Engineering Commons^™

Ai Data Center Dynamic Load Effects On Current Transformer Saturation, Sergio A. Hernandez

Electrical Engineering Theses

AI data centers can produce rapid changes in electrical demand that may influence current transformer performance during faults. This study evaluates the effect of an AI data center transient on CT saturation during single line-to-ground faults using a 400 V, 60 Hz grid connected inverter model in MATLAB/Simulink. The normal condition transient produced a maximum RMS current rate of approximately 211 A/ms, which was used along with the maximum power condition to define fault inception cases. A MATLAB time-domain CT model then swept the fault current DC offset coefficient to determine the minimum offset required for CT saturation. The calculated …

Experimental Thermal Characterization And Comparison Of Direct Liquid Cooling And Air Cooling For A High-Density Gpu Server Thermal Test Vehicle, Oluwagbolahan Esan

Mechanical and Aerospace Engineering Theses

As the power density of artificial intelligence (AI) and high-performance computing (HPC) servers escalates, air cooling is approaching fundamental scaling limits set by air's low convective heat transfer coefficient and rising parasitic fan power. This thesis presents an experimental comparison of direct-to-chip liquid cooling and air cooling for a high-density GPU server, using a Thermal Test Vehicle (TTV) that emulates the device layout and power-density regime of an 8-GPU SXM5-class baseboard (eight emulated GPU blocks and four NVLink Switch modules). The liquid configuration was tested at 8.8 kW (8.0 kW GPU, 800 W switch) across three Coolant Distribution Unit (CDU) …

End-To-End Development And Experimental Validation Of A 1/10-Scale Autonomous Vehicle, Rikkin Pankaj Panchal

Electrical Engineering Theses

Autonomous vehicle development demands vast resources, making scaled down platforms a critical alternative for solving core algorithmic challenges. The primary contribution of this thesis is the end to end development and validation of a complete real time autonomous driving pipeline deployed on a one tenth scale vehicle. To streamline platform development, an AI assisted annotation framework automates dataset generation, significantly reducing manual labor while improving training data quality. The system perception stack features a reinforcement learning guided online multi camera calibration framework that enables adaptive surround view stitching without the need for offline recalibration. This is paired with robust lane …

Heterogeneous Robots Cooperation Via Multi-Agent Reinforcement Learning, Rehab Uddin Shawon

Graduate Theses/Dissertations

Enabling heterogeneous robots with diverse capabilities, roles, and task responsibilities to coordinate effectively in complex, dynamic environments remains a fundamental challenge in autonomous multi-robot systems. Multi-Agent Reinforcement Learning (MARL) provides a promising framework for decentralized cooperation. However, most existing MARL approaches assume homogeneous agents or fixed single-task settings and suffer significant performance degradation as the number of robot and task types increases. This thesis presents a scalable shared-policy MARL framework that allows heterogeneous robots to learn specialized behaviors for individual, sequential, and collaborative tasks involving temporal and spatial dependencies through a single neural policy. I first embed robot identity directly …

A Taxonomy-Driven Modular Defense Against Non-Canonical Language In Vision-Language-Action Models, Viraj Samson

Electronic Theses and Dissertations

Vision-Language-Action (VLA) models have recently achieved strong performance across manipulation benchmarks, but these benchmarks rely on highly templated instructions on which the models are typically fine-tuned, leaving their behavior under realistic language-side perturbation unclear. It remains an open question whether the linguistic flexibility inherited from vision-language pretraining survives this fine-tuning, or whether the resulting policies become narrowly tuned to benchmark phrasing and brittle to the intent-preserving language variation that real users naturally produce. We address this gap with a systematic study of VLA robustness under non-canonical instructions, comprising three components: a structured taxonomy of intent-preserving variations spanning linguistic, orthographic, and …

Data-Driven Optimization Of Memory Effects And Critical Components In Cascading Failure Interaction Networks, Md Farhan Tanvir

Electronic Theses and Dissertations

Cascading failures are a major concern for modern power systems‚ where a small failure can cascade through the network to create a large blackout. Because such an event could have catastrophic economic and social costs it is important to understand cascading failures‚ how to model them‚ and the possibility of reducing them. In this thesis‚ we develop a data-driven framework based on actual utility outage data to model and reduce cascading failures. The proposed methodology is based on generation-dependent interaction models and in this study interaction matrices obtained from historical outage events are used to describe the interaction between generations. …

Computational Modeling Of Biophysical Transport: Respiratory Drug Delivery And Tissue-Level Physics, Md Tariqul Hossain

Electronic Theses and Dissertations

The nasopharynx, the upper part of the pharynx located at the back of the nose serves as a critical hotspot for initial respiratory infections via inhaled transmission, largely due to the presence of specific surface receptors that pathogens can exploit for cell invasion, combined with a relatively sparse local mucociliary substrate. To enhance the therapeutic efficacy against certain pathogens, such as the SARS and Influenza viruses, it is therefore essential to improve the targeted delivery of drugs to the nasopharynx. This study explores the use of intranasal sprays as a method for drug administration and models the transport of sprayed …

Numerical Investigation Of Injector Location And Equivalence Ratio In A Flame‐Holder Cavity Scramjet, Matthew Sorenson

Electronic Theses and Dissertations

This thesis presents a CFD-based parametric study of injector location and fuel rate in an ethylene-fueled flame-holder cavity scramjet using STAR-CCM+. Simulations are performed for three injector locations (x/D = 18, 36, and 54) and nine equivalence ratios spanning from ϕ = 0.2 to 1.0 in 0.1 increments. The study aims to determine how injector placement and fueling level alter scramjet performance across a broad operating sweep. The results show a clear regime change between ϕ = 0.2 and ϕ ≥ 0.3. At ϕ = 0.2, combustor behavior is weakly sensitive to injector location compared to the higher-fueling cases. For …

Wearable Biosensors For Continuous Monitoring Of Chronic Kidney Disease: Materials, Biofluids, And Digital Health Integration, Anupamaa Sivasubramanian, Shankara Narayanan, Gymama Slaughter

Center for Bioelectronics Publications

Chronic kidney disease (CKD) is a progressive and irreversible disorder affecting over 850 million individuals globally and is associated with significant morbidity, mortality, and healthcare burden. Conventional diagnostic approaches rely on intermittent laboratory measurements, including serum creatinine, estimated glomerular filtration rate (eGFR), and urinary albumin, which provide limited temporal resolution and fail to capture dynamic physiological changes. Recent advances in wearable biosensing technologies offer new opportunities for continuous, non-invasive monitoring of biochemical and physiological markers relevant to renal function. This review provides a comprehensive analysis of wearable biosensors for CKD monitoring, focusing on sensing mechanisms (electrochemical, optical, and field-effect transistor), …

Modulation Of Prussian Blue Redox Signaling By Molecular Imprinting For Reagent-Free Electrochemical Detection Of Emtricitabine, Abdellatif Ait Lahcen, Gymama Slaughter

Center for Bioelectronics Publications

Reagent-free electrochemical sensors offer significant benefits for rapid, affordable point-of-care drug testing. In this study, we introduce a novel, reagent-free electrochemical sensor based on a molecularly imprinted polymer (MIP) specifically designed for the selective detection of Emtricitabine (FTC), a common antiretroviral used in HIV therapy. The sensor uses laser-induced graphene (LIG) electrodes, renowned for their high conductivity and porosity, ideal for electrochemical sensing. To enable reagent-free operation, the LIG surface was electrochemically coated with Prussian Blue, serving as a redox-active layer. Next, an MIP-PPy film was electropolymerized onto the Prussian Blue surface in the presence of FTC as a template, …

Ion-Imprinted Polymer-Based Sensors For Toxic Metal-Ion Detection In Water: Coordination Chemistry, Transduction Strategies, And Environmental Applications, Ghita Yammouri, Gymama Slaughter

Center for Bioelectronics Publications

Toxic metal contamination in aquatic environments remains a persistent threat to human health and ecosystems. Yet, the high cost, infrastructure demands, and centralized nature of conventional analytical methods constrain routine monitoring. Ion-imprinted polymers (IIPs), a subclass of molecularly imprinted polymers, have emerged as promising synthetic recognition materials for metal-ion sensing because they generate coordination-defined binding sites with high selectivity, chemical stability, low cost, and reusability. This review summarizes recent advances in Ion-imprinted polymer (IIP)-based sensing technologies for toxic metal-ion detection in water from 2016 to 2026. It examines the fundamental recognition chemistry of IIPs, major synthesis strategies used to generate …

Effect Of Ionic Strength On Gelation Time And Strength Of Amps-Based Polymer Gels, Maryam Sharifi Paroushi, Xuyang Tian, Baojun Bai, Thomas P. Schuman, Yin Zhang, Mingzhen Wei

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Polymer gel treatment has been widely applied for improving sweep efficiency and controlling excessive water and gas production. Their performance depends on gelation time and final gel strength. In most studies, brine salinity is used to describe the effect of formation water on gel behavior. However, changing salinity also changes ionic strength and ion composition at the same time. Because of this coupling, it is difficult to identify the mechanisms controlling gelation, which has led to inconsistent trends in the literature. Increasing salinity has been reported to either slow or accelerate gelation and to weaken or strengthen gels depending on …

Cross-Linking Peg Microgels With Mesoporous Organosilica Nanoparticles To Engineer Microporous Annealed Particle Scaffold Properties, Jonathan M. Zuidema, Alessandro Ajo, Marco Carofiglio, Luisa De Cola

Mechanical Engineering Faculty Publications

Microporous annealed particle (MAP) scaffolds composed of cross-linked microgels are emerging as important biomaterials due to their modular design, high porosity, and large surface area, which allow for highly tailored properties, cellular infiltration, nutrient and waste exchange, and improved drug release characteristics. To further expand on these technologies and enhance their modular design, thiolated mesoporous organosilica nanoparticles (ssMSN-SH), which degrade in response to glutathione, were first cross-linked inside of 4-arm poly(ethylene glycol) maleimide microgels. The microgel size, rheological properties, and payload release characteristics were determined. Hierarchical MAP scaffolds were then created by cross-linking 4-arm poly(ethylene glycol) maleimide microgels with ssMSN-SH. …

Effects Of Matched Freespace And Wall Damping On Stiffness Perception, Madeleine Toland, M Bourgeois, Emma Treadway

Engineering Faculty Research

Stiffness perception has previously been shown to be influenced by damping. This work addresses open questions about what damping conditions are best for enabling classification of virtual walls by their stiffness. Through a forced-choice classification experiment with 12 participants, we found that the highest mean classification performance (in terms of both information transfer and percent correct responses) occurred when freespace damping matched wall damping, rather than being higher or lower. However, statistically significant differences did not appear between the closest damping values employed, suggesting that the effects do not become pronounced until the damping is quite mismatched.

Work In Progress: The Impact Of Classroom Interventions On Student Success And Retention In Electric Circuits, Cherian Mathews

All Faculty Articles - School of Engineering and Computer Science

University of the Pacific has embarked on a university-wide endeavor to improve student success and retention. This effort involves academic coaches being placed in each unit, early grade reporting in the fifth week of the semester, follow-ups by faculty advisors and academic coaches for struggling students, and documentation of interactions with such students in the university CRM system. These follow-ups with students typically involve conversations to explore factors contributing to poor performance (e.g., health issues, excessive work hours, study skills), suggesting approaches to improve performance, and making referrals to care teams and supplemental instruction. Despite all these efforts, DFW rates …

Ai For Life Sciences: From Geometric Protein Modeling To Multimodal Drug Design, Feng Jiang

Computer Science and Engineering Dissertations

Predicting biomolecular interactions, from immune recognition to drug–target binding, is a central problem in the life sciences and computational drug discovery. Deep learning has advanced this area, yet three challenges persist: the topology of large, highly imbalanced interaction networks; structural noise in computationally predicted protein models; and the integration of multimodal information such as functional text and taxonomic annotations. This dissertation develops a coherent set of models spanning immune complex prediction and small-molecule drug design: graph learning that addresses network topology and severe class imbalance; a noise-tolerant method that fuses predicted structures with evolutionary sequence features; and multimodal representation learning …

Navigating The Intersection Of Faa Grant Assurances And Environmental Regulations: Assessing Impacts On Airport Sustainability Efforts, Chad D. Richards

Senior Honors Theses and Projects

Airports in the United States operate within a very complicated regulatory environment that is shaped by federal aviation policy, environmental and state laws, and promises made to the federal government through sponsor assurances, also known as grant assurances. As environmental concerns surrounding aviation continuously grow, airports have been increasingly implementing sustainability initiatives aimed at reducing emissions and improving energy efficiency. Implementing these initiatives is often influenced by regulatory frameworks governing airport operations and infrastructure development. The goal is to examine how federal regulatory structures influence sustainability initiatives at U.S. airports by using a qualitative case study approach to examine sustainability …

Impact Of In-Cabin Human Machine Interface Designs On Passenger Trust In Urban Air Mobility, Ricole A. Johnson, Erika E. Gallegos

Journal of Aviation/Aerospace Education & Research

Urban Air Mobility (UAM) presents a promising solution for alleviating urban traffic congestion and enhancing transportation efficiency. However, the widespread acceptance of UAM, particularly sustained ridership of autonomous passenger air vehicles (PAVs), is contingent upon addressing critical human factors for building passenger trust, especially in the absence of a human pilot. This paper evaluates how different in-cabin human-machine interface (HMI) designs affect passenger trust in the aircraft and in-cabin display, situation awareness, and pilot preferences. Forty participants, equally split between early and late technology adopters, completed two simulated flights: a baseline flight with no HMI and a second flight featuring …

The Role Of User Experience In Virtual Reality Flight Training: A Comparison With Pc-Based Simulation, Tianxin Zhang, Christina M. Frederick, Barbara Chaparro

Journal of Aviation/Aerospace Education & Research

The current project explores how user experience (UX) in virtual reality (VR) flight simulation influences both cognitive learning outcomes and procedural skill acquisition when compared to traditional desktop-based simulation.. Using a quasi-transfer of training design, 48 student pilots were randomly assigned to VR, Desktop, or Control groups and trained on the Chandelle maneuver. UX was measured with the User Experience Questionnaire (UEQ), while training effectiveness was evaluated through a post-training knowledge test and recorded maneuver performance on a high-fidelity flight training device. Results indicated that the VR group reported significantly higher UX scores in Attractiveness, Stimulation, and Novelty, and showed …

Soil Freezing Characteristic Surface For Partially Frozen Soils, Antai Dong, Xiong Zhang, Ming Xiao

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The soil freezing characteristic curve (SFCC), which relates unfrozen water content to temperature, is a fundamental constitutive relationship in frost heave simulations. However, the influence of soil suction, another critical state variable, is often neglected. This study highlights how the SFCC is significantly affected by suction conditions, with unfrozen water content varying markedly between saturated (suction = 0) and completely dried (suction = ∞) conditions at the same subfreezing temperature. Recognizing this limitation, the concept of the soil freezing characteristic surface (SFCS) is proposed to incorporate the impacts of both temperature and suction on unfrozen water content. After that a …

Managing And Accelerating The Circular Economy Transitions Within The Construction Value Chain Using Network Governance And Game Theory Systems Perspectives, Radwa Eissa, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The fragmented nature of the construction industry has hindered its transition toward circular economy (CE) practices. While game theory (GT) has been successfully applied to support the strategic decisions of CE transitions in other sectors, CE-GT models in the construction domain remain extremely limited. This paper addresses two research questions: (1) how are CE network governance activities currently modeled using GT across domains? (2) How can such models be transferred and adapted to solve strategic interactions within the construction value chain in a manner that enables CE practices to emerge as equilibrium outcomes? These questions are driven by the need …

Carbonated Blast-Furnace Slag As Supplementary Cementitious Material: Phase Transition And Effect On Cement Hydration, Gao Deng, Nannan Zhang, Wenyu Liao, Yongjia He, Linnu Lu, Lingyu Chi, Hongyan Ma

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Blast-furnace slag, which contains high levels of CaO (and MgO), holds potential as a feedstock for CO₂ capture and storage. This study investigates the phase transitions occurring during the wet carbonation of ground granulated blast-furnace slag (GGBFS), characterizes the physical and chemical properties of carbonated GGBFS (CS), evaluates its pozzolanic reactivity, and examines the microstructure and performance of cement pastes blended with GGBFS or CS. The findings reveal that aragonite and calcite, the primary carbonation products, precipitate on the surface of GGBFS, hindering its dissolution and thereby reducing both the pozzolanic reactivity and the early strength of cement pastes. …

Localized Air Pollution Impacts From Data Centers In Northern Virginia, Damian Pitt, Ivan Suen, Ellie Plisko

Institute for Sustainable Energy and Environment Publications and Presentations

This report examins the extent of air pollution emissions resulting from the use of backup generators at data centers in Northern Virginia, including both actual current emissions and potential future emissions, and how those emissions totals compare to other sources of air pollution in the Northern Virginia region. It also examines how exposure to data center emissions correlates with demographic characteristics such as race, income, and education.

We while the air pollution emissions from individual data centers is minor, the collective impact from the 100+ such facilities in the Northern Virginia region is significant. Notably, the cumulative emissions exposure in …

Ransomware As Organization: A Comparative Analysis Of Corporate And Criminal Structures In Conti, George Urling

Theses, Dissertations and Capstones

Cybercriminal groups continue to pose major threats to global cybersecurity. One of the most common types of cybercriminal groups are, “Ransomware-as-a-Service (RaaS)" groups, who create and sell ransomware. While research is conducted into the development of ransomware, there is limited reporting on the organizational structure and habits of RaaS groups. In 2022, prominent RaaS group Conti had their chat logs leaked, with the logs ranging from 2020 to 2022. This study seeks to provide a deeper understanding of RaaS group structures by utilizing the Conti leaked logs as a case study. The study, entitled “Ransomware as Organization: A Comparative Analysis …

A Macrocognitive Design Taxonomy For Simulation-Based Training Systems: Bridging Cognitive Theory And Human-Computer Interaction, Jessica M. Johnson

Virginia Digital Maritime Center (VDMC) Faculty Publications

Simulation-based training systems are increasingly deployed to prepare learners for complex, safety-critical, and dynamic work environments. While advances in computing have enabled immersive and data-rich simulations, many systems remain optimized for procedural accuracy and surface-level task performance rather than the macrocognitive processes that underpin adaptive expertise. Macrocognition encompasses higher-order cognitive processes that are essential for performance transfer beyond controlled training conditions. When these processes are insufficiently supported, training systems risk fostering brittle strategies and negative training effects. This paper introduces a macrocognitive design taxonomy for simulation-based training systems derived from a large-scale meta-analysis examining the transfer of macrocognitive skills from …

Stentrx, Emma Barna, Minuthi Cooray, Bruce Newlands, Joseph A. Sabetta

Williams Honors College, Honors Research Projects

This project aims to develop a biodegradable, drug-eluting biliary stent for the treatment of biliary cancers. Current metal stents that restore bile flow bit are non-degradable, prone to migration, and unable to deliver drugs locally. The proposed stent will be biocompatible, biodegradable, and capable of controlled drug release to both maintain bile flow and treat tumors. The end goal is to produce a functional prototype that can be deployed via a minimally invasive catheter and maintain bile duct patency for at least three months. The project is expected to be involved in the NEOMED Bench-to-Bedside competition and provisionally patented.

Goal-Driven Shared Control In Eeg-Based Brain Machine Interface For Freewill Reaching And Grasping With Movement Intention Detection And Goal Position Decoding, Bhoj Raj Thapa

Theses and Dissertations--Electrical and Computer Engineering

Upper limb motor impairments can severely limit a person’s ability to perform everyday reaching and grasping tasks. Electroencephalogram (EEG)-based brain machine interfaces (BMIs) offer a non-invasive approach for translating neural activity into control signals for assistive devices such as robotic arms. However, traditional EEG-based BMI studies have generally focused on externally cued paradigms, where both movement timing and target selection are specified by the experimenter rather than freely chosen by the user. In addition, shared control offers a practical framework for assistive BMI operation by dividing responsibility between the user and the intelligent robotic system. However, in many EEG-based shared …

Ai-Driven Network Orchestration: Adaptive Routing For Federated Learning Over Software-Defined Hybrid Wans, Osama Abu Hamdan

Computer Science and Engineering Dissertations - Archive

Modern wide-area networks increasingly adopt hybrid architectures that combine high-capacity wired backbones with flexible wireless links to extend connectivity to remote and underserved locations. However, the bandwidth variability inherent in wireless segments creates routing challenges that traditional protocols, designed for static link capacities, cannot adequately address. Simultaneously, Federated Learning (FL) has emerged as a privacy-preserving distributed machine learning paradigm in which geographically dispersed clients collaboratively train shared models without exchanging raw data. When deployed over wide-area networks, FL training is severely bottlenecked by communication overhead, particularly in cross-silo settings where model payloads reach hundreds of megabytes and synchronous aggregation protocols …

Microwave Synthesis And Characterization Of Fe2ptge Nanoparticles, Ally T. Fennell, David Carnevale

Chemistry Theses

Magnetic, semiconductor, and spintronic materials are vital to the functionality of devices from household appliances and sensors to medical and computing systems. This study discusses a novel synthesis and characterization of nanoscale Fe₂PtGe nanoparticles. The material was synthesized using microwave irradiation (175oC, 5 minutes) and characterized using XRD, XRF, TEM, and VSM. XRD of the synthesized particles correlates to a cubic crystal structured, indicating a face-centered cubic (fcc) platinum structure with iron and germanium incorporated in a disordered manner. XRF confirms the presence and relative ratios of iron, platinum, and germanium species. TEM imagery shows spherical nanoparticles with an average …

Rope Cutting Task Module, Rebecca Usher

Engineering Theses

This project focuses on the design and evaluation of a rope-cutting module for use with robotic platforms developed by New England Robotics Validation and Experimentation Center (NERVE) and the University of Massachusetts Lowell. The system is designed to cut nylon rope using a specialized robotic cutting arm that can be attached to the robot.

The system consists of a module task box that has two pegs that hold two arms to each one. One arm where the spring- mechanism inside of the task module and the second arm the one on top of the box hold the string in place …