Digital Commons Network^™

Data-Driven Koopman Theory For Transient Stability And Safety Analysis Of Power Systems With Renewable Penetration, Bhagyashree Umathe

All Dissertations

This dissertation presents a novel approach to analyzing and controlling nonlinear systems using the Koopman operator framework and data-driven methods. Nonlinear power systems, characterized by complex behaviors and sensitivity to initial conditions, pose significant challenges for stability and safety assessment, especially during transient events.

The first part of this work focuses on reachability analysis using the spectral properties of the Koopman operator. By leveraging eigenfunctions extracted from sampled trajectory data, the approach computes forward and backward reachable sets efficiently, even in high-dimensional nonlinear systems, without requiring dense state-space sampling. This method is validated through numerical examples, demonstrating its ability to …

Development Of A High-Performance, Cost-Effective Architecture For Real-Time Fourier Transform Analysis On An Efinix Trion Fpga, Luke Cashwell

Honors Theses

This project presents the development of a high-performance, cost-effective, and powerefficient pipelined architecture designed to execute 10,000 Fast Fourier Transforms (FFTs) per second on an Efinix Trion T120 FPGA. Each FFT processes 4096 signed 13-bit elements, facilitating real-time data analysis for a Time-Domain Impedance Probe (TDIP) operating at a maximum data rate of 490 Mbit/s. The algorithm utilizes the built-in multipliers and dual-port memory cells of the FPGA to optimize data storage, transfer, and processing. It achieves this high performance while only using approximately 4% of the Look-Up Tables (LUTs), 7% of the integrated RAM cells, and 15% of the …

Data-Driven Stochastic Programming For Disaster Housing Logistics Planning, Sheng-Yin Chen

All Dissertations

This dissertation develops an integrated modeling and solution framework for direct temporary disaster housing logistics under demand uncertainty. The proposed framework addresses the problem from short-term, long-term, and computational perspectives. First, a two-stage chance-constrained stochastic programming (TSCC) model is developed for short-term housing logistic planning, with demand scenarios generated via a data-driven spatial regression model that captures the relationship between housing demand, hazard exposure, and socioeconomic factors. A case study based on Hurricane Ian demonstrates that the TSCC model outperforms deterministic and traditional scenario-based models in both solution quality and robustness. Second, to address long-term housing logistics planning, a multi-horizon …

Crevice Corrosion Mechanisms Of Cocrmo Alloys In Orthopedic Implants: Retrieval Analysis, Nano-Tribocorrosion And Cellular Responses, Hwaran Lee

All Dissertations

Mechanically assisted corrosion and non-mechanically (chemically) driven corrosion in modular junctions of orthopedic implants using cobalt-chromium-molybdenum (CoCrMo) alloys remain clinical concerns and may contribute to implant failure. The underlying corrosion mechanisms are not yet fully understood, leaving a critical research gap. We hypothesized that corrosion in modular junctions may be driven by aggressive local environments, including fretting, metal ion release (cobalt ion, Co²⁺), low pH and reactive oxygen species (ROS). This dissertation aims to (1) analyze corrosion modes and potential causes in modular junctions; (2) identify chemically driven corrosion modes on CoCrMo alloys using simulated inflammatory modular taper …

Self-Poled P(Vdf-Trfe) Based Composites For Energy Harvesting And Wearable Sensor Applications, Lavanya Muthusamy

All Dissertations

The growing demand for flexible, low-power, and self-powered wearable electronic systems has accelerated research interest in polymer-based sensors and energy harvesting technologies. Among piezoelectric polymer materials, Poly(vinylidene fluoride-trifluoro ethylene) [P(VDF-TrFE)], over the years, has garnered significant attention due to its unique piezoelectric properties, high dielectric constant, mechanical flexibility, thermal stability, chemical resistance, biocompatibility and compatibility with scalable fabrication processes. Despite its advantages, conventional P(VDF-TrFE)-based devices often require external poling and face limitations in integration with low-cost, flexible substrates. To overcome these limitations, this research study explores the nanofiller approach, along with facile fabrication processes, and structural design strategies aimed at …

Simulation- And Machine Learning-Based Methods For Inland Waterway Operation And Maintenance Decision-Making, Maryam Aghamohammadghasem

Graduate Theses and Dissertations

The U.S. inland waterway transportation system (IWTS) is an essential part of the country's multimodal freight transportation network. In addition to seasonal droughts and floods, the operations of the IWTS may be disrupted by random malfunctions and scheduled maintenance of its critical components. Among these critical components, locks play a key role in the operation of navigable inland waterways, and lock-induced disruptions to the supply chains of related industries, such as agriculture and manufacturing, often result in significant economic losses. To assess the performance of the U.S. IWTS, we develop a PyNetLogo simulation tool to capture the movements and delays …

Coupling Effect Of Abrasion And Erosion On Ultrahigh-Performance Seawater-Sea Sand Concrete, Dawei Ding, Wei Zhang, Lanqin Wang, Hongyan Ma, Biqin Dong, Song Han, Hongjian Xu, Dongshuai Hou

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Preparing ultrahigh-performance seawater-sea sand concrete (UHPSSC) to mitigate the scarcity of freshwater and river sand resources has generated considerable recent research interest. However, the deterioration mechanisms of UHPSSC under the effect of abrasion and erosion remain unstudied. In this paper, the underwater steel ball method was conducted to evaluate the impact of seawater, sea sand, steel fiber, and seawater abrasion on the abrasion resistance of UHPSSC. Then the stress erosion models of calcium-silicate-hydrate (C-S-H) were constructed to investigate the degradation mechanisms of UHPSSC under the effect of external stress and seawater erosion. The results show that the application of seawater …

Stabilization Of Cr³⁺ Using Iron Rich Slag-Derived Phosphate Cement: An Integrated Solution For Heavy Metals And Hazardous Solid Wastes, Ting Huang, Hongyan Ma, Zhongqiu Luo, Xintao Zhou, Zhengqing He, Peiwen Lv, Xiunan Cai, Pingyan Wang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

A novel iron-based phosphate cement (IPC), derived from iron-rich smelting slag (ISS), was developed as a sustainable and efficient binder for the stabilization/solidification of trivalent chromium (Cr³⁺). The mechanical properties, hydration behavior, microstructure, leaching toxicity, chromium chemical forms, and environmental safety of chromium-stabilized iron phosphate cement (CIPC) were thoroughly evaluated. The results showed that, with a mass ratio of ISS to ammonium dihydrogen phosphate (ADP) of 2.0, and even with the addition of 20 % chromium nitrate nonahydrate (CN), the compressive strength of CIPC reached 4.2 MPa after curing for 28 d. Furthermore, chromium leaching was well below …

Trauma Network Design Considering Patient Safety And Cost., Lin Lin

Electronic Theses and Dissertations

Trauma, as the leading cause of mortality and morbidity for those under the age of 45 in the US, incurs trillions in annual economic costs. The time-sensitive nature of trauma treatment necessitates an effective, coordinated regional trauma system to optimize patient safety. However, the financial burden associated with trauma care, especially due to low-insured population, presents a significant challenge to the financial health of trauma centers (TCs). To address critical challenges in this domain and provide much-needed insights to trauma decision-makers regarding their trauma system cost, network design, and subsidy policy, this dissertation proposes 3 contributions. First, we introduce an …

Anisotropic Object-Based Shifts Of Attention Arise From Unequal Influences Of Visual Field Meridians On Neural Attention Gradients, David H. Hughes, Adam J. Barnas, Adam S. Greenberg

Biomedical Engineering Faculty Research and Publications

Object-based attention prioritizes the processing of information appearing within a selected object. We previously showed an object-based shift direction anisotropy (SDA) whereby horizontal shifts are more efficient than vertical shifts (Barnas AJ, Greenberg AS. Atten Percept Psychophys 78: 1985–1997, 2016; Barnas AJ, Greenberg AS. Vis Cogn 27: 768–791, 2019), an effect modulated by the visual field meridians (Barnas AJ, Greenberg AS. Q J Exp Psychol (Hove) 77: 2516–2532, 2024). Our present aim was to understand how the functional brain mechanisms of attention give rise to the SDA. We hypothesized that the SDA arises from attentional resources being partitioned differently by …

Exploring Methods For Quantifying Uncertainty In Neural Network-Based Turbulence Closures, Cody Grogan

All Graduate Theses and Dissertations, Fall 2023 to Present

Machine Learning (ML) is a very promising field for data-driven modeling of different phenomena. In the field of Computational Fluid Dynamics (CFD), ML is an enticing alternative to traditional methods to improve the accuracy and computational efficiency of simulations. However, many ML models, like Neural Networks, don’t quantify their uncertainty or indicate their confidence in a prediction to those who wish to use them. This is especially important because the use of inaccurate ML predictions in a CFD simulation can greatly impact the validity of a simulation. However, with uncertainty quantification, an ML model can indicate to a modeler the …

Evaluating The Impact Of Maximum Aero-Thermal Heating On A High-Speed Fixed-Wing Atmospheric Aircraft Optimum Trajectory, Benjamin M. Ford

All Graduate Theses and Dissertations, Fall 2023 to Present

This study explores how extreme heating affects the flight paths of hypersonic aircraft—vehicles that travel at speeds many times faster than sound. Analyzing how to fly a high-speed aircraft without overheating it can prevent structural failure while operating at maximum possible performance. The results shown in this section indicate that it is possible to operate at very high speeds in an aircraft while keeping peak vehicle temperature below our limits while saving fuel.

A Provable Semi-Infinite Programming Approach For Solving Dynamic Nash Games, Tyler C. Gardner

All Graduate Theses and Dissertations, Fall 2023 to Present

Many engineering problems must account for the non-cooperative decisions and actions of multiple players. These problems can be modeled within a game-theoretic framework. The approach herein is to model problems as Nash games, convert them to semi-infinite programs, and leverage provable semi-infinite algorithms to solve the original problem. A particular algorithm that leverages off-the-shelf solvers is used to solve four low-dimensional benchmark problems successfully. Two types of linear quadratic dynamic games are then investigated: ones where each player’s problem is convex and ones where at least one player’s problem is nonconvex. Within each type, variations based on information structure, communication …

Evaluating Cyanotoxins In Surface Water And Aerosols Near Utah Lake, Dylan R. Mcpeake

All Graduate Theses and Dissertations, Fall 2023 to Present

Utah Lake is a freshwater lake in Utah County near Provo, Utah. It is the third- largest lake in Utah and is important for recreation and local businesses. However, from June to October, the lake often has cyanobacteria harmful algal blooms (cHABs), which contain a toxin called cyanotoxin. These toxins can be dangerous to people who come into contact with the water. Government agencies regularly check for cHABs and warn people when the water is unsafe for activities like swimming. Collecting water samples to test for cHABs can be risky because it can possibly result in direct contact with the …

Analysis Of Thrust Performance And Noise Generation Of Uam Composite Propellers Fabricated Using Composite-Based Additive Manufacturing, Samiul Alam

All Graduate Theses and Dissertations, Fall 2023 to Present

Urban air mobility (UAM) is an emerging transportation concept that uses lightweight, efficient aircraft for transporting goods and passengers and performing other logistical activities. One of the biggest challenges in developing UAM from a structural perspective is manufacturing strong and reliable propellers that are lightweight and durable. Traditional manufacturing methods for composite propellers are expensive, time-consuming, and difficult to scale. This study explores a new approach using Composite-Based Additive Manufacturing (CBAM) to produce high-performance propellers more efficiently. CBAM allows for the fabrication of strong, lightweight composite propellers using short manufacturing lead times. However, one challenge with this technique is that …

An Ant-Colony Approach To Scheduling Charging Sessions Of Electric Vehicle Fleets With Heterogeneous Scheduling Constraints, Derek D. Redmond

All Graduate Theses and Dissertations, Fall 2023 to Present

Electric vehicles and electric-vehicle fleets are gaining widespread usage. A major challenge of managing an electric-vehicle fleet is scheduling when the vehicles can charge and when the vehicles can complete their tasks. Finding smart ways to schedule electric-vehicle charging reduces both the cost of charging vehicles and increases the health of the grid and the environment. This best-of-both-worlds outcome is because of the pricing structure that electric utility companies use. When minimizing the cost of charging the vehicles, it is important to consider that vehicle fleets have constraints on when they can charge. Vehicles are usually limited by the tasks …

Optimization And Utilization Of Microbial Electrolysis Cells In Waste To Product Applications, Hayden Harrison

All Graduate Theses and Dissertations, Fall 2023 to Present

As the world searches for cleaner and more sustainable energy solutions, turning waste into fuel is an increasingly attractive strategy. This research focuses on microbial electrolysis cells, a new technology that uses bacteria and a small amount of electricity to convert organic waste—like food scraps or wastewater—into useful gases such as hydrogen and methane. These gases can be used as energy sources to reduce dependency on more traditional fuels.

This thesis tackles two key challenges that limit the real-world use of microbial electrolysis systems. First, it introduces a simpler and more effective method to stop hydrogen losses in single-chamber cells. …

Assessing Public Satisfaction And Transportation Choices During Winter Road Maintenance: A Case Study Of Utah, Shailendra Khanal

All Graduate Theses and Dissertations, Fall 2023 to Present

Winter road maintenance is essential to keeping people safe and mobile during snowstorms. In Utah, where winter weather is a regular part of life, the Utah Department of Transportation (UDOT) plays a vital role in keeping roads clear and functional. While much attention is given to how roads are plowed and managed, there has been less focus on how the public experiences these efforts—and how the decisions to travel during storms are shaped by personal circumstances and perceptions.

This research sets out to understand two things: how satisfied people are with winter road maintenance, and what influences their transportation decisions …

Enhanced Point Cloud Generation From A Novel 360° Underwater Lidar, Olagoke E. Daramola

Dissertations

This dissertation presents novel algorithms to improve the mapping capabilities of a 360-degree underwater Pulsed Laser Line Scanner LiDAR (PLLS-360°). Due to its 360° field-of-view (FOV), the PLLS-360° is a compact full-waveform omnidirectional imager suitable for seafloor mapping, underwater asset inspection, object detection, ice-sheet mapping, and construction progress monitoring. The proposed methodology includes an improved waveform fitting technique for saturated waveform recovery, detection array response correction, radiometric corrections, and fusion of LiDAR and sonar bathymetric datasets. The first part of this dissertation assesses the LiDAR’s performance and describes how the data for this unique 360° FOV architecture is processed. The …

Assessing The Robustness Of Test Selection Methods For Deep Neural Networks, Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy, Wei Ma, Mike Papadakis, Lei Ma, Yves Le Traon

Research Collection School Of Computing and Information Systems

Regularly testing deep learning-powered systems on newly collected data is critical to ensure their reliability, robustness, and efficacy in real-world applications. This process is demanding due to the significant time and human effort required for labeling new data. While test selection methods alleviate manual labor by labeling and evaluating only a subset of data while meeting testing criteria, we observe that such methods with reported promising results are simply evaluated, e.g., testing on original test data. The question arises: are they always reliable? In this article, we explore when and to what extent test selection methods fail. First, we identify …

Localized Multivariate Statistical Assessment Of United States Construction Labor Shortages, Ahmed Shiha, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Craft labor shortage is a persistent challenge facing the construction industry across various markets. The historically low geographic mobility of construction labor exacerbates and localizes labor shortages. Several research efforts relied on subjective evaluations to quantify the existence of labor shortages on a national level. As such, there is a lack of empirical quantification of labor shortages at different geospatial levels. This paper fills this knowledge gap. To this end, the authors adopted a methodology that encompassed: (1) conducting a literature review to identify and collect national-level and subnational indicators that explain the changes in labor supply and demand; (2) …

Visceral, Neural, And Immunotoxicity Of Per- And Polyfluoroalkyl Substances: A Mini Review, Pietro Martano, Samira Mahdi, Tong Zhou, Yasmin Barazandegan, Rebecca Iha, Hannah Do, Joel Burken, Paul Ki-Souk Nam, Qingbo Yang, Ruipu Mu

Chemistry Faculty Research & Creative Works

Per- and polyfluoroalkyl substances (PFASs) have gained significant attention due to their widespread distribution in the environment and potential adverse health effects. While ingestion, especially through contaminated drinking water, is considered the primary route of human exposure, recent research suggests that other pathways, such as inhalation and dermal absorption, also play a significant role. This review provides a concise overview of the toxicological impacts of both legacy and emerging PFASs, such as GenX and perfluoro butane sulfonic acid (PFBS), with a particular focus on their effects on the liver, kidneys, and immune and nervous systems, based on findings from recent …

Integration Of Highly Mismatched Iii-Sb Virtual Substrates On Silicon Via Interfacial Misfit Arrays For Short-, Mid-, And Long-Wave Infrared Applications, Trent Garrett

Boise State University Theses and Dissertations

Lattice constants of the III-V semiconductors range from 5.45 Å (GaP) to 6.48 Å (InSb). III-V semiconductors are grown on commercially available substrates made from binary III-V materials (e.g., GaAs, InP, and GaSb), or group IV materials (e.g., Si or Ge). These substrates offer very high quality, but only offer access to a small number of specific lattice constants. Given this constraint, it is desirable to develop growth methods that would allow the grower to modulate from the substrate lattice constant into the lattice constant of the material structure under investigation.

Device structures made from III-V semiconductors lattice-mismatched to these …

Failure Study Of Silicon Gated Field Emitter Arrays: Experiment And Simulation, Rushmita Bhattacharjee

Boise State University Theses and Dissertations

Silicon-based Gated Field Emitter Arrays (Si-GFEAs) are among the most well-developed field emitters. They are being actively explored for vacuum transistors and microwave vacuum electron devices due to their high-frequency performance, radiation resistance, and thermal stability up to 400 °C. However, their long-term reliability is limited by sudden failure events, resulting in cathodic vacuum arcs. This dissertation presents a combined experimental and simulation-based investigation into arc initiation mechanisms in Si-GFEAs. Different device arrays were tested under normal operation in vacuum at 10^-7 Torr with gate voltages of 50-70 V and emission currents from tens of nA to tens of µA. …

Engineering Properties And Stress-Strain Behavior Of Bcsa Concrete: Flexural Design Parameters, Strain Measurement Methods, And Models, Gabriel R. Johnson

Graduate Theses and Dissertations

Belitic calcium sulfoaluminate (BCSA) cement concrete has gained popularity due to advantages over portland cement (PC), including, its fast-setting, high early strength gain, high durability, and reduced global warming potential. Though primarily used for pavement repair, it has good potential for structural applications. Building codes like ACI 318:19 permit alternative cement materials like BCSA cement if they can be shown to have adequate and predictable structural, durability, and fire performance comparable to PC concrete. This study evaluates the structural and mechanical behavior of BCSA cement concrete, measuring standard engineering properties and comparing results to PC concrete and code prediction equations. …

Low-Power Hardware-Based Real-Time Cervical Spine Localization Via Image Processing, Patricia Angela R. Abu, Chao-Shin Liu, Sung-Hsin Tsai, Po Lin Huang, Hong-Kai Wang, Shih Wei Chung, Chiung-An Chen, Shih-Lun Chen, Sze-Teng Liong, Tsung-Yi Chen

Department of Information Systems & Computer Science Faculty Publications

With the growing prevalence of cervical spine degeneration in the aging population, there is an urgent need for accurate and real-time cervical image analysis to assist in preliminary evaluations during neurosurgical outpatient visits. This study suggests a hard-ware-based real-time cervical spine localization system that uses image preprocessing algorithms to address this need. The system can quickly finish image enhancement and greatly speed up the localization process by turning preprocessing steps like median filtering and binarization into hardware modules. With a power consumption as low as 4.859 mW, the proposed hardware-based median filter demonstrates over 60% reduction in power and 35% …

Bilateral Leading Edges With Tubercle Modifications: An Experimental Study, Roberto Sanchez

Theses and Dissertations

The increasing demand for better performance and maneuverability from airfoils to sustain superior performance over a wide range of platforms, including vehicles, propellers, and wing designs, continues to grow. Researchers have drawn inspiration from nature, looking at birds of prey, dragonflies, and humpback whales for aerodynamic improvements. Among these, tubercle airfoils, inspired by the humpback whale’s flipper, have gained increasing interest. This experimental study presents the results of bilateral tubercle leading-edge airfoils based on a modified NACA 0018 design with a chord length of 1.82 inches, a span width of 7.5 inches, and an amplitude of 6.3c%. Five configurations were …

Development Of A Wearable Biosensor For Cortisol Detection In Human Sweat Utilizing Pani/Peo Polymer Blend And Nitrogen-Doped Graphene Quantum Dots, Cesar Sanchez

Theses and Dissertations

Since the development of the first biosensor in 1962, the evolution of commercially available wearable biosensors has been driven by an increasing consumer interest in real-time health tracking. However, challenges related to sensor sensitivity and cost have hindered progress. Deploying a novel approach, the biosensor integrates a blend of Polyaniline (PANi) and Polyethylene Oxide (PEO) along with Nitrogen-doped Graphene Quantum Dots (N-GQDs) to enhance sensitivity and electroactivity, crucial for cortisol detection. To optimize performance, three distinct synthesis methods for N-GQDs; hydrothermal, microwave, and hot plate synthesis were compared employing a bottom-up approach utilizing citric acid (CA) as the primary reactant …

Primary And Parametric Resonances Of Angled Mems And Nems Cantilever Resonators, Benjamin Matthew Huerta

Theses and Dissertations

This work investigates the resonances of electrostatically actuated micro- and nano-electromechanical systems (MEMS/NEMS) uniform cantilever resonators positioned at an angle relative to a ground plate. The resonances considered in this work include primary and parametric resonance. For each resonance, the amplitude-frequency and amplitude-voltage responses are presented. The model is constructed using Euler-Bernoulli beam theory. Results are obtained by construction of a Reduced Order Model considering up to the first five modes of vibration. The Method of Multiple Scales is used when considering only the first mode shape, and the software AUTO 07p is used for higher terms. Two models are …

Low-Dimensional Learning For Remaining Useful Life Prediction Of Batteries Operating Under Various Environments, Rodrigo Benavides

Theses and Dissertations

In reliability, we typically define the standard operating conditions under which a component operates. However, the differences in battery operating conditions cause variability in the degradation patterns of identically manufactured batteries, rendering remaining useful life prediction a major challenge. To aid this task, several sensors are utilized to monitor battery state-of-health. However, traditional prognostics algorithms do not scale well to the volume of data generated. Furthermore, several authors do not explicitly consider operating environments in their prediction models. Therefore, we present a high-dimensional data analytics framework that integrates operating environment information for battery prognostics. This framework combines Multilinear Principal Component …