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Ce 495 - 102: Civil Engr Design Ii, Babu Veeragowda

Civil and Environmental Engineering Syllabi

No abstract provided.

Ene 262 - 004, Hm2: Intro To Environmental Engr, Paul Schorr

Civil and Environmental Engineering Syllabi

No abstract provided.

Ene 465 - 101: Sustainable Env Infrastructure, William Pennock

Civil and Environmental Engineering Syllabi

No abstract provided.

Mech 235 - 002,004: Eng Mech: Statics, Sunil Saigal

Civil and Environmental Engineering Syllabi

No abstract provided.

Mech 236 - 002, 004, 006, 008, Hm2: Dynamics, Yuan Ding

Civil and Environmental Engineering Syllabi

No abstract provided.

Mech 234 - 002, 004: Engineering Mechanics: Statics, Geraldine Milano

Civil and Environmental Engineering Syllabi

No abstract provided.

Mech 237 - 002, 004, 014, 016, 106, 108: Strength Of Materials, Eduardo Castro

Civil and Environmental Engineering Syllabi

No abstract provided.

Mech 237 - 010, 012, 110, 112: Strength Of Materials, Geraldine Milano

Civil and Environmental Engineering Syllabi

No abstract provided.

Mech 320 - 102: Statics & Mech Of Materl, Mohamad Saadeghvaziri

Civil and Environmental Engineering Syllabi

No abstract provided.

Ce 341 - 002: Soil Mechanics, Andrew Ciancia

Civil and Environmental Engineering Syllabi

No abstract provided.

Ce 350 - Hm2: Transportation Engr - Honors, Branislav Dimitrijevic

Civil and Environmental Engineering Syllabi

No abstract provided.

Ce 320a - 102, 104, 108: Hydraulics Laboratory, Thomas Olenik

Civil and Environmental Engineering Syllabi

No abstract provided.

Ce 431 - 002: Contruction Materials Lab, Walter Konon

Civil and Environmental Engineering Syllabi

No abstract provided.

Virtual Fixtures For Teleoperated Robots For The Visually Impaired, Vishwaak Chandran Thamaraiselvan

Computer Science and Engineering Theses - Archive

This paper presents our preliminary study on enabling individuals with visual impairments to safely operate mobile robots and vehicles. To achieve this, we developed a teleoperation with accessibility at its core. The system incorporates features that enhance usability and situational awareness, including assistive control based on artificial potential fields to prevent collisions and ensure smooth navigation. It also provides multimodal feedback through (a) haptic vibrations on the gamepad controller, which convey the proximity of nearby objects detected by the robot’s laser sensor, and (b) color-coded overlays that differentiate paths, obstacles, and people through semantic segmentation performed by a deep neural …

Phase-Field Modeling Of A Protective Layer For The Suppression Of Dendrites In Metallic Anode-Based Rechargeable Batteries, Bharat R. Pant

Material Science and Engineering Dissertations - Archive

Metallic anodes, such as Lithium (Li) and Zinc (Zn), offer promise for the development of high-capacity rechargeable batteries. However, metallic anode-based batteries suffer from severe dendrite growth during the plating process, which poses safety hazards and accelerates capacity degradation. Experimental studies suggest that using a protective coating on the anode surface could potentially mitigate dendrite growth and prolong the battery’s life. However, there are limited theoretical studies on the inhibition effect of a protective layer on dendrite growth. Herein, we developed a phase-field model to simulate the impact of a protective layer on the plating and stripping cycle for Li …

Intelligent Microfluidic Systems For Precision Manipulation And Real-Time Recognition Via Dielectrophoresis And Deep Learning, Negar Danesh

Mechanical and Aerospace Engineering Dissertations - Archive

This dissertation introduces intelligent microfluidic platforms by combining advanced DEP-based manipulation with real-time visual feedback. A DEP device featuring circular corral traps and dual-plane electrodes enables precise submicron particle trapping, high-resolution particle separation, and cell-particle co-assembly. Simulations and experiments confirm enhanced electric field control and stable confinement. To enable adaptive operation in EWOD systems, a deep learning model (U-Net) was developed for real-time droplet meniscus segmentation. The model achieved 98% accuracy and remained robust under noisy, low-contrast conditions. A live video pipeline was implemented, enabling consistent frame-by-frame feedback for closed-loop control. Together, these innovations establish a foundation for autonomous, high-performance …

Deep Neural Network Models For Heatsink Performance Prediction And Optimization In Single Phase Immersion Cooling: Framework For Future Design Tools And Digital Twin Integration, Braxton J. Smith

Mechanical and Aerospace Engineering Theses - Archive

The rapidly rising computational power of modern computing components combined with the advanced packaging techniques being implemented has resulted in exponentially increasing thermal design powers (TDP) from CPUs and GPUs. Traditional air-cooling methods are approaching their effective cooling limits for many of these components, requiring lower supply air temperatures, higher supply air flowrates, and much larger heatsinks to remain feasible. Transitioning from air-cooling to single-phase immersion cooling offers numerous benefits in thermal performance, data-center size reduction, and energy efficiency. To leverage the merits of immersion cooling, the performance of a given heatsink must be predicted and optimized for best performance …

Strategies For Enhanced Meg Data Analysis In Clinical Practice And Emerging Frontiers, Pegah Askari

Bioengineering Dissertations - Archive

Epilepsy and dementia are debilitating neurological disorders that pose substantial challenges for patients, caregivers, and healthcare systems. Advances in magnetoencephalography (MEG) and signal processing offer new opportunities to improve diagnostic accuracy, surgical planning, and treatment monitoring. This dissertation presents a unified body of work comprising artifact removal, automated event detection, and deep learning-based biomarker discovery. These approaches collectively enhance the clinical utility of MEG for diverse patient populations.

The first study addresses a significant technical obstacle in the management of drug-resistant epilepsy. Patients receiving responsive neurostimulation (RNS) have historically been excluded from MEG as the data is contaminated by device-related …

Functional Enhancement Of Pancreatic Islets Through Photobiomodulation For Potential Diabetes Therapeutics, Kelli Fowlds

Bioengineering Dissertations - Archive

Islet transplantation is a potential therapeutic route for type 1 diabetic patients facing chronic ketoacidosis and/or hypoglycemia unable to be properly regulated with standard insulin administration. However, successful engraftment is hampered by a multitude of factors. Harvested islets face rapid, substantial degradation due to hypoxia and nutrient depletion once isolated. Transplanted islets are additionally susceptible to the instant blood-mediated inflammatory reaction (IBMIR). This combination of factors leads to more than half of transplanted islets failing to engraft post-surgery. Many areas of research are dedicated to investigating alternative approaches or supplemental treatments to improve the success rate of engraftment and insulin …

Novel Electrophysiological Biomarkers In Pediatric Drug Resistant Epilepsy And Genetic Epilepsy Syndromes, Sakar Rijal

Bioengineering Dissertations - Archive

Pediatric epilepsies, particularly those that are drug-resistant or genetically driven, represent some of the most complex neurological disorders encountered in childhood. Central to their pathophysiology is a disruption in the delicate balance between cortical excitation and inhibition (E/I), often resulting from impaired GABAergic interneuron function. This imbalance manifests as aberrant network dynamics and altered neural oscillations, giving rise to seizures and long-term cognitive impairments. In this thesis, we developed a translational framework to identify electrophysiological biomarkers that (i) assess cortical E/I imbalance and (ii) map epileptogenic zones, with the aim of enhancing diagnosis, guiding surgical planning, and informing therapeutic monitoring …

Vision Of Nuclear Power Deployment In Latin America And The Caribbean: A Focus On Small Modular Reactors And The Regional Experience Of Central Argentina De Elementos Modulares, Alejandra Loreto Alfaro, Florencia Rentería, Camila Araujo

International Journal of Nuclear Security

Increasing the number of nuclear power reactors in the Latin American and Caribbean region presents technical, financial, regulatory, and environmental challenges. Focused on fostering economic stability, growth, and human capacity development, the deployment of small modular reactors (SMRs) emerges as a key aspect in the region’s energy landscape. The emergence of SMRs represents an opportunity for multidisciplinary cooperation among different sectors. To comprehensively address the challenges related to the protection of nuclear facilities in the region, the Tlatelolco Treaty and the Non-Proliferation Treaty should be strengthened as legally binding instruments to enforce the safety and safeguarding principles integral to the …

Exploring Large Language Models For Summarizing And Interpreting An Online Brain Tumor Support Forum, Christy Muasher-Kerwin, M. Courtney Hughes, Michelle L. Foster, Ibrahiim Al Azher, Hamed Alhoori

Faculty Articles, Papers, and Other Scholarship

Objective

Methods

Quantifying Multidimensional Effects Of Physicochemical Parameters On Pfas Adsorption Using A Hybrid Response Surface Methodology-Machine Learning Approach, Harsh V. Patel, Jazmin Green, John Park, Stephanie Luster-Teasley Pass, Renzun Zhao

Engineering Management & Systems Engineering Faculty Publications

Per- and polyfluoroalkyl substances (PFAS) contamination has posed a significant environmental and public health challenge due to their ubiquitous nature. Adsorption has emerged as a promising remediation technique, yet optimizing adsorption efficiency remains complex due to the diverse physicochemical properties of PFAS and the wide range of adsorbent materials. Traditional modeling approaches, such as response surface methodology (RSM), struggled to capture nonlinear interactions, while standalone machine learning (ML) models required extensive datasets. This study addressed these limitations by developing hybrid RSM-ML models to improve the prediction and optimization of PFAS adsorption. A comprehensive dataset was constructed using experimental adsorption data, …

Sustainable Aviation Fuel Production From Plastic Waste On Bifunctional Catalysts, Kamryn Culp

Williams Honors College, Honors Research Projects

Catalytic hydrocracking was studied as a chemical recycling method for converting mixed plastic polypropylene (PP) and polyvinyl chloride (PVC) waste into sustainable aviation fuel-range hydrocarbons. Addressing both plastic pollution and aviation-related CO₂ emissions, bifunctional Ni- and Pt-based catalysts supported on Al₂O₃ and TiO₂ were evaluated under 30 bar hydrogen pressure at 250 °C. The inclusion of PVC, often regarded as a catalyst poison due to chlorine content, was examined at 1 wt% and 5 wt% to assess catalyst tolerance to it and resulted performance. Reaction rates and product selectivity were analyzed using gas chromatography. Results show that Ni/TiO₂ outperformed other …

Automatic Hole Saw Testing For Mk Morse, Jason Watson, Justin Zapotoczny

Williams Honors College, Honors Research Projects

M.K. Morse has a hole saw tester they use for their hole saw product line. The tester currently requires constant operator attention for a process that could be automated. The goal of this project is to create a new hole saw tester that can run without the need for an operator's complete attention and give reliable data for the hole saws.

Individual Design Task Final Report Security Design, Ciarrah Bell

Honors Academy

"The Environmental Services Campus project is a comprehensive development designed to support the City of Springfield’s Environmental Services operations, with a focus on functionality, sustainability, and safety. The campus includes administrative office space, staff parking, a maintenance vehicle garage, and educational facilities aimed at community outreach. A component of the project is establishing site-wide security that not only protects personnel and assets but also integrates seamlessly with the architectural and environmental goals of the facility.

The primary focus of the Security IDT is the development and implementation of a comprehensive security strategy for the entire site. This includes designing and …

Understanding The Usefulness Of Self-Escape Technologies In Underground Mining: Perspectives Of Metal/Nonmetal Miners, Eugene A. Gyawu, Kwame Awuah-Offei, D. A. Baker

Mining Engineering Faculty Research & Creative Works

Research on mine self-escape often focuses on coal mining, while perspectives from underground metal/nonmetal miners remain understudied despite their distinct emergency response challenges and unique operating environments. Using a scenario-based survey approach, this study evaluated underground metal/nonmetal miners' perceptions of the usefulness of 18 hypothetical self-escape interventions and how these perceptions are influenced by worker characteristics. Employment type was the strongest predictor of usefulness ratings, with hourly employees rating several self-escape interventions significantly higher than salaried employees, including those related to improving self-contained self-rescuers (SCSRs) and tethered guidance systems. The data suggested potential trends where perceived usefulness increased with more …

An Intelligent Robotic System For Multi-Sensory Cognitive Fatigue Detection To Assist Persons With Paralysis In Activities Of Daily Living, Enamul Karim

Computer Science and Engineering Dissertations - Archive

Assistive robotics is a promising area for improving the quality of life of people with paralysis, specifically through assistance in Activities of Daily Living (ADLs). Current state-of-the-art assistive robotic systems do not have the capability to dynamically modulate their functionality according to the cognitive fatigue level of the user, which can negatively impact their effectiveness and usability in real-life settings.

This dissertation explores an adaptive robotic framework that adjusts its behavior depending on the cognitive fatigue level of users. The system operates in three different modes, and switches between Fully Controlled, Semi-Autonomous, and Fully Autonomous modes. The overall goal is …

Signal Analysis Of Calcium Dynamics In Pancreatic Cells, Abhidha Kunwar

2025 Fall Honors Capstones Projects - Archive

Calcium (Ca²⁺) signaling plays a critical role in insulin secretion from pancreatic βcells. Photo-biomodulation (PBM) of red or near-infrared wavelengths is applied to enhance cellular metabolism and Ca²⁺ activity in pancreatic cells. This study aims to rigorously analyze how PBM influences calcium dynamics in pancreatic cells by applying the Fast Fourier Transform (FFT), converting Ca²⁺ spiking patterns to the frequency domain to determine dominant oscillatory behaviors. Using a calcium-binding fluorophore, Ca²⁺ activity was acquired before and after PBM at 810 nm, processed with a machine learning algorithm, and further analyzed in MATLAB using FFT to assess changes in calcium signal …

Medical Ai: Solving Healthcare Challenges And Inspiring Ai Innovation, Xiaowei Yu

Computer Science and Engineering Dissertations - Archive

Artificial Intelligence (AI) is transforming healthcare by enabling large-scale analysis of medical data and integrating multimodal information for more comprehensive diagnostics. I present my work addressing fundamental and challenging problems in developing state-of-the-art AI models for medical data analysis, including multimodal brain data and other medical datasets. Additionally, I design brain-inspired AI models by integrating insights from organizational principles of brain networks. Specifically, my research tackles three critical aspects: (1) AI in Computational Neuroscience, where I design deep learning models for brain network analysis to uncover the organizational principles of brain networks; (2) Brain-Inspired AI, where I integrate superior brain …