Engineering Commons^™

Low-Field Magnetoresistance In Nanocomposites Of La₀.₇Sr₀.₃Mno₃ And Metal Oxides, Nicholas K. Thiel-Hudson

University Scholar Projects

Pure La_0.7Sr_0.3MnO₃ (LSMO) exhibits colossal magnetoresistance (CMR) with large applied magnetic field over a narrow temperature range (intrinsic behavior), limiting its application to narrow temperature ranges. In contrast, the extrinsic CMR effect originates from inhomogeneities at larger length scales, such as grain boundaries and phase separation, where the structural features act as tunneling barriers, leading to a low-field magnetoresistance (LFMR) response, thereby expanding the application of LSMO into the low-field regime over a broader temperature range. In this work, the magnetotransport behavior of pure LSMO thin film is compared to the composite layered heterostructures of …

Design And Implementation Of A Notification System For The Purpose Of Improving Communication Between Nurses And Patients, Aindrila Bhattacharya

2025 Spring Honors Capstone Projects - Archive

Communication is an important part of how nurses administer treatment to their patients. Without proper communication, it is difficult for the nurses to connect with their patients and vice versa. This paper will be going into some previous literature about communication between patients and nurses in general, communication with respect to pediatric patients and how notification systems have been implemented in the past. It will then discuss the methodology and implementation of a notification system for a medical app. The medical app is meant to facilitate communication from the side of the patient to the nurse, while the notification system …

Controlling A Mobile Inverted Pendulum And Optimizing Leaning Angle To Apply Force Using Reinforcement Learning, Aryan Mediratta

2025 Spring Honors Capstone Projects - Archive

Reinforcement Learning is a Machine Learning paradigm that involves simulating learning through rewards and penalties in intelligent systems. This technique is often employed in robotics when traditional control methods are insufficient or when human intuition does not provide a good solution on how to control robot systems, This project involves training a Segway-style Mobile Inverted Pendulum (MIP) robot to balance and push a box forward. The BeagleBone Blue board is used that includes a built-in Inertial Measurement Unit (IMU) and encoder ports. These sensors enable the system to measure its current state. The goal is to find the optimal leaning …

Integration Of Notes Section With Access Management, Inshaad Merchant

2025 Spring Honors Capstone Projects - Archive

This research explores the development of a notes section with access management, specifically designed to assist Computer Science and Engineering students to revisit and revise all the notes and key points highlighted in their tutoring sessions. While the senior design project focuses on the CSE Student Success Center application that allows students to schedule tutoring sessions, manage appointments, and manage their profiles within this application, the Honors capstone project adds on a specific section for students to save all their notes and important video links and attachments to continue their learning outside of the tutoring sessions. A centralized platform for …

Tutortech: A Web App For A Smarter And More Efficient Tutoring System, Smarika Pathak

2025 Spring Honors Capstone Projects - Archive

The Computer Science and Engineering (CSE) department faces challenges with managing its tutoring services, especially tracking attendance, booking sessions, and overall management of the tutoring system - all of which severely limits the ability for tutors to connect and engage with students. To help overcome these issues, TutorTech, a web-based application that provides improved management of the tutoring system and supports more engaging learning experiences between students and tutors was designed. Through this project, the aim was to optimize the TutorTech search capabilities - assisting students to find tutors based on skills, while also considering the effect of user interface …

Beyond The Hard Hat: Examining Barriers Of Women In Construction, Allison Pham

2025 Spring Honors Capstone Projects - Archive

The construction industry is falling behind in female representation, with women only making up 11.2% of the industry. The existing labor shortage is further exacerbated by the limited interest among women to pursue a career in construction. The purpose of this research is to investigate the factors that contribute to the lack of women in the construction industry and explore how HR strategies can attract and retain women in construction careers. Environmental, Social, and Governance (ESG) reports from three different industries were used to analyze the percentage of men and women employees. Multivariate regression analyses were conducted to examine whether …

Development Of A Cost-Effective Daq For Measuring Brake Performance In Race Cars, Adrin Alias

2025 Spring Honors Capstone Projects - Archive

This project explores the feasibility of creating a cost-effective data acquisition (DAQ) system for high-speed, real-time brake performance testing of Formula SAE racecars. The research addresses the limitations of the current MoTeC DAQ system currently employed by the team, which is costly and time-consuming to set up for on-car testing. The team will use a brake dynamometer for steady-state comparisons of different brake pad compounds (senior design project), but evaluating real-world performance requires on-car testing. By systematically comparing various hardware platforms, sensors, communication protocols, and storage solutions, this project aims to balance cost-efficiency with reliability and performance. The research evaluates …

Computational Modeling Of Torque Arm And Load Cell Interactions In Uta Racing Brake Dynamometer, Anthony A. Aiyedun

2025 Spring Honors Capstone Projects - Archive

The UTA Racing Team is developing a brake dynamometer to measure the coefficients of friction of various brake pads and calipers under controlled conditions. The dynamometer simulates on-track braking scenarios, testing brake pads at temperatures up to 1300ºF and pressures similar to racing environments. Its primary goal is to generate accurate friction vs. temperature graphs for various brake pad and rotor combinations, addressing the need for dedicated testing equipment. This project creates an ANSYS simulation of the torque arm and load cell interaction. The computational model accurately represents the relationship between applied torque and measured load cell force, incorporating precise …

A Data Driven Approach To Student Success: Visualizing Engagement And Performance Metrics, Araohat Kokate

2025 Spring Honors Capstone Projects - Archive

Many tutoring centers lack tools to analyze and visualize key performance metrics, limiting data driven decision making. This study develops a data visualization feature for the CSE Student Success Center App at the University of Texas at Arlington, enabling administrators to track student engagement, tutor performance and session trends. Using the data of students and tutors, the feature provides interactive dashboards for real-time insights. Administrators can monitor attendance patterns, tutor workloads and booking trends, optimizing resource allocation. Findings indicate that real-time data visualization enhances decision-making, reducing manual effort while improving operational efficiency. This can further help improve student support services. …

Design Of A Helical-Type Rotor For Enhanced Energy Harvesting In Smallscale Vertical Axis Wind Turbines, Aadee M. Mitee

2025 Spring Honors Capstone Projects - Archive

This research investigates the design optimization of a small-scale Vertical Axis Wind Turbine (VAWT) utilizing helical rotor blades fabricated from graphene-reinforced polyethylene terephthalate. While previous studies have largely concentrated on largescale turbines for rural environments or on high-performance composite materials that often compromise recyclability, this research addresses the specific challenges associated with small-scale VAWTs intended for urban and populated areas. The study identified tip speed ratio, helical angle, and blade length as critical design parameters. Optimization of these parameters was achieved through systematic evaluation of their impact on the turbine’s aerodynamic performance, quantified by the coefficient of performance. Structural and …

Near-Earth Object (Neo) Surveyor Development: Challenges And Opportunities In Support Of Planetary Defense, G. Loftus, B. Carlsen, P. Scott, S. Backlund, L. Reinhart, T. Martin, T. Hoenes, R. Burgon, S. Ashby, J. Peterson, B. Lamborn, J. Bowman

Space Dynamics Laboratory Publications

The Near-Earth Object (NEO) Surveyor mission is a key element in our future planetary defense portfolio, which will survey our solar system in the infrared to discover and characterize asteroids and comets.

The mission is designed to detect, track, and characterize small bodies throughout our solar system. By United States Congress mandate, NASA must discover more than 90% of all asteroids and comets that are larger than 140 meters in diameter and could potentially impact Earth. NEO Surveyor will provide critical decision support for stakeholders who must assess the risks of NEO impacts to Earth and identify potential mitigation strategies. …

Hickory Street Square Revitalization, Spencer Knight, Grace Dungan, Tim Kula, Evan Lauritsen, Lindsey Mennenga

Honors Program: Senior Projects (Public)

The Hickory Street Square Revitalization Project seeks to transform a central public space in Sidney, Nebraska into a dynamic, community-oriented area that supports local events, economic activity, and cultural heritage. The project addresses six core objectives: 1) convertible street design, 2) parking lot reconfiguration, 3) public amenities, 4) event flexibility, 5) lighting and signage, and 6) old electric plant renovation. A conceptual design was developed by the design team (S.T.E.E.L. Sentinel Solutions) by synthesizing the most effective features of three preliminary alternatives, shaped further through community feedback and evolving project constraints. The final project design minimizes disruption to existing activity …

Stop Design: Rethinking The Approach To Public Transit's Architecture, Elizabeth M. Nielsen

Architecture Masters of Science Program: Theses

Public spaces are the foundation of our social health and wellbeing, but are often designed without considering the needs of the public, creating spaces that people do not feel encouraged to use. Just as public space design as a whole often falls short of serving the public, the same can be said for a subset of public space design, public transit stops. While they are public spaces created for the purpose of waiting, their design rarely reflects this.

Well-designed public transit stops are capable of both maintaining existing ridership and drawing in new riders. Most commonly, this design occurs at …

Intermediate Stage Densification Kinetics Of High-Entropy Ceramics During Spark Plasma Sintering, Steven M. Smith, William G. Fahrenholtz, Greg E. Hilmas, Stefano Curtarolo

Materials Science and Engineering Faculty Research & Creative Works

The intermediate stage densification kinetics of (Hf, Nb, Ta, Ti, Zr) B2 and (Hf, Nb, Ta, Ti, Zr) C were studied using a Coble creep rate model. (Hf, Nb, Ta, Ti, Zr) B2 was synthesized by boro/carbothermal reduction and (Hf, Nb, Ta, Ti, Zr) C was synthesized by carbothermal reduction. Both ceramics were densified by spark plasma sintering at 1700–1850°C. The activation energies for densification were 575 ± 53 kJ/mol for the high-entropy boride and 646 ± 4 kJ/mol for the high-entropy carbide. The densification mechanisms were grain boundary diffusion for the high-entropy boride and lattice diffusion for the high-entropy …

Tumor-Specific Surface Marker–Independent Targeting Of Tumors Through Nanotechnology And Bioorthogonal Glycochemistry, Hyesun Hyun, Bo Sun, Mostafa Yazdimamaghani, Albert Wielgus, Yue Wang, Stephanie Ann Montgomery, Tian Zhang, Jianjun Cheng, Jonathan S. Serody, Andrew Z. Wang

Chemical and Biochemical Engineering Faculty Research & Creative Works

Biological targeting is crucial for effective cancer treatment with reduced toxicity but is limited by the availability of tumor surface markers. To overcome this, we developed a nanoparticle-based (NP-based), tumor-specific surface marker–independent (TRACER) targeting approach. Utilizing the unique biodistribution properties of NPs, we encapsulated Ac4ManNAz (Maz) to selectively label tumors with azide-reactive groups. Surprisingly, while NP-delivered Maz was cleared by the liver, it did not label macrophages, potentially reducing off-target effects. To exploit this tumor-specific labeling, we functionalized anti–4-1BB Abs with dibenzo cyclooctyne to target azide-labeled tumor cells and activate the immune response. In syngeneic B16F10 melanoma and orthotopic 4T1 …

Additive Manufacturing Of Zinc-Based Biomaterials: Fabrication, Performance And Property Evaluation, S. Bandekian, M. Zolfaghari Baghbaderani, J. Drelich, S. Sharif, A.F. Ismail, H. R. Bakhsheshi-Rad

Michigan Tech Publications

The use of zinc and its alloys in additive manufacturing has become an important focus in interventional medical field. This is because zinc as an implant is naturally degradable, has solid mechanical characteristics, and is biocompatible. Biodegradable Zn-based metals made with additive manufacturing offer significant advantages in creating personalized medical implants. This review aims to provide an overview of different types of additive manufacturing methods and processes that can be used in the fabrication of Zn-based medical implants. It offers a comprehensive understanding of additive-manufactured Zn-based alloys for interventional surgeries. The study also summarizes the relationships between degradation properties, mechanical …

Experimental Study Of Process Parameter Effects On Internal Defects In Titanium Coaxial Wire-Based Laser Metal Deposition, Remy Mathenia, Braden Mclain, Todd Sparks, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Wire-based laser metal deposition is an additive manufacturing process that can be used in the efficient manufacturing of complex structures. This paper utilizes a three-beam coaxial laser wire system to explore the effect of process parameters on the resultant deposition density. The reduction in or elimination of defects is important to the mechanical properties of the additively manufactured material and the widespread adoption of additive manufacturing processes. In this work, two-bead-wide walls were deposited under varying experimental conditions, including the traverse feed rate and workpiece illumination proportion. A method for calculating the bead pitch and layer height increment based on …

Performance Evaluation Of Highly Modified Asphalt-Based Binders In High Friction Surface Treatment: Comparative Study With Epoxy-Based System, Alireza Roshan, Magdy Abdelrahman, Mohyeldin Ragab

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

High Friction Surface Treatments (HFSTs) are frequently used to increase skid resistance and reduce collisions, particularly in crash-prone zones, including horizontal curves and intersections. Epoxy-based binders traditionally have been the sole option for HFSTs, but their drawbacks, such as high costs and compatibility challenges, have led to the search for substitute binders, including asphalt-based options. This study investigates the comparative performance of highly modified asphalt-based binders, including polymer-modified, mastic, and highly modified emulsions, in HFST applications using two aggregate types, Calcined Bauxite (CB) and Rhyolite with different gradations, with an emphasis on their frictional properties, durability, and resistance to polishing. …

On The Optimal Design Of Coreless Afpm Machines With Halbach Array Rotors For Electric Aircraft Propulsion, Matin Vatani, John F. Eastham, Xiaoze Pei, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper provides a comprehensive analysis of the winding factor and winding harmonic distribution in coreless stator axial flux permanent magnet (AFPM) machines. The topology of this type of machine and its similarities to conventional cored AFPM machines are discussed. Popular pole/coil number combinations in coreless stator AFPM machines are identified and analyzed in detail. It is demonstrated that the winding factor in these machines varies with radius and can be expressed as the product of the conductor distribution factor, pitch factor, and coil group factor. The formulas for each factor are derived and presented in multiple forms based on …

Hybrid Fea And Meta-Modeling For De Optimization Of A Highly Saturated Spoke Ipm, Oluwaseun A. Badewa, Marcelo Silva, Rosemary E. Alden, Pedram Asef, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper introduces a novel approach for high performance electric motor design that combines machine learning (ML)-based meta-modeling with a differential evolution (DE) optimization algorithm. The method leverages finite element analysis (FEA) results to train the ML meta-model, enabling efficient design optimization for high-power density cored machines, such as spoke interior permanent magnet motors (IPM), which exhibit complex nonlinearities and saturation effects. This hybrid ML-DE framework seeks to provide an alternative for physics-based electric motor design and optimization, offering significant reductions in computational effort while maintaining accuracy. The meta-model’s accuracy in capturing the nonlinear relationships between design parameters, core losses, …

Optimal Design Of Coreless Axial Flux Pm Machines Using A Hybrid Machine Learning And Differential Evolution Method, Matin Vatani, David R. Stewart, Pedram Asef, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Coreless stator axial flux permanent magnet (AFPM) machines require computationally intensive three dimensional finite element analysis (FEA) for accurate performance evaluation, making optimization time-consuming and impractical for large-scale design studies. This paper presents a hybrid optimization approach that integrates differential evolution (DE) with artificial neural networks (ANNs) to accelerate the optimization of coreless AFPM machines. In this method, DE driven FEA simulations generate a dataset used to train an ANN surrogate model, significantly reducing reliance on direct FEA computations. The effectiveness of this approach is demonstrated through a multi-objective DE optimization, where the ANN’s predictions are validated against FEA results. …

Winding Factors And Harmonics Of Coreless Axial Flux Pm Machines, Matin Vatani, John F. Eastham, Xiaoze Pei, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper provides a comprehensive analysis of the winding factor and winding harmonic distribution in coreless stator axial flux permanent magnet (AFPM) machines. The topology of this type of machine and its similarities to conventional cored AFPM machines are discussed. Popular pole/coil number combinations in coreless stator AFPM machines are identified and analyzed in detail. It is demonstrated that the winding factor in these machines varies with radius and can be expressed as the product of the conductor distribution factor, pitch factor, and coil group factor. The formulas for each factor are derived and presented in multiple forms based on …

Graphics Processing Unit-Enabled Path Planning Based On Global Evolutionary Dynamic Programming And Local Genetic Algorithm Optimization, Junlin Ou, Ge Song, Yi Wang

Faculty Publications

This paper presents a novel path planning method for real-time robotic path planning in a dynamic environment involving moving obstacles. It combines on a holistic platform a global approach to rapidly generate initial paths of prominent diversity and a heuristic approach to enable local path refinement for enhanced computational efficiency, exploration, and robustness. The global approach innovates a formulation that treats a path planning problem with a visibility graph as a Markov decision process and decomposes the process into many subproblems. A new evolutionary dynamic programming approach (EDP) is proposed to solve these subproblems in an iterative manner using …

Development And Characterization Of Quercetin-Loaded Microparticles Via Spray Drying For Pulmonary Drug Delivery Applications, Daniel Jose Perez Torres, Samantha Ann Meenach

Senior Honors Projects

Pulmonary inflammation is associated with respiratory

disorders such as pulmonary arterial hypertension and chronic

obstructive pulmonary disease. A hallmark of these diseases is

an increase in reactive oxygen species in the body, leading to

further inflammation and acerbation of these diseases.

Fortunately, a class of natural products termed plant-derived

flavonoids have been found to alleviate inflammation and

oxidative stress in lung tissue, making them promising

therapeutic agents for the treatment of pulmonary diseases.

Flavonoids are accessible and cost-effective, with quercetin

being one of the most commonly consumed flavonoids in the

human diet. Despite its therapeutic potential, the efficacy of

quercetin …

Robust Distributed Learning Against Both Distributional Shifts And Byzantine Attacks, Guanqiang Zhou, Ping Xu, Yue Wang, Zhi Tian

Electrical and Computer Engineering Faculty Publications

In distributed learning systems, robustness threat may arise from two major sources. On the one hand, due to distributional shifts between training data and test data, the trained model could exhibit poor out-of-sample performance. On the other hand, a portion of working nodes might be subject to Byzantine attacks, which could invalidate the learning result. In this article, we propose a new research direction that jointly considers distributional shifts and Byzantine attacks. We illuminate the major challenges in addressing these two issues simultaneously. Accordingly, we design a new algorithm that equips distributed learning with both distributional robustness and Byzantine robustness. …

From In-The-Head To In-The-World: Frameworks For Understanding And Applying Computational Thinking, Justin Olmanson, Gretchen K. Larsen, Azadeh Hassani

Department of Teaching, Learning, and Teacher Education: Faculty Publications

In the five decades since Papert coined the term Computational Thinking (CT), it has become a core framework for thinking about learning, problem-solving, design, and creativity. Although CT is most commonly, and initially, associated with the cognitive orientations involved in coding and learning to code, it also includes situated and critical processes related to computational problem solving. Herein we unpack ways researchers in different fields and points in time have organized CT. We include creative coding as a uniquely generative lens for rethinking CT, outlining its potential as an expressive, constructionist, and culturally situated practice. In doing so, we explore …

Sonochemically Synthesized Zno Nanowires (Nws)-Based Sensor For Non-Invasive Glucose Detection In Sweat, G. M. Mehedi Hossain, Ahmed Hasnain Jalal, Hasina Huq, Nazmul Islam, Karen Lozano, Nezih Pala, Fahmida Alam

Electrical and Computer Engineering Faculty Publications

Glucose is a crucial metabolic marker, providing critical insights into energy regulation and insulin sensitivity, making its monitoring essential for managing diabetes and overall metabolic health. In this context, flexible biosensors have gained considerable attention for their potential to enable real-time and non-invasive glucose monitoring. One promising advancement in this domain is using Zinc-Oxide (ZnO) nanostructures through sonochemical synthesis. ZnO has a wide bandgap of ∼3.37 eV and a large binding energy of 60 meV. This research focuses on ZnO-Nanowires' growth for the first time on a flexible polymer substrate. The average length and diameter of the nanowires are 2.5µm …

Automated Identification Of Clinically Meaningful Biomechanical Phenotypes In Cerebral Palsy Through Multicenter Gait Data, Adam Graf, Joseph Krzak, Karen M. Kruger, Jon Davids, Ryan Smith, Brandon Steinlein, Anita Bagley

Biomedical Engineering Faculty Research and Publications

Background

Cerebral palsy is the most prevalent motor disability in childhood, encompassing various movement disorders that affect walking. Researchers have described gait patterns in cerebral palsy, but these are often subjective and based on clinician experience. This study introduces an automated approach to objectively identify clinically meaningful biomechanical phenotypes in cerebral palsy and test it on multicenter gait data. Utilizing instrumented gait analysis, this research aims to improve treatment strategies for gait dysfunction. This study addresses whether classification algorithms can objectively identify clinically meaningful gait patterns and if severe gait deviations are more frequent in advanced forms of cerebral palsy. …

The Trials And Tribulations Of Building An Ebike From Recycled Parts, Olivia Conrady

Senior Honors Projects

The United States is far from being “walkable” in most suburban areas. Though public transportation has grown in its infrastructure in some large cities, it is far from sufficient. As a result of this, millions of people drive their cars every single day -- a practice that is unsustainable and becoming an increasingly evident issue. One possible solution that has become popular is the use of electric bicycles, since they are less physically taxing than a normal bike and allow for quicker transport. Though electric bicycles have been on the rise, they are still well outside of many people’s budget, …

Engineering Affinity Of Yth Protein To M6a-Rna, Katelynn E. Horvath

Honors Scholar Theses

Engineered RNA-binding proteins (RBPs) show promise for diverse applications in research and therapeutic development. Modulating the interaction between YTH-domain containing proteins and methylated RNA ligands could result in a high affinity, highly specific binding protein for the advancement of research tools in neurodegenerative disease. N6-methyladenosine (m6A) modified RNA contributes to stress granule formation that promotes neurotoxicity in neurodegenerative disease, with concentrations of m6A-RNA increased fivefold in Alzheimer’s Disease. Further affinity maturation of the YTH-m6A interaction through directed evolution of the YTH domain could produce a novel protein with increased affinity better suited for the development of biological detection tools or …