Engineering Commons^™

Robustness Investigation, Detection, And Defense Of Deep Learning Models Against False Data Injection, Amirhossein Nazeri

All Dissertations

This dissertation addresses the critical challenge of adversarial robustness in deep learning systems, focusing on two fundamental domains: time-series prediction and object detection. As these AI systems become increasingly deployed in safety-critical applications from power grid management to autonomous vehicles their vulnerability to adversarial attacks poses significant risks to infrastructure and human safety.

The first contribution introduces a novel stealthy black-box False Data Injection (FDI) attack specifically designed for quasi-periodic time-series data. Unlike existing attacks that produce easily detectable anomalies, our method generates adversarial perturbations that preserve the underlying periodicity and statistical properties of the data, effectively bypassing traditional anomaly …

Robust Adaptive Rigid Body State And Mass Property Estimation Via Unscented Kalman Filter On Tse(3) With Process Noise Estimation, Herman Gunter

Doctoral Dissertations and Master's Theses

Mass property estimation, including mass, center of mass, and moment of inertia, is a crucial yet challenging problem in spacecraft autonomy and astrodynamics. Knowledge of mass properties of a spacecraft is essential for future astronautical missions, as changes in the mass properties of a spacecraft due to a shift in cargo distribution often require a careful and costly recalculation to ensure applied control inputs produce the desired results. As spacecraft missions grow in both duration and number, meeting the need for precise and accurate measurements becomes increasingly complex. Stochastic effects, such as angle and velocity random walks, along with persistent …

Real-Time Fiducial Marker Based Localization For Autonomous Unmanned Aerial Vehicle Navigation, Sourav Raxit

LSU New Orleans Theses and Dissertations

By harnessing fiducial markers as visual landmarks in the environment, Unmanned Aerial Vehicles (UAVs) can rapidly build precise maps and navigate spaces safely and efficiently, unlocking their potential for fluent collaboration and coexistence with humans. Existing fiducial marker methods rely on handcrafted feature extraction, which sacrifices accuracy. On the other hand, some deep learning pipelines for marker detection fail to meet real-time runtime constraints crucial for navigation applications. In this work, I propose YoloTag- a real-time fiducial marker-based localization system. YoloTag uses a lightweight YOLO v8 object detector to accurately detect fiducial markers in images while meeting the runtime constraints …

Discovery Of High-Performance Cathode Materials For Protonic Ceramic Fuel Cells, Liang Han

All Dissertations

Environmental pollution and rapid energy consumption have become common problems in global development and will continue to grow with the world population. PCFCs use proton-conducting ceramics as electrolytes, with low activation energy and high ionic conductivity at intermediate temperatures, enabling them to operate at intermediate-temperature conditions, which can effectively solve the problems of poor stability and high cost of exotic materials of traditional solid oxide fuel cells. However, as the operating temperature decreases, the electrocatalytic activity of the cathode decreases significantly, seriously affecting PCFC’s performance. Therefore, developing high-performance cathode material suitable for working under intermediate-temperature conditions has become the key …

Secure Control And Trust Evaluation Framework For Autonomous Transportation Systems, Grace Muriithi

All Dissertations

This dissertation advances the cybersecurity of hybrid tracked vehicles (HTVs) and ship power systems (SPSs) by developing innovative cyber-attack models and corresponding defence frameworks. First, we formulate stealthy false-data-injection attacks (FDIAs) on HTV energy-management systems as a partially observable Markov decision process (POMDP) solved via deep reinforcement learning. A novel sniffing-based reward function guides the attacker to covertly degrade battery capacity and energy efficiency, which we evaluate using custom stealth–impact metrics and a sliding-window anomaly detector (Isolation Forest with Dynamic Time Warping). Additionally, we model sophisticated control-layer attacks in HTVs, including reinforcement-learning-optimised replay attacks and denial-of-service (DoS) attacks targeting generator-speed …

Understanding The Elements Of Sterile Processing Workflow: Or, Sterilization And Personnel, Sayed Rezwanul Islam

All Dissertations

The Sterile Processing Department (SPD), also known as the Central Sterile Services Department (CSSD), is an essential part of hospitals and healthcare facilities and is responsible for ensuring the cleanliness, sterility, and proper functioning of medical instruments. Sterile processing departments (SPDs) are key drivers of productivity, effectiveness, safety, and infection control in hospitals. A well-designed SPD workflow can enhance patient safety, reduce operating room (OR) delays, and improve productivity. To understand the flow of sterile processing and interactions between the OR and SPD, process maps and task analyses were developed through direct observations of the basic SPD functions: decontamination, assembly, …

Pseudo-Soft-Switching Switched-Capacitor Drive Circuits For Small-Scale Dielectric Actuators, Yanqiao Li

Dartmouth College Ph.D Dissertations

Applications including micro-robotics and haptics have motivated extensive exploration of dielectric actuators due to their high bandwidth and high efficiency at cm and mm scales. To maximize their benefits, dielectric actuators, including piezoelectric and electrostatic actuators, typically require high driving voltages, ranging from 100V to several kV. Generating such high driving voltages presents a challenge for drive circuits, particularly when powered by a small battery. Dielectric actuators are predominantly capacitive in most circumstances, necessitating the drive circuits to deliver and recover reactive energy for efficient operation. In some applications, such as micro-robotics, the drive circuits may need to have a …

Population Analysis Of Cyanobacteria In Rotating Algal Biofilm Reactors, Eric H. Matthews

All Graduate Theses and Dissertations, Fall 2023 to Present

Algal biofilms have numerous applications in wastewater treatment and bioproduct production. The Sustainable Waste-to-Bioproducts Engineering Center at Utah State University is working to develop rotating algal biofilm reactors (RABRs) to remove excess nitrogen and phosphorus from wastewater effluent while producing biomass for downstream production.

Genetic analysis of algal biofilms on various RABRs was performed to gain improved understanding of the biofilm populations. This analysis focuses on a pilot-scale RABR and how it compares to several other RABRs. Additionally, old methods of genetic analysis filtered out important cyanobacterial populations. A new method was developed to identify the cyanobacteria within the biofilms. …

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 …

A Computational Study On Impact Performance Of Concrete Barriers For Protecting Transportation Assets, Ashesh Pokhrel

All Graduate Theses and Dissertations, Fall 2023 to Present

Highway safety is a major concern as roads accommodate increasing numbers of vehicles, including large trucks and tractor-trailers. Concrete barriers are commonly used along highways and bridges to prevent accidents by redirecting vehicles and protecting important structures like bridge piers. However, their effectiveness depends on how well they withstand vehicle impacts, how they perform after being damaged in previous crashes, and how they protect bridge piers when space is limited. This research examines these issues using advanced computer simulations to better understand barrier performance and improve roadway safety.

The first part of this study reviews how researchers and engineers use …

Precision Agriculture Applications In Tart Cherries: Yield Mapping Technologies And Remote Sensing For Water Stress Estimation, Anderson Luiz Dos Santos Safre

All Graduate Theses and Dissertations, Fall 2023 to Present

Tart cherry is an important specialty crop in the United States, particularly in Utah where the area dedicated to tart cherry cultivation is larger than any other fruit grown in the state. However, growers face increasing challenges due to rising land prices, limited water availability, and extreme weather events. These factors make it essential to adopt new technologies that improve efficiency and sustainability. Precision agriculture, which uses data-driven tools to manage crops more effectively, can help address these challenges. However, most tart cherry orchards still rely on traditional practices due to a lack of specialized technologies for this crop. This …

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 …

Operationalizing Camera-Based Hydrologic Monitoring With Ai And Edge Computing: Towards Real-Time Water Level And Discharge Measurements, Razin Bin Issa

All Graduate Theses and Dissertations, Fall 2023 to Present

Monitoring river water levels and flows is critical for managing water supplies, protecting against floods, supporting ecosystems, and informing infrastructure planning. However, traditional methods rely on sensors installed directly in rivers, which can be expensive, difficult to maintain, and vulnerable to damage—particularly in remote or hazardous locations. In many regions, limited budgets and access challenges result in large gaps in river monitoring networks.

This research explores an innovative alternative: using fixed cameras and artificial intelligence (AI) to monitor rivers from a distance. The approach allows for non-contact observation of water levels and flows by analyzing images captured by cameras installed …

Enhancing Emotional Accuracy And Behavioral Novelty In Robot Behaviors: A Generative-Discriminative Approach, Rista Baral

Boise State University Theses and Dissertations

Recent advancements in language modeling have improved robotic emotion expressiveness, yet several challenges remain. Many existing robotic expression models rely on fixed rules and static frameworks, which limit their ability to capture the dynamic nature of emotional expression. Additionally, these systems often struggle to balance emotional accuracy with generating novel and varied behaviors. These limitations underscore the need for method capable of delivering both emotionally accurate and diverse robot behaviors.

In this thesis, we addresses these challenges by introducing a new framework for expressive behavior generation in robots. We develop a generative model that generates robot behavior sequences that align …

Aging Effect On Effective Connectivity Within The Prefrontal-Motor Network And Postural-Related Muscle Responses During Dual-Task Paradigms, Jiahao Pan

Boise State University Theses and Dissertations

Falls are a significant global public issue for older adults, leading to severe health and social impacts. To understand the underlying mechanism of increased fall risk with aging, loss of postural automaticity has been suggested as increased prefrontal cortex and motor cortices activation, as well as worse balance performance in response to the secondary cognitive task. However, the interaction within these cortical regions and its effects on postural-related muscle responses are poorly understood. This dissertation investigated age-related changes in effective connectivity within the prefrontal-motor network, postural related lower limb muscle response, and biomechanical characteristics in response to the secondary cognitive …

Considerations For Developing Dna-Templated Dye-Aggregate Systems, Simon Kristopher Roy

Boise State University Theses and Dissertations

Molecular excitons have been the subject of significant research interest for nearly 100 years. Molecular excitons arise when conjugated organic molecules (dyes) are excited such that the resulting excitation is delocalized over multiple dyes in a wavelike manner. The shared excited states that allow the excitation energy to hop between molecules is of particular interest for applications that can make use of the wavelike properties of excitons, including applications in quantum information science. A key challenge for developing materials for these advanced applications is to overcome the knowledge gaps associated with precisely templating dyes with spatial control of their aggregation, …

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 …

Linearized Rigid-Body Dynamics Of Asymmetric Aircraft, Troy A. Abraham

All Graduate Theses and Dissertations, Fall 2023 to Present

Most aircraft are symmetric about their mid-plane, which permits simplifying assumptions when modeling their aerodynamic and mass properties, as well as estimating their dynamic modes. This work considers methods for modeling asymmetric aircraft, including capturing the dynamic mode characteristics that result from their asymmetric properties. While the primary focus of this work is on the dynamic mode properties of these aircraft, a significant portion of the dissertation is dedicated to modeling their aerodynamic, mass, and trimmed flight characteristics. The linearized rigid-body aircraft equations of motion used for dynamic mode estimates are developed to include the effects of asymmetries in both …

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 …

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 …

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 …

A Numerical Investigation Of Erection Bridging In Double-Pitched Open-Web Steel Joists, Logan Joshua Ward

All Graduate Theses and Dissertations, Fall 2023 to Present

Open-web steel joists are truss members used to support roofs and floors in steel buildings. They are commonly used because they are lightweight and inexpensive to manufacture on a large scale but have a large load carrying capacity due to their depth. Because of this depth, these joists are very unstable laterally, which is addressed by adding bridging (horizontal or diagonal) members between them to resist rotation of the joists. One of the bridging types is erection bridging, which is used to prevent a joist from buckling laterally while steel erectors are traversing it during construction.

The current erection bridging …

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.

An Optimization Study Of Multi-Orifice Synthetic Jets, Rhett T. Parry

All Graduate Theses and Dissertations, Fall 2023 to Present

From the mixing of creamer into coffee, to the dynamics of a dust storm, or smoke rising from a chimney—everything is driven by turbulent fluid motion. Experimentalists bring the complex driving mechanism that is turbulence into a laboratory setting to fundamentally understand its behavior in response to certain test parameters. Researchers may choose various drivers, or “actuators”, of fluid motion to start the turbulent regime for their applications. However, in building an entire experimental apparatus, they miss the step of ensuring that an individual driver is performing as best as possible. A common actuator used in experimental studies is a …

Optimal Distributed Energy Resource Control And Scheduling In A Microgrid Framework, Timothy M. Dodge

All Graduate Theses and Dissertations, Fall 2023 to Present

As we use more renewable energy, such as solar power, and add new devices, such as electric vehicle chargers and battery storage, to our buildings, the management of electricity becomes more complex. These local energy sources and devices can form small "microgrids" that need careful coordination to work efficiently with the main power grid. The system figures out the best times to use, store or charge different devices (such as batteries and EVs) to avoid costly, high electricity demand spikes and help stabilize the main power grid, especially when asked by the utility company. A major part of this work …

Metaheuristic Planning For Vehicle Fleets With Kinematic, Uncertain, And Battery Constraints, James Swedeen

All Graduate Theses and Dissertations, Fall 2023 to Present

The planning of vehicle actions and movements is becoming increasingly important in daily life. With the growing list of potential and current applications of autonomous planning, the field is faced with an ever-growing list of complications. These complications make the task of producing efficient plans increasingly difficult. This research studies and develops solutions for a few of the most important vehicle planning applications in recent years.

First, there is the planning of vehicle motion while considering the physical limitations of the vehicle. For many vehicles, for example, cars, airplanes, and boats, the biggest limitation is the inability to pan directly …

The Effects Of Effective Stress And Overconsolidation Ratio On The Undrained Shear Strength Of Soil, Gunniga Suwannawong

All Graduate Theses and Dissertations, Fall 2023 to Present

This study investigates the effect of effective stress and overconsolidation ratio (OCR) on normalized undrained shear strength, which represents the soil deformation and soil strength from applied load. Theoretical frameworks indicate that undrained shear strength (S_u) is affected by soil parameters such as void ratio and is linked to the soil consolidation condition, stress path, and stress history. Furthermore, S_u is functionally related to the OCR. The purpose of these test are to test two hypotheses: 1) that the undrained shear strength conforms with normalized soil engineering properties, this is true if the following equation describes the …

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. …

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 …

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 …