Engineering Commons^™

Modeling Disaster Resilience Through A Human-Centered Lens: Exposure, Vulnerability And Adaptation, Tong Liu

All Dissertations

The core of reframing and operationalizing disaster resilience with a human-centered lens is to incorporate concepts from socio-ecological resilience into engineering resilience to better understand the humans’ capability for disaster adaptation. Existing studies have drawn practical implications by identifying actionable thresholds for infrastructure systems under disasters, which can be easily applied by policymakers, emergency managers and municipal agencies. However, how individuals interact with, respond to, or adapt under these infrastructure thresholds remain understudied. This hinders the operationalization of disaster resilience at the human scale.

First, I examined exposure by analyzing how configuration and distribution of urban infrastructure systems, such as …

Synthesis And Characterization Of Magnetic Nanoparticles To Study Effective Magnetic Anisotropy For Biomedical And Catalytic Applications, Alexander Malaj

All Dissertations

This dissertation focuses on understanding how to tune the magnetic properties of nanoparticles through controlling the effective magnetic anisotropy (Keff), which is a key variable in determining a nanoparticle’s Néel relaxation time, which will dictate its magnetic behavior in various applications. In this work, magnetocrystalline anisotropy is tuned by synthesizing tri-metallic substituted ferrite (Fe3-x-yMnxCoyO4) nanoparticles with specific metallic compositions that were informed by computer simulations using density functional theory (DFT) to target magnetocrystalline anisotropy values. A drip synthesis was used to control the size and composition of the tri-metallic ferrites, which were revealed to be monodisperse and compositionally mixed by …

Constructing A State: Canals And The Transformation Of The Economy, Politics, And Finance In Nineteenth-Century New York, Youwei Xing

All Dissertations

This dissertation consists of three essays in economic history, unified by a focus on one of America's earliest transportation infrastructures, the canal system, in nineteenth-century New York. Each chapter explores a different aspect of the state's transformation: its economy, politics, and finance, each of which helped construct New York as the Empire State.

The first chapter studies the economic impact of canals on economic modernization from three aspects: sectoral transition, urbanization, and banking development. Contrary to much of the modern literature finds transportation infrastructure leads to decentralization, I find the opposite-evidence of centralization. Specially: (1) canal towns experienced a transition …

Fleet Algorithm Design For Pooled Rideshare: Integrating Human Factors, Simulation, And Optimization, Joseph Paul

All Dissertations

This dissertation explores the study the integration of human factors modeling and rideshare fleet control algorithms. Pooled rideshare is a unique transportation mode offering that allows riders increased flexibility and accessibility over public transportation, and decreased cost relative to personal vehicles or traditional rideshare. Additionally, relative to personal vehicles, pooled rideshare offers reduced costs and options for those with difficulty obtaining transportation. Prior research in the space typically focused on modeling human behavior, or optimizing system performance, but a lack of integration of the concepts leads to unrealistic or underutilized outcomes. To tackle this problem, novel rideshare assignment, and repositioning …

International Comparison Of Weather And Emission Predictive Building Control, Christian Hepf, Ben Gottkehaskamp, Clayton Miller, Thomas Auer

Research Collection College of Integrative Studies

Building operational energy alone accounts for 28% of global carbon emissions. A sustainable building operation promises enormous savings, especially under the increasing concern of climate change and the rising trends of the digitalization and electrification of buildings. Intelligent control strategies play a crucial role in building systems and electrical energy grids to reach the EU goal of carbon neutrality in 2050 and to manage the rising availability of regenerative energy. This study aims to prove that one can create energy and emission savings with simple weather and emission predictive control (WEPC). Furthermore, this should prove that the simplicity of this …

Developing An Integrated Risk Assessment Framework To Quantify The Resilience Of Critical Railway Infrastructure: Characterization Of Risks And Hazards To The U.S. Rail Network Through Empirical Data And Past Events, Haizhong Wang, Brian M. Staes, Benyamin Ghoreishi

Mineta Transportation Institute

To improve understanding of the impact of natural hazards on the U.S. railway system, this project developed a comprehensive, geospatially precise dataset that maps historical hazard events to specific rail segments. The project provides insight into when, where, and how much damage natural hazards have inflicted on rail infrastructure across the country. While a rail-specific hazard database did not previously exist, this research combines data from the Geological Survey (USGS) Flood Events Database, Hydrologic Unit Codes (HUC), the National Centers for Environmental Information (NCEI) from the National Oceanic and Atmospheric Administration (NOAA), and the National Weather Service (NWS) forecast zones. …

Genwriter: Reducing Gender Cues In Biographies Through Text Rewriting, Shweta Soundararajan, Sarah Jane Delany

Conference papers

Gendered language is the use of words that indicate an individual’s gender. Though useful in certain context, it can reinforce gender stereotypes and introduce bias, particularly in machine learning models used for tasks like occupation classification. When textual content such as biographies contains gender cues, it can influence model predictions, leading to unfair outcomes such as reduced hiring opportunities for women. To address this issue, we propose GenWriter, an approach that integrates Case-Based Reasoning (CBR) with Large Language Models (LLMs) to rewrite biographies in a way that obfuscates gender while preserving semantic content. We evaluate GenWriter by measuring gender bias …

Heat-Pipe-Based Thermal Management System Design For A 250-Kw Gan-Based Integrated Modular Motor Drive, Seyed Iman Hosseini Sabzevari, Salar Koushan, Armin Ebrahimian, Towhid Islam Chowdhury, Nathan Weise, Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

Integrated modular motor drive (IMMD) is an effective approach for realizing high-efficiency, high-power-density, and fault-tolerant electric machines. However, designing an efficient thermal management system (TMS) for the motor drive becomes a challenge, particularly due to space constraints. This article presents the design of a TMS based on 3-mm heat pipes for a 250-kW IMMD intended for aviation applications. The power electronics module is simulated using PLECS software where an electrothermal analysis is conducted. A simplified thermal resistance model of the system is developed to estimate the die junction temperature of gallium nitride (GaN) semiconductors. The performance of the proposed TMS …

Applying Large Language Models For Surgical Case Length Prediction, Adhitya Ramamurthi, Bhabishya Neupane, Priya Deshpande, Ryan Hanson, Srujan Vegesna, Deborah Cray, Bradley H. Crotty, Melek Somai, Kellie R. Brown, Sachin S. Pawar, Bradley Taylor, Anai N. Kothari

Electrical and Computer Engineering Faculty Research and Publications

Importance Accurate prediction of surgical case duration is critical for operating room (OR) management, as inefficient scheduling can lead to reduced patient and surgeon satisfaction while incurring considerable financial costs.

Objective To evaluate the feasibility and accuracy of large language models (LLMs) in predicting surgical case length using unstructured clinical data compared to existing estimation methods.

Design, Setting, and Participants This was a retrospective study analyzing elective surgical cases performed between January 2017 and December 2023 at a single academic medical center and affiliated community hospital ORs. Analysis included 125493 eligible surgical cases, with 1950 used for LLM fine-tuning and …

Synergistic Enhancement Of Tribological Behavior And Colloidal Stability In Cuo Nanolubricants Via Ligand Tuning, Sherif Elsoudy, Sayed Akl Akl Dr, Sayed Akl A. Akl Dr, Esm Lane, Abas Hadawey, Philip D. Howes

Mechanical Engineering

Nanoparticle-based lubricants, or nanolubricants, can exhibit superior tribological properties compared to unmodified base oils. However, these performance gains are highly dependent on the nanoparticle surface chemistry, particularly in maintaining stable colloidal dispersions. This study explores the influence of oleic acid (OA) and oleylamine (OAm) functionalization on the tribological and colloidal properties of CuO nanoparticles dispersed in an SAE 20W50 base oil. We present a hybrid optimization framework combining Response Surface Methodology (RSM) with Bayesian Optimization (BO) to identify the optimal OA to OAm ratio (OA–OAm) for CuO nanolubricants. Unlike prior studies that employed either RSM alone or trial-and-error approaches, this …

Revealing Building Operating Carbon Dynamics For Multiple Cities, Winston Yap, Abraham Noah Wu, Clayton Miller, Filip Biljecki

Research Collection College of Integrative Studies

Achieving carbon neutrality is a critical yet elusive goal for many cities, hindered by limited understanding of the relationship between building emissions and their surroundings. To address this challenge, we present a generalizable open science framework that integrates building energy-consumption data, multi-modal geospatial inputs and graph deep learning to quantify building operating emissions and their links to urban form and socio-economic factors. Applying this approach to five cities with diverse climates and planning contexts—Melbourne, New York City (Manhattan), Seattle, Singapore and Washington DC—we demonstrate that our models explain 78.4% of the variation in building operating carbon emissions across cities, achieving …

Development And Application Of Novel Apparatus For Ocean Spray In Turbulent Atmospheres, Alicyn S. Koldewyn

All Graduate Reports and Creative Projects, Fall 2023 to Present

Ocean spray droplets can have significant effects including reducing surface heating from the sun, degrading air quality, and intensifying tropical cyclones. However, quantifying these effects has been challenging due to the multiscale, chaotic nature of wave breaking and turbulent flow. This research presents the development of a novel apparatus designed to combine bubble column droplet generation with synthetic jet actuators for turbulence generation. The purpose is to demonstrate reliable bubble formation and droplet generation, air turbulence effect on droplet dynamics, and quantitative measurement and analysis of these effects. The primary goals of the apparatus include optical accessibility for high-resolution imaging, …

Effective Transformer Networks For Undersampled Magnetic Resonance Image Reconstruction, Tahsin Rahman

Open Access Theses & Dissertations

The proliferation of data-driven tools for solving problems in every possible domain, coupled with rapid advances in computing technology, has led to an arms race of AI development and application research in industry and academia. One field of research that stands to gain immeasurably from this revolution is medical imaging. It is a critical part of modern diagnostics, and advancements in this area can directly benefit the average person by making healthcare more accessible, accurate, and affordable. Breakthroughs in mainstream image processing and computer vision have long fueled development in medical imaging, and it is now common to see cutting …

Model-Based Systems Engineering For Aerospace Applications: Strategic Requirements Prioritization In Complex Adaptive Systems And Digital Integration, Iqtiar Md Siddique

Open Access Theses & Dissertations

Ineffective systems engineering practices continue to jeopardize aerospace missions, resulting in multi-billion-dollar losses, delays, and fragmented development outcomes. As complexity intensifies and timelines shrink, conventional document-based methods increasingly fail to support early validation, cross-domain traceability, and synchronized tool usage. This research presents an integrated approach that addresses three critical gaps: synchronizing executable and traceable MBSE models across structural, behavioral, and requirements domains; applying scalable requirements prioritization techniques tailored for Complex Adaptive Systems; and establishing automated simulation feedback loops through digital toolchain integration. Central to this strategy is the Digital Trinity, which connects system models, simulations, and lifecycle data through a …

Pressure Recovery Analysis Downstream Of Valves And Meters: An Experimental And Numerical Investigation, Stephen J. Sanders

All Graduate Theses and Dissertations, Fall 2023 to Present

In pressurized water systems, flow control devices such as valves and meters cause pressure losses that can affect energy efficiency and measurement accuracy. Industry standards assume that all devices recover within the same distance downstream, but this may not be true for all device types. In this study we used laboratory testing and computer modeling to determine how far downstream pressure stabilizes after flowing through various valves and meters. Devices like Venturi meters recovered pressure quickly, while orifice plates required longer distances and resulted in greater permanent energy loss. In most cases, pressure recovered within four to six pipe diameters. …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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. …

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 …

Digital Twin For Real-Time Monitoring And Control Of Conveyor Systems Using Flexsim, Ai And Plc Integration, Jose Francisco Arvizu Astorga

Open Access Theses & Dissertations

Modern manufacturing is making significant advancements by innovating and automating most processes. However, a major challenge remains: systems are constantly evolving and becoming more complex to analyze. Fortunately, a powerful tool can help, Digital Twin (DT) technology. This technology enables the analysis and optimization of processes like never before. A Digital Twin is a real-time virtual model of a physical system that continuously up dates with live data. One of its greatest features is the ability to create infinite scenarios, allowing hundreds of configurations to be tested virtually, risk-free, and without making any real-world changes that could disrupt ongoing operations. …