study, subjected to an extensive experimental program. The laboratory investigation employed different monotonic tests recommended in BMD Phase 1, as well as the dynamic modulus test. Three long-term aging protocols were investigated in terms of their impact on the mechanical, rheological, and chemical characteristics of asphalt mixtures and binders. Moreover, field …

Evaluation Of The Effects Of Various Types Of Inert And Active Fillers On Asphalt Mixture Performance, Mohammad Hadizadeh Pirbasti

LSU Master's Theses

Abstract:

The performance of asphalt mixtures is significantly influenced by the type and characteristics of fillers used as a replacement for filler part of the aggregates’ batching. According to this research investigation the performance along with durability characteristics of asphalt mixtures are evaluated through different inert and active fillers. The fillers used include Fly Ash, Cement, steel slag powder, and additional filler. These fillers incorporate into two types of asphalt mix design of Stone Matrix Asphalt (SMA) and a surface mix. Fillers are categorized according to their reactive properties alongside their physical attributes leading to active fillers strengthening bond formation …

Burst Pressure Performance Of Multilayer Co-Extruded Polystyrene/Poly (Methyl Methacrylate) Pipes, Negar Shaghaghi, Erik Steinmetz, João Maia

Faculty Scholarship

This study investigates advancements in multilayer co-extrusion of annular structures, focusing on the mechanical properties of a 129-layer polystyrene (PS)/poly(methyl methacrylate) (PMMA) pipe with 50% PS as a skin layer for proof-of-concept validation. We explore the impact of angular rotation on burst pressure, layer structure, and failure mechanisms, emphasizing the potential of this technique for enhanced mechanical performance through biaxial orientation and the elimination of weld lines. Utilizing high aspect ratio (HAR) multipliers and angular rotation, our findings demonstrate improved layer structure and burst pressure performance at higher velocity ratios, which is the ratio of the linear component of angular …

Interaction Of Liquid Phase Diisopropyl Methyl Phosphonate (Dimp) With Material Surrogates For Components Of Soil And Combustion Products Of Metal Fuels, Khushi Sunil Patel

Theses

Combustion products of three different Al-based materials, Al-CaCO₃, Al-SiO₂, and Al-Fe₂O₃ , have been produced to understand their interaction with liquid diisopropyl methyl phosphonate (DIMP), a surrogate for chemical weapon agents. The purpose of this is to see which materials were more effective at DIMP adsorption and decomposition at different temperatures. Prepared materials were characterized using electron microscopy, x-ray powder diffraction, and nitrogen adsorption. Prepared powders were submerged in DIMP and heated in a thermal analyzer, tracking the mass changes as a function of temperature. Surfaces of the recovered materials were studied using …