Digital Commons Network^™

Comparison Of Forces Generated By An Impinging Water Jet Using Numerical And Physical Experimentation, Spencer R. Young

All Graduate Theses and Dissertations, Fall 2023 to Present

When water is released from hydraulic structures such as dams water jets are formed and land on the downstream surfaces. When these jets land there is high potential for erosion or scour. Scour has the potential to compromise the structure and cause the uncontrolled release of water that can endanger downstream communities and infrastructure.

Engineers use tools including computational fluid dynamics (CFD) to inform their designs to mitigate the risk of scour. This study compares how well CFD is able to model the forces created by a water jet by comparing the results to laboratory collected physical data. To make …

A Cfd-Dem Framework For Characterizing Nanoparticle Adhesion Effects On Creeping-Flow Permeability In Composite Manufacturing, Gavin Stoker

All Graduate Theses and Dissertations, Fall 2023 to Present

Modern aircraft, spacecraft, and high-performance vehicles are increasingly built from composite materials, engineered combinations of plastics and fibers that are lighter and stronger than traditional metals. Researchers are now pushing these materials further by mixing in microscopic particles thousands of times smaller than a human hair, called nanoparticles, to make them even tougher and more resistant to damage. The challenge is getting those nanoparticles distributed evenly. During manufacturing, liquid plastic resin is pumped through a network of tightly packed fibers, carrying the nanoparticles along with it. But nanoparticles tend to clump together and stick to surfaces as they travel, clogging …

Experimental And Numerical Investigation Of Flow Coefficients In Three-Way, T-Port, Ball Valve, Tyler A. Mindrum

All Graduate Theses and Dissertations, Fall 2023 to Present

Many systems that move fluids, like water distribution networks and heating, ventilation, and air conditioning (HVAC) systems, rely on valves to control flow. This study evaluates a three-way valve, which can direct flow in multiple directions, but has not been extensively researched. Testing included physical data collection and computer simulations to compare how the valves behaved under different valve openings and flow conditions. The results showed that computer simulations can predict the general flow behavior of three-way valves, but that physical testing is still important, especially for valves with complex internal geometries.

A Laboratory Investigation Of Energy Dissipators At Embankment Dams, Nathan L. Young

All Graduate Theses and Dissertations, Fall 2023 to Present

Dams play a critical role in protecting communities from flooding and providing reliable water supplies. When large amounts of water pass through a dam’s spillway during floods, the discharge can travel at high speeds and carry potentially destructive kinetic energy that can damage the dam or erode downstream channels if that energy is not properly controlled. To reduce this risk, engineers commonly use hydraulic structures called energy dissipators that slow spillway discharge and safely release it downstream.

Commonly used energy dissipators at embankment dams include stilling basins that rely on a hydraulic jump – a sudden rise in water depth …

Cadmium Biosorption By Fusarium Venenatum And Its Application In Functional Permeable Materials For Metal Removal, Bradley Lawson

All Graduate Theses and Dissertations, Fall 2023 to Present

Heavy metals are pollutants of increasing concern as continued industrialization and urbanization have escalated the discharge of these toxins into aquatic environments. Cadmium (Cd) is a metal of particular concern due to its acute toxicity and high mobility in aquatic ecosystems. Given these characteristics Cd poses significant health risks to both humans and aquatic ecosystems. The continued development of sustainable, low-cost remediation technology is imperative to manage metal pollution.

This research explores the use of fungal-based remediation systems to remove Cd from contaminated water. Living biomass of the filamentous fungus Fusarium venenatum was evaluated as a biosorbent material for Cd …

Examining Ai Use Strategies Among Engineering Students: An Exploratory Quantitative Study, Jenny Lee Blonquist

All Graduate Theses and Dissertations, Fall 2023 to Present

Artificial intelligence tools like ChatGPT have quickly become part of everyday life for many people, including engineering students. This has raised concerns about the effects of students relying or over-relying on AI to help with their coursework. Are they still building the problem-solving and reasoning skills they will need as engineers? The purpose of this study is to understand not just whether engineering students use AI, but how they use it.

This research focused on two different ways students can use AI tools. 'Understanding-seeking' is when a student uses AI as a learning support such as asking thoughtful questions to …

Modulating Linear Frequency Modulated Pulses To Send Communications Data In A Bistatic Sar Scenario, Jarren T. Worthen

All Graduate Theses and Dissertations, Fall 2023 to Present

Synthetic aperture radar (SAR) is the technology that enables the creation of images using radar waves, allowing images to be formed regardless of weather. In bistatic SAR a radar platform uses a radar pulse from a separate platform to form an image. It is important that these radar systems are able to communicate with each other. Rather than wasting energy and space flying with a separate communication system, the radar systems could use the already existing SAR system to send data between each other while still forming SAR images. The work of this thesis is to show how very simple …

High-Throughput Characterization Of Creep In Additively Manufactured 316l Stainless Steel, Raushan Kumar Singh

All Graduate Theses and Dissertations, Fall 2023 to Present

Advanced materials are widely used in industries such as nuclear energy, aerospace, and automotive engineering, where components are exposed to extreme temperatures and stresses over long periods of time. As new materials continue to emerge, researchers need efficient ways to evaluate their mechanical performance so they can be used safely and effectively. Among several mechanical challenges, creep is a major concern in these conditions. Creep is a type of mechanical failure in which materials gradually deform when exposed to high temperatures and constant load. Conventional methods for evaluating creep typically involve testing a single specimen at a time, which can …

Theory, Implementation, And Practical Applications Of A Modern Parabolized Navier-Stokes Code, Logan B. Freeman

All Graduate Theses and Dissertations, Fall 2023 to Present

The Parabolized Navier-Stokes (PNS) method is a specialized computational approach for solving the equations that govern fluid flowing faster than the speed of sound, known as supersonic flow. By leveraging unique physical properties of supersonic environments—specifically that information cannot travel upstream—this method allows for significantly more efficient calculations than traditional approaches. Supersonic flows are important for many military and civilian applications including hypersonic weapons, high-speed passenger aircraft, and reentry. This thesis provides a comprehensive review of the two-dimensional PNS formulation, detailing the mathematical derivation and its practical implementation for solving flow problems. Through performance analysis and error assessment, this research …

Simulation Of Hypersonic Conditions In A Lab-Scale Environment Using A Hybrid Rocket With Nitrogen Cooling, Joshua R. Sorenson

All Graduate Theses and Dissertations, Fall 2023 to Present

Developing hypersonic vehicles requires testing under extreme heat, airflow, and pressure. Traditional facilities like shock tunnels and arc-heated wind tunnels are costly and slow to set up. This thesis proposes a simpler, low-cost method using a small-scale hybrid rocket motor as a gas generator. The rocket’s hot exhaust is directed onto the front edge of a scaled-down model that represents the nose of a hypersonic vehicle. This creates a realistic flow that matches both the intense heat energy and the pushing force experienced in high-altitude hypersonic flight. The setup allows easy measurement of motor performance, surface pressures, leading-edge temperatures, and …

Thermal Rating And Prediction Of Roadway-Embedded Power Electronics For Dynamic Wireless Power Transfer, Forrest D. Nichols

All Graduate Theses and Dissertations, Fall 2023 to Present

Electric vehicles can be charged while driving through wireless charging coils buried in the road surface. To avoid running expensive cables from roadside equipment to each charging pad, the electronics that control the power transfer can also be buried in the road. However, burying these circuit boards removes the ability to cool them with fans or flowing air, so the heat generated during operation must escape naturally into the surrounding road material. If the boards get too hot, components fail—a problem that has already been observed in prototype systems.

Predicting how hot each component on a circuit board will get …

Clogging Behaviour And Management In Two Full-Scale Infiltration Schemes: A Treated Wastewater Basin And A Surface-Water Weir In Australia, John Awad, Declan Page, Joanne Vanderzalm, Geoffrey J. Puzon, Jason Wylie, Falko Mathes, Debbie Reed, Michael Bartkow, Mehdi Khiadani, Karen Barry, Peter Dillon

Research outputs 2022 to 2026

Managed Aquifer Recharge (MAR) schemes are increasingly used to enhance water security, yet infiltration schemes are susceptible to clogging which consequently reduces operational efficiency. This study examines two full-scale Australian case studies: Jurien Bay (JB, Western Australia) and Lockyer Valley (LV, Queensland), representing treated wastewater (TWW) and surface water recharge, respectively. Recharge water at JB exhibited high clogging potential in relation to literature values proposed to manage clogging: total suspended solids (TSS) ranged from 100 to 176 mg/L (target ≤2 mg/L), turbidity 70–100 NTU (target ≤3 NTU), and total nitrogen (TN) 5–16 mg/L (target ≤10 mg/L). LV showed lower clogging …

Experimental Thermal-Hydraulic Performance Enhancement Of A Parabolic-Trough Solar Collector Using 3d-Printed Propeller-Shaped Turbulators, Shayan Pourhemmati, Barun Kumar Das, Majid Tolouei-Rad, Abdellah Shafieian

Research outputs 2022 to 2026

This experimental study investigates the thermal-hydraulic performance of a parabolic trough collector (PTC) equipped with propeller-shaped turbulators, which were 3D printed and installed along the absorber tube to enhance convective heat-transfer by increasing flow mixing. Nine turbulator configurations were tested by varying the blade angle (β = 22.5° and 45°, and β = 67.5°) and the number of turbulators (Nt = 6, 12, and Nt = 18) over a Reynolds number range of 1000 to 6000. To ensure a rigorous and unbiased comparison, all experiments were conducted under identical operating conditions, including a constant inlet temperature and a constant Reynolds …

Optimizing Few-Shot Learning In Pruned Large Language Models With Task-Specific Prompts, Danyal Aftab

Dissertations

Few-shot learning enables large language models to efficiently perform tasks given only a limited number of labeled examples. However, training these models entirely from scratch requires substantial computational resources, making it challenging for many organizations to fully leverage their potential. This thesis explores how structured pruning, task-specific prompting, and parameter-efficient fine-tuning can be combined to preserve few-shot learning capabilities in compressed LLMs, while also extending their utility to real-world recommendation systems.

In this research, we propose the Tailored LLM framework, which first reduces model size through structured pruning and then enhances few-shot learning performance using carefully designed prompts. We experiment …

Policy And Regulation In Virtual Power Plants Development, Hemlal Bhattarai, Aziz, Stefan Lachowicz

Research outputs 2022 to 2026

Electricity systems are changing due to the rapid deployment of distributed energy resources (DER), which also presents significant regulatory obstacles to their coordinated integration into energy markets and power grids. However, the majority of current material in publications concentrate on operational optimization and technical architectures, with little systematic synthesis of the legal and policy frameworks governing the deployment of VPP on a broad scale. To provide grid services, improve flexibility and support decarbonization objectives, virtual power plants (VPP) have become a crucial aggregation method. To close this gap, this research critically looks at the institutional roles, market structures, global policy …

Multistage Integrated Systems For Wastewater Treatment And Resource Recovery: A Systematic Process Design Framework, Mahsa Golmohammadi, Ensiyeh Taheri, Ratish Ramyad Permala, Sebastien Allard, Mehdi Khiadani, Amir Razmjou

Research outputs 2022 to 2026

The wastewater treatment paradigm is shifting from pollutant removal toward integrated systems that simultaneously achieve contaminant treatment and resource recovery. Despite extensive literature on individual technologies, systematic frameworks for designing multistage integrated wastewater treatment and resource recovery systems remain notably absent. This review addresses this gap by developing a comprehensive decision framework that guides designers from influent characterization through technology selection across pretreatment, main process, and post-treatment stages. The framework accommodates diverse integration strategies, ranging from fully unified treatment processes to stage-specific configurations where each treatment stage employs technologies tailored to its designated function. Rather than optimizing for a single …

Secure And Compassionate Dementia Care: Non-Intrusive Remote Monitoring Of Falls, Wandering, And Agitation, Awan-Ur- Rahman

Master's Theses

Alzheimer’s disease and related dementias (ADRD) present significant safety challenges, as affected individuals may experience falls, wandering, agitation, and a progressive decline in independence. Although continuous monitoring can enable timely intervention, many existing systems rely on cameras or wearable devices, which may introduce concerns related to privacy, comfort, and sustained use. This thesis explores privacy-preserving and non-intrusive remote monitoring through two complementary studies. The first study presents an ambient Wi-Fi channel state information framework for recognizing agitation and eight daily activities. The proposed approach translates behavioral and physiological markers commonly captured by wearable sensors into the Wi-Fi sensing domain. The …

Constructing Female High School Students’ Stem Self-Efficacy: The Role Of High School Stem Research Experiences, Hyunjin Son

Dissertations

In the U.S., nearly a quarter of the workforce is employed in Science, Technology, Engineering, and Mathematics (STEM) occupations. However, the STEM workforce lacks diversity, limiting perspectives to address real-world problems facing society. While many factors influence decisions to pursue STEM majors in college and enter the STEM workforce, one factor commonly associated with performance and persistence in STEM is STEM self-efficacy. Independent research experiences have been shown to increase conceptual understanding and confidence in STEM, leading to STEM degrees and careers. As high school co-curricular STEM research opportunities become more common, the effects of such experiences on students’ STEM …

Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury

Dissertations

The environmental benefits of electric vehicle (EV) adoption depend on more than replacing internal combustion engine vehicles with electric powertrains. EV adoption reshapes electricity demand, interacts with regional generation mixes, and influences travel behavior and congestion, creating a coupled transportation-energy system in which vehicle and power-plant emissions must be evaluated together. This dissertation develops machine-learning frameworks for predicting energy consumption and emissions from vehicles and power grids under rising EV adoption. The first component forecasts grid emissions from EV charging. Using simulation data from NREL's Cambium database, a Prophet-based time-series framework predicts carbon dioxide, nitrous oxide, and methane emission rates …

Understanding The Correlation Between Prediction Performance And Trust In Ai Through Scenario-Based Tasks, Likhitha Kammara

Theses and Dissertations

Trust in artificial intelligence is commonly assessed through self-reported scales or behavioral reliance, yet behavioral reliance is retrospective and can only be observed after a decision has already been made. This thesis examines whether prediction accuracy — a user's ability to predict what an AI system will recommend before its output is revealed — can serve as a prospective correlate of trust in the same empirical sense as behavioral reliance. The study was conducted in two phases using scenario-based AI decision tasks across disaster response, healthcare, and infrastructure restoration contexts, employing a between-group design in which participants either predicted AI …

Review: Mechanics Of Mycelium Materials, Md Anwar Sadat Anik, Ehsanul Azim, Gerardo I. Zapata, Mohammad R. Islam

Mechanical Engineering Faculty Publications

The biological growth of fungal root structure, called mycelium, can be engineered to develop innovative fibrous and biocomposite materials. Mycelium materials have potential as sustainable alternatives to petroleum-derived materials for load-bearing applications. To realize this potential, there is an increasing effort dedicated to understanding the mechanics of mycelium materials. This work presents a systematic review of our current understanding of the mechanics of mycelium materials with a specific focus on structure–property relationships. The review first explores how the mycelium’s fiber network structure varies depending on whether it is grown as a two-dimensional (2D) membrane, a cellular foam, or as a …

Prompt-Driven Tabletop Robotic Manipulation With A Structured Llm Interface And Visual Verification, Tomas Franco

Master's Theses

Creating a tabletop robotic manipulation system that connects language goals to robot actions is a challenging problem. Large language models can interpret mission objectives and reason through actions, but when placed directly in control of hardware they can produce hallucinated commands that result in unsafe behavior without the proper safeguards.

This thesis presents a constrained LLM-guided manipulation system built around the Quanser Qarm, a four degree of freedom manipulator with a mounted Realsense RGB-D camera and a gripper with readable current. Every decision made by the LLM planner is routed through a gated command interface that restricts the model to …

Hardware-In-The-Loop Evaluation Of Sensor-Source Selection For Prosthetic Locomotion Intent Recognition, Victoria Asencio-Clemens

Master's Theses

Active lower-limb prostheses use intent-recognition systems to identify a user’s locomotion mode and select an appropriate control strategy, but sensor configurations that perform well offline may be unsuitable for resource-constrained embedded hardware. Existing sensor-selection methods generally prioritize classification accuracy without directly accounting for processing latency, memory usage, or other hardware-dependent requirements. To address this limitation, this thesis develops a hardware-in-the-loop source-selection framework for embedded classification of level walking, ramp ascent, ramp descent, stair ascent, and stair descent using multimodal biomechanical data from transtibial amputee participants. Subject-specific linear support vector machine classifiers were evaluated using trial-held-out validation, and candidate configurations from …

Predicting Student Belonging In Computing Education: A Multimodal Machine Learning Approach Using Eeg And Survey Data, Hannah Moshtaghi

Master's Theses

Measuring students’ sense of belonging, characterized by feelings of acceptance, inclusion, and encouragement from teachers, remains a significant challenge in computing education. Prior research has associated this multidimensional construct with positive academic outcomes and has identified instructors’ growth- and fixed-mindset messaging as a potential influence. However, belonging is a complex and deeply personal experience that is difficult to capture through direct observation alone. Current measurement methods rely on self-report surveys, which may not capture every aspect of an experience that can also involve emotional and cognitive responses.

This thesis investigates whether combining EEG data recorded during a belonging questionnaire with …

A Maintainable Extensible And Performant Compiler Toolchain For The Trustguard Architecture, Ethan N. Emery

Master's Theses

TrustGuard is a hardware architecture implementing a CAVO (Containment Architecture with Verified Output) model, which provides security guarantees by bootstrapping trust of a system to a hardware component known as the Sentry. Rather than verifying an entire system, TrustGuard re-executes trusted computation on the Sentry and validates the host system's execution before allowing values to pass to the outside world, thereby containing the effects of erroneous computation. Implementing this architecture in practice without hardware modifications to a host CPU requires a compiler toolchain capable of automatically generating instrumented binaries for both the untrusted host and the trusted Sentry from C …

Expected Structural Damage, Residual Capacity, And Repairability Of Light-Frame Timber Houses, Mikayla Caruthers

Master's Theses

Earthquake damage in light-frame timber structures is commonly evaluated using peak inter-story drift. However, drift alone does not fully represent the remaining structural capacity of a building or its ability to be repaired following a seismic event. Although expected structural damage, residual capacity, and repairability have each been studied extensively, these concepts are often considered independently, leaving limited guidance that links them within a unified post-earthquake assessment methodology.

This thesis establishes an integrated framework that relates expected structural damage, residual capacity, and repairability for light-frame timber residential structures. Existing literature was synthesized to develop drift-based damage-state classifications, identify methods for …

Synthesis And Characterization Of Carbon Quantum Dots And Gold Nanoparticles For Norovirus Biosensing Applications In Water Systems, Breanne Evans

Master's Theses

Rapid, reliable detection of viral pathogens remains a significant challenge across water-treatment and environmental monitoring systems, including drinking-water, wastewater, water reuse, and environmental surveillance applications. Waterborne viral contamination can pose substantial public-health risks, making early detection essential for protecting water quality and responding quickly to treatment failures or contamination events. Direct potable reuse (DPR) is one particularly demanding example because it requires continuous verification of treatment performance and the broader need for rapid virus monitoring extends across many water-treatment and environmental surveillance applications. Norovirus is a priority target because of its widespread occurrence in wastewater, environmental persistence, and exceptionally low …

A Technoeconomic And Lifecycle Analysis Of Catalytic Non-Thermal Plasma Steam Methane Reforming For Renewable Hydrogen Production, Gustav M. King

Master's Theses

When produced with sufficiently low life-cycle emissions, hydrogen may support low-carbon, dispatchable electricity generation to realize statewide renewable energy regulatory objectives. This thesis develops a screening-level electrothermochemical process model of catalytic non-thermal plasma steam methane reforming (CNTP-SMR) and integrates it with techno-economic and life-cycle assessments. Biogas and natural gas fed CNTP-SMR scenarios are compared with conventional steam methane reforming to evaluate hydrogen production cost, global warming potential, and the effects of key operating parameters. Under the baseline assumptions, CNTP-SMR generated hydrogen at a higher levelized cost (baseline of $3.86/kg H₂ and a range of $3.68 to $4.11) when compared …

Asm And A Culture Of Sharing, Caring, And Fun In Education, David J. Westenberg

Biological Sciences Faculty Research & Creative Works

One doesn't always equate a professional scientific society with sharing, caring, and fun, but in this age of public distrust, public engagement with science and active student learning are ways to regain trust. ASM holds a leadership position in promoting and recognizing the value of education in the future of our profession and is there to support your educational journey. From K12 outreach and public engagement, to professional development, to presenting and publishing scholarship of teaching and learning, ASM has been at the forefront of biology education. Under the leadership of visionary directors such as Amy Chang and now Irene …

A Transfer-Learning And Continuous Optimization-Based Framework For Predicting Heat Treatment-Dependent Mechanical Properties Of Ded-Processed Low-Alloy Steels, Atiqur Rahman, Sung Heng Wu, Ranjit Joy, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Directed energy deposition (DED) of low-alloy steels involves strongly coupled effects among alloy composition, solidification behavior, and post-deposition heat treatment, making mechanical property prediction difficult when target-domain data are limited. This study develops a transfer-learning and continuous optimization framework for predicting heat treatment-dependent yield strength (YS), ultimate tensile strength (UTS), hardness (HV), and as-solidified phase fractions of martensite, ferrite, and austenite in DED-processed low-alloy steels. A CALPHAD-based dataset was generated for 125 low-alloy steel compositions. A multilayer perceptron (MLP) surrogate was first trained as a baseline model, then fine-tuned through transfer learning and progressively updated as staged continuous optimization; the …