Engineering Commons^™

Foundations' Deep, Emily Williams, Morgan Williams

University Honors Theses

Most historic buildings do not survive as they were built, yet preservation frameworks still tend to evaluate them as if they did.

Foundations' Deep begins with a structure located in Helena, Montana 59602, a building that sits uneasily within the categories it has been asked to meet. Built in the early twentieth century, it has persisted through alteration, abandonment, and use. What remains is not a stable artifact but a record of accumulated decisions, some careful and many indifferent, now embedded in the fabric of the building itself.

The thesis grows from this condition and from the limits of the …

Evaluating Chest-Worn Light Logger Adherence: Development And Application Of A Wear/Non-Wear Model, Carlyn Patterson Gentile, Adah Thomas, Ryan Shah, Blanca Marquez De Prado, Nichelle Raj, Christina Szperka, Geoffrey Aguirre

Student Papers, Posters & Projects

Light exposure plays an important role in overall health because it entrains circadian rhythms. Recent technological advances in wearable light loggers allow measurement daily light exposure habits. Using a chest-worn light logger, our goal was to (1) develop methodology for differentiating adherent versus non-adherent use, and (2) define differences in lighting intensity in indoor and outdoor environments, to improve data reliability in future clinical studies using this technology. Four testers used a 10-channel chest worn light logging device under different conditions of wear and non-wear (experiment 1), and another tester made measurements with the light logger across a variety of …

Matching Two Long Interferometric Pathlengths Using Low Temporal Coherence Light For Finding Hong–Ou–Mandel Dip, Keith A. Wyman, Noah S. Everett, Anil K. Patnaik

Faculty Publications

Hong–Ou–Mandel (HOM) dip from a biphoton source in a two-photon interferometer provides a myriad of quantum tools for quantum communication and sensing. But the stringent requirements for spatial coherence between the photon pair makes it prohibitively difficult to observe high-fidelity HOM dip in long-distance free-space implementations, e.g., for the photon pairs involved in quantum communication need to match the two path lengths within a few 10 s of micron because of the short coherence width of the two-photon wave-packet. While many techniques for the pathlength balancing of two interferometric arms have been studied and applied extensively, such balancing is further …

Numerical Assessment On The Use Of Structured Coral Reefs To Mitigate Tsunamis, Rim Ahmed Alsheikh Ali

Thesis/ Dissertation Defenses

This thesis investigates the role of coral reefs as nature-based tsunami protection systems for coastlines in the United Arab Emirates (UAE). The study is significant because the UAE is located near the seismically active Makran Subduction Zone in the Arabian Sea, which may generate tsunami hazards. The research provides a quantitative assessment of how coral reef morphology, particularly reef width and depth, influences tsunami wave attenuation, flow velocity, flow depth, roughness, and bed shear stress.

The study used a multi-phase methodology combining literature review, laboratory experiments, and numerical modelling. Flume experiments were conducted at UAEU using high-fidelity 3D-printed Acropora coral …

Declination Of Groundwater Potential Zones Of Nashik, Maharashtra Using Geographic Information System With Analytic Hierarchy Process-Fuzzy Techniques, Madhusudhan M. Reddy, Bhogayya G. Naidu, Bharat N. Mulay, Ramanjaneyulu B, Ravi K. Kumar, Mirzi L. Betasolo, Praveen U. Goud, Snehal N. Chaudhari

Mansoura Engineering Journal

Groundwater is a critical resource for agriculture and domestic use in the semi-arid region of Nashik District, Maharashtra, where overexploitation and erratic climatic conditions have led to declining groundwater availability. This study integrates Geographic Information System (GIS) with Analytic Hierarchy Process (AHP) and Fuzzy-AHP techniques to delineate groundwater potential zones (GWPZs) and identify suitable sites for artificial recharge. A total of ten thematic layers drainage density, rainfall, geomorphology, elevation, distance from river, geology, slope, land use/land cover, topographic wetness index (TWI), and curvature were derived from SRTM DEM, Landsat-8, and IMD datasets, representing key controls on groundwater recharge, infiltration, and …

Broncosgo: Driving Student Event Participation Via Human-Ai Collaborative Event Curation, Katherine Carter, Ethan Sychangco

Computer Science and Engineering Senior Theses

College campuses rely heavily on email communication for event advertisement. However, due to the sheer number of emails any student may receive, the individual effectiveness of each advertisement decreases. A better alternative for event promotion was needed. How could we introduce students to events they would not usually find on their own, without continuing to fill up their email inbox? And how would information on all of those events be collected and maintained without requiring organizations to jump through extra hoops? Our project, BroncosGo, solves this issue by maintaining a database of campus events which is populated with information provided …

Club Finance Management Application, India Bell, Lydia Martin, Sola Kawahara, Zachariah Wang

Computer Science and Engineering Senior Theses

There are over 160 Registered Student Organizations (RSOs) at SCU as of 2023 [6]. There is currently no centralized system that RSO treasurers use to track and manage club finances. As a result, many organizations rely on fragmented methods such as spreadsheets, shared documents, email chains, and manual record keeping to manage budgets, reimbursements, and financial reports. These disconnected systems often lead to inconsistent organization, communication difficulties, and challenges during leadership transitions between club officers. This project proposes the development of a web-based Club Finance Management Application, Kaikei, designed specifically for Santa Clara University student organizations. The application centralizes financial …

Fatigue Behavior Characterization Of Magnesium And Aluminum Alloys In Military Trainer Aircraft, Alysson Sousa Rabelo, José Aécio Gomes De Sousa, Feliciano José Ricardo Cangue, Luiz Leroy Thomé Vaughan

Journal of Aviation Technology and Engineering

The increasing demand for lightweight and durable materials in aviation industry necessitates continuous improvements in research into fatigue-resistant alloys to improve operational efficiency, safety, and cost-effectiveness. The estimation of the operational life of aeronautical structures is directly related to the study of their mechanical properties, particularly concerning fatigue behavior due to the constant exposure to cyclic loads. For this reason, the aeronautical sector often invests significant capital in research for the development of new alloys that enable high structural performance, lightness, low cost, high durability, and tolerance to environmental damage. Despite the advancements in composite materials, aluminum and magnesium alloys …

Iajes Website Redesign, Justin Fan, Nicolas Gibson, Isabelle Hu, Anisha Malani

Computer Science and Engineering Senior Theses

The International Association of Jesuit Engineering and Science Schools (IAJES) connects more than sixty Jesuit institutions worldwide to promote collaboration and shared learning in STEM research. Santa Clara University is one of more than sixty member universities whose faculty and staff participate in conferences and task forces to address priority issues identified by the Society of Jesus. IAJES’ existing website, built on a static no-code platform, limited the organization’s ability to manage content, support member interaction, and scale with its growing global network. Users faced unclear navigation options, a basic design, and no effective tools for managing roles, resources, or …

Winddensity-Mbir: Model-Based Iterative Reconstruction For Wind Tunnel 3d Density Estimation, Karl J. Weisenburger, Gregery T. Buzzard, Charles A. Bouman, Matthew R. Kemnetz

Faculty Publications

Experimentalists often use wind tunnels to study aerodynamic turbulence, but most wind tunnel imaging techniques are limited in their ability to take non-invasive three-dimensional (3D) density measurements of turbulence. Wavefront tomography is a technique that uses multiple wavefront measurements from various viewing angles to non-invasively measure the 3D density field of a turbulent medium. Existing methods make strong assumptions, such as a spline basis representation, to address the ill-conditioned nature of this problem. We formulate this problem as a Bayesian, sparse-view tomographic reconstruction problem and develop a model-based iterative reconstruction algorithm for measuring the volumetric 3D density field inside a …

A Provable Semi-Infinite Programming Approach For Solving Constrained Dynamic Games, Tyler C. Gardner, Matthew W. Harris, Logan Lancaster

Mechanical and Aerospace Engineering Student Publications and Presentations

Many engineering problems must account for the non-cooperative decisions and actions of multiple players. These problems can be modeled within a game-theoretic framework. The approach herein is to model such problems as mathematical games, convert them to semi-infinite programs, and utilize a semi-infinite program solver whose output is provably an ϵ-optimal Nash equilibrium. The approach is successfully benchmarked on two low-dimensional problems. Two types of higher-dimensional linear quadratic dynamic games are then investigated: ones where each player’s problem is convex and ones where at least one player’s problem is nonconvex. Within each type, variations based on information structure, control …

Bilingual Math For Kindergartners (Biki), Anna Aldrin, Caroline Tapia, Lillian Le

Computer Science and Engineering Senior Theses

For many children from bilingual households, kindergarten represents a critical, learning benchmark where the introduction of fundamental math concepts coincides with their first significant exposure to the English language. Traditional educational methods often fail to support English language learners, leading to a disconnect between their understanding of math in the home and its application in the classroom. This linguistic barrier frequently results in reduced engagement, diminished confidence, and an unstable educational foundation that can discourage students from pursuing STEM careers later in life. While existing platforms like Khan Academy and Duolingo address either language acquisition or mathematical proficiency independently, they …

Bridgeide, Maya Srimal, Jeshwin Prince, Arnav Gupta, Will Zumbolo

Computer Science and Engineering Senior Theses

Anyone who has done a group project knows the pattern: the first meeting burns an hour on logistics—which document to use, who has access, why the formatting broke on one laptop—before real work begins. In computer science courses that gap is worse. Students must install the right compiler, runtime, and libraries on their own machines; a four-person team on four different laptops can lose the first week to setup alone. Instructors who want to review submissions often download every zip from the learning management system and run each one locally. Existing tools solve pieces of this puzzle—real-time document editing, browser-based …

Maya Roots, Erin Schmidt, Megu Kanzawa

Computer Science and Engineering Senior Theses

This project focused on the continued development of Maya Roots, a mobile and web-based platform designed for farmers in Tahcabo: a rural agricultural community located in Yucatán, Mexico. Yucatán faces unique agricultural challenges due to its karst limestone terrain and highly variable land conditions that can significantly impact farming outcomes. At the same time, traditional agricultural knowledge such as Milpa farming practices is increasingly at risk of being lost across generations. These environmental and cultural challenges highlighted the need for a portable, accessible system that could preserve agricultural knowledge, improve access to geospatial information, and strengthen communication between farmers and …

A Comprehensive Survey Of Artificial Intelligence Applications In Predicting Mining-Induced Subsidence, Deformation, And Landslides: Strengths, Limitations, And Future Trends, Long Quoc Nguyen, Dung Ba Nguyen, Minh Tuyet Dang

Journal of Sustainable Mining

Mining activities often cause mining-induced ground deformation, including subsidence and landslides, and related geo-environmental impacts, posing significant risks to infrastructure and safety. This study conducts a systematic assessment to identify, categorize, and evaluate AI-based methods (machine learning, deep learning, and hybrid models) for predicting and monitoring mining-induced ground deformation. The literature search was performed across major scientific databases, using predefined keywords and selection criteria, resulting in a final dataset of relevant peer-reviewed studies. The reviewed works were classified into three methodological groups: traditional machine learning, deep learning-based approaches, and hybrid methods. The results show that ML still dominates in terms …

Decoding Stock Market Movements: The Role Of Unemployment And Volatility, Bipllab Roy, Suparna Bhattacharjee

Northeast Journal of Complex Systems (NEJCS)

This study investigates how unemployment and market volatility interact with stock prices in the Indian context, framing the stock–labour–volatility nexus as a complex adaptive system (CAS) rather than a set of linear, time-invariant relationships. Using verified secondary data on unemployment, India VIX, and NSE stock indices for 2013–2023, we first apply simple and multiple regression as a descriptive baseline. Results show a strong negative association between unemployment and stock prices (R ≈ 0.824, R² ≈ 0.68, p < 0.05), consistent with Keynesian demand-side channels, while the linear VIX–stock relationship is weak and statistically insignificant (R² ≈ 0.07, p > 0.05), consistent with the expectation that volatility operates through non-linear, regime-dependent mechanisms not captured by OLS.

Importantly, we document and transparently disclose critical …

Investigations Of Carbon Dioxide Storage In Low-Temperature Reservoirs For Non-Leaking Storage, Md Nahin Mahmood

Doctoral Dissertations

Carbon dioxide (CO₂) injection into subsea or low-temperature water zones has emerged as a promising strategy for long-term, non-leaking CO₂ storage through the formation of solid hydrates. This research investigates CO₂ injection into Berea sandstone cores saturated with water under simulated subsea conditions, focusing on hydrate formation behavior across varying temperatures, pressures, and injection flow rates. Experimental results demonstrate that CO₂ hydrate formation under dynamic (flowing) conditions occurs at significantly higher pressure compared to static conditions reported previously. At temperatures ranging from 0 °C to 5 °C, dynamic hydrate formation pressures were observed to be approximately double. This can be …

Multidomain Modeling And Ramp-Aware Forecasting Of Floating Photovoltaic Systems For Water-Energy Nexus Applications, Md Atiqur Rahaman

Doctoral Dissertations

Floating photovoltaic (FPV) systems have become a transformative renewable energy technology because of their cooling effects on PV performance and ability to prevent water evaporation in land-constrained areas. Although FPV systems have the potential to become a commercially viable technology, their large-scale deployment remains constrained by uncertainties in thermal behavior, sustainability, and grid-operational variability. This dissertation identifies and characterizes these three key issues and presents an integrated, measurement-based evaluation of a 130 kW FPV installation located at the Passaúna reservoir in Brazil. In the first contribution, four temperature models, including physical and empirical models, were developed and comparatively evaluated to …

Automating Distillation Column Internals Design Via Reinforcement Learning: A Hybrid Action Space Approach, Holden B. Broussard

Masters Theses

Distillation columns are the most used separation technique in all chemical fields. The design of column internals presents a hybrid action space problem, where trayed internal parameters are continuous and packed parameters are discrete; Hybrid meaning the action space consists of both discrete and continuous design parameters. Hybrid action spaces have presented a challenge in the reinforcement learning space, since the most robust algorithms are designed to handle specific action types. This research develops and validates a hierarchical multi-agent reinforcement learning framework that divides the action spaces into different agents. The Controller agent selects between internal types, the Soft Actor- …

A Simulation-Based Lean Six Sigma Framework For Process Optimization In Textile Manufacturing Toward Industry 4.0, Md Shafiqul Islam Chowdhury

Masters Theses

This study focuses on integrating simulation modeling with Lean Six Sigma (LSS) within the DMAIC (Define, Measure, Analyze, Improve, Control) framework for process optimization in textile manufacturing industry. Although traditional LSS framework such as Value Stream Mapping (VSM) and Root Cause Analysis are effective in identifying waste, they mainly rely on static and historical data which make their capability limited for real analysis or predictive decision making. As a result, many textile manufacturing processes still face challenges such as production delays, excessive work-in-process (WIP), high cycle time, and inefficient resource utilization. To address this issue, this research proposes a simulation-based …

Hyperdimensional Computing For Edge And Mobile Devices, Colin Eddy Dupuis

Masters Theses

This thesis presents a set of four Hyperdimensional Computing (HDC) frameworks and their Android application implementations to evaluate efficiency and feasibility on resource-constrained devices. These proposed methods target a range of application domains, including wearable health monitoring, mobile malware detection, and activity recognition utilizing both computer vision and multiple sensor streams as input. The proposed frameworks utilize HDC’s simple, lightweight arithmetic operations to convert raw data into high-dimensional representations for use in both binary and multi-class classification schemes. Each method utilizes unique encoding techniques tailored for each use case, demonstrating the flexible nature and specialization HDC offers as an emerging …

Geological Carbon Storage In Deep, Low Permeable Shale Reservoirs: Insights From The Haynesville Formation, Louisiana, Himakshi Goswami

Masters Theses

As global initiatives to mitigate greenhouse gas emissions intensify, depleted unconventional shale gas formations have emerged as critical candidates for large-scale geological carbon storage (GCS). This study investigates the feasibility, dynamic trapping mechanisms, and operational optimization of CO₂ sequestration in deep, low-permeability shale reservoirs, using the Upper Jurassic Haynesville Shale in northwest Louisiana as a comprehensive case study. Compositional reservoir simulation (CMG GEM 2021.10) was performed using the SPE Haynesville dataset, with CO₂ injected at a rate of 10,000 ft³/day across single and multiple depth intervals spanning 11,290–11,314 feet. Results demonstrate that multi-depth injection significantly improves residual trapping, reduces buoyancy-driven …

Mitigating Surfactant-Gas Interactions In Associated Gas Reservoirs: A Simulation And Machine Learning Guided Approach, Francis Dela Nuetor

Masters Theses

Surfactant flooding is a promising chemical enhanced oil recovery (EOR) method for mobilizing residual oil through interfacial tension reduction and wettability alteration. However, its performance in associated-gas reservoirs can be limited by salinity, gas composition, surfactant adsorption, and possible chemical instability. This study investigates the effect of salinity on surfactant flooding efficiency using an integrated reservoir simulation and machine learning workflow. A synthetic three-dimensional reservoir model was developed in ECLIPSE using a 10 × 10 × 3 Cartesian grid to simulate surfactant flooding over a 300-day production period under salinity conditions ranging from 100 to 50,000 ppm. Key outputs, including …

Optimizing Co₂ Wag Flooding Parameters For Enhanced Oil Recovery And Formation Damage Control In Asphaltene Reservoirs Using Soft Experimentation, Derrick Amoah Oladele

Masters Theses

CO₂ Water Alternating Gas flooding has become an important enhanced oil recovery process in increasing oil production in medium to heavy oil reservoirs. However, CO₂ injections have the potential to cause asphaltene destabilization, leading to precipitation, deposition, and pore plugging. This study evaluated and optimized the effect of CO₂ flooding parameters to maximize oil recovery and minimized formation damage. Eclipse 300 compositional reservoir simulator was used to assess the effect of CO₂ Water Alternating Gas (WAG) Injection Rate, WAG Ratio, and CO₂ Water Alternating Gas (WAG) Injection Pressure on the reservoir. Predictive models for Cumulative Oil Production (FOPT) and Asphaltene …

Competitions Among Stations In Ieee 802.11be Networks, Jun Peng

Electrical and Computer Engineering Faculty Publications

The IEEE 802.11be standard aims for the next-generation applications that demand connections of extremely high bandwidth and low latency. It is the basis for Wi-Fi 7. An IEEE 802.11be device can operate in the 2.4, 5, and 6 GHz frequency bands simultaneously under the multi-link operation (MLO) mode. In the 6 GHz band, it can use a channel width up to 320 MHz. Its QAM-constellation can have up to 4096 states. Some of its other features include multiple resource units (MRU), preamble puncturing, and enhanced security. This paper shows the competitions among the stations in an IEEE 802.11be network with …

Large-Scale Synthesis (75 G/Batch) Of Single-Atom Catalysts For Selective Electrochemical Co2 Reduction To Co And Commercialization Potential Analysis, Carter Racine, Ahmed Badreldin, John Pellessier, Yayun Chen, Shaoqin Chen, Shengyao Wang, Jin Feng, Chengcheng Fei, Yun Hang Hu, Ying Li

Michigan Tech Publications

A promising approach to mitigate climate change is to use renewable electricity to convert carbon dioxide (CO2) emissions into useful products like carbon monoxide (CO) and hydrocarbons. While research has largely focused on developing high-performance catalysts for electrochemical CO2 reduction (eCO2R), scalability of catalyst synthesis remains underexplored. Metal–nitrogen–carbon (M–N–C) catalysts with dominant single-atom sites are among the most effective materials for CO production, but conventional synthesis methods rely on energy-intensive steps and complex pre- and post-treatment processes, hindering scalability and adding negative environmental impacts. This work demonstrates a scalable, single-step synthesis of M–N–C (M = Ni/Fe) catalysts using commercially available …

Jsd: Novel Methodology For Synthetic Data Evaluation, Jeffrey Lane, Scott Wang, Vincent Chang, Bojun Zhang

Computer Science and Engineering Senior Theses

The proliferation of sensitive Personally Identifiable Information (PII) on dark web marketplaces has created an urgent need for robust data protection systems, especially for vulnerable populations such as minors. Traditional PII redaction often fails to identify implicit privacy risks—such as author gender indicators or non-fictional child-related context—hidden within large-scale e-commerce datasets. This paper presents JSD, a dual-stage framework for the detection and protection of sensitive text data. The Detection phase utilizes Transformer and CNN-based architectures and Human-in-the-Loop AI to surpass the "semantic ceiling" of traditional NER approaches, enabling context-aware identification of implicit PII. The Protection phase introduces GASE (Genetic Algorithm …

Hemlock, Ephraim Esson, Ambrose Vellequette, Geno Meschi

Computer Science and Engineering Senior Theses

Hemlock is a tool designed to protect musicians from having their work used to train generative AI models without their consent. It works by adding carefully crafted inaudible noise to audio files that disrupts the ability of AI models to learn from them — a technique known as adversarial perturbation. Our system targets three different types of AI model simultaneously: a Music Information Retrieval (MIR) classifier, a sequential audio generation model (Mel-LSTM), and Meta’s AudioCraft, a transformer-based music generator. Testing in twenty songs showed an average 15% reduction in the MIR model’s classification confidence, a 59% increase in Mel- LSTM …

6tisch Based Sensing Network For Smart Agriculture, Riley Heike, Griffin Jones, Justin Odo, Jalen Paige, Rosalie Wessels

Computer Science and Engineering Senior Theses

This project investigates 6TiSCH (IPv6 over Time-Slotted Channel Hopping), a relatively recent IETF networking standard introduced in 2013 that combines deterministic TSCH scheduling, 6LoWPAN header compression, and RPL mesh routing to enable low-power, reliable, multi-hop wireless communication for IoT deployments. Despite its strong theoretical properties, 6TiSCH remains underexplored in practice, and real-world questions around configuration, scalability, power behavior, and end-to-end integration are not well documented. Our primary goal was to build and operate a working 6TiSCH network, characterize its performance through iterative testing, and understand what it takes to go from raw packet delivery to a complete data pipeline.

To …

Mimica, Sean Lai, Gurprasaad Hora, Stephanie Campos

Computer Science and Engineering Senior Theses

Language barriers remain a significant obstacle to natural human communication, limiting access to healthcare, business, travel, and daily social interaction for billions of people worldwide. Existing translation solutions such as smartphone applications and earpiece devices address the functional problem of converting words between languages but fail to preserve the speaker’s voice identity, require hands-on interaction, or depend on proprietary device ecosystems. These limitations disrupt the natural flow of conversation and reduce the human quality of cross-lingual communication.

Mimica is a real-time wearable translation necklace designed to address these shortcomings. Built around an ESP32-S3 microcontroller with an integrated microphone and speaker, …