Digital Commons Network^™

Thermal Modeling Techniques For Additively Manufactured Porous Metals, Lucas D. Rambo

Master's Theses

Advances in additive manufacturing have enabled the creation of metallic components with tailored porosity, offering design flexibility for thermal, structural, and fluid transport applications. This thesis investigates the effective thermal conductivity (ETC) of porous Inconel 625 (IN625) and Inconel-ceramic composites (IN625-RAM2) fabricated by Laser Powder Bed Fusion (LPBF) using Elementum 3D’s PermiAM technology. Experimental measurements of thermal conductivity using the laser flash method are compared to numerical models built from micro-computed tomography data. Simulations were performed using both finite element (FE) and finite volume (FV) methods to evaluate thermal transport in real microstructures. The study investigates the effects of micro- …

Remote Monitoring And Control Of Protection Relays Via Programmable Logic Controller, Rio Mcgown-Kauffman

Master's Theses

The purpose of this study is to explore the ability of a programmable logic controller (PLC) to wirelessly monitor and control power protection relays. The technologies surrounding power protection and industrial automation are ever evolving and have developed significantly in recent history. Industrial power applications call for consistent condition monitoring and status updates for various high-importance components. The high-importance components have power protection schemes that are managed by digital relays to trip circuit breakers in fault or unsafe operating conditions. The smart relays have a wide range of capabilities, including communications. Cal Poly assembled a collection of relays from Schweitzer …

Range-Dependent Meso-Scale Geoacoustic Seabed Quantification, Tim Sonnemann, Jan Dettmer, Charles W. Holland, Stan E. Dosso

Electrical and Computer Engineering Faculty Publications and Presentations

This study presents a probabilistic one-step two-dimensional (2D) inversion method of spherical-wave reflection coefficient data to estimate the range-dependent structure and geoacoustic parameters along a track. The approach of inverting such datasets independently as one-dimensional (1D) layered models and merging them to a 2D section is feasible but computationally expensive. This study demonstrates a more parsimonious 2D parametrization for active source data recorded on a towed hydrophone array. The comparison of data variance reduction for 1D- and 2D-based results clearly favors the 2D parametrization described here.

Bentonite Erosion And Cation Exchange Effects On Hydraulic Conductivity Of Geosynthetic Clay Liners, Grace Paananen

Master's Theses

Geosynthetic clay liners (GCLs) are used in municipal solid waste landfill (MSW) liner and cover systems as an alternative to thick compacted clay layers. Previous field studies have revealed potential for bentonite erosion in GCLs when subjected to wet-dry cycles that occur when GCLs are placed on slopes, covered with a geomembrane, and left exposed without additional soil cover. A laboratory test program was conducted to quantify the effects of bentonite erosion on hydraulic conductivity of sodium-bentonite geosynthetic clay liners and samples subjected to cation exchange treatment in addition to bentonite erosion. This test program determined what level of bentonite …

Load Balancing In Mobile Networks Using Deep Reinforcement Learning And Traffic Prediction, Shorouk Raafat Mokhtar Abouamasha

Theses and Dissertations

Wireless communication networks are advancing at a rapid pace, driven by various challenges and ambitious goals. This rapid growth is driven by a range of applications, including technologies like the Internet of Things (IoT), as well as innovations in smart cities, autonomous vehicles, and more. Different applications demand specific performance criteria such as high data throughput, low latency, robust reliability, and efficient energy usage. In this thesis, we investigate two enhancements that can be adopted in wireless networks to tackle the challenges of resource optimization and network management. The motivation behind this is the fact that future networks will face …

Experimental Evaluation Of Novel Nano Polymer Hybrid Enhanced Oil Recovery In Carbonate Reservoir, Altamish Ahmed Pakeer

Theses

Innovative enhanced oil recovery (EOR) strategies are needed to unlock additional reserves in heterogeneous, oil-wet carbonate reservoirs. This study evaluates hybrid nano-polymer flooding by integrating silica nanoparticles (SiO₂) and single-walled carbon nanotubes (CNT) with novel HPAM polymers (Sav10 and Sav10 VHM) to optimize wettability alteration, rheological parameters, and recovery mechanisms.

A comprehensive experimental approach was employed, where rheological tests assessed viscosity enhancement under varying shear conditions, and wettability alteration was quantified via contact angle measurements using HPAM-SiO₂, HPAM-CNT, Sav10 VHM-SiO₂, and Sav10 VHM-CNT systems. Core floods were performed in three consecutive phases; waterflooding (baseline), standalone nanoparticle flooding, and hybrid nano-polymer …

Assessing The Impact Of The Women In Construction Leadership Course And Disc Training On The Construction Industry For Students And Recent Graduates, Amanda E. Mcdowell

Construction Management

This study examined the impact of the Women in Construction Leadership Course, paired with DISC training, on students transitioning into the construction industry. The DISC instrument classifies behaviors into four personality types (i.e., Dominant, Influencer, Steady, Conscientious) and the training helped students identify each personality type to improve their communication skills. Although technical skills are essential for completing daily tasks, effective leadership and communication are crucial to project success. This research explored how DISC training can improve new hires’ perceptions of their abilities to interact and communicate with their project team members. Through a survey of course participants, the study …

Investigation Of Retention And Dehydration Of Preformed Particle Gel For Conformance Control In Fractured Carbonates, Abdulaziz A. Almakimi, Abdullah O. Almansour, Junchen Liu, Baojun Bai, Ibnelwaleed A. Hussein

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Preformed particle gel (PPG) treatment has proved to be among the most effective methods to reduce excessive water production in fractured reservoirs. The blocking ability of PPGs to fractures or fracture-like features is highly dependent on injected gel properties and volume. Gel dehydration during extrusion through fracture is common and has a considerable effect on gel properties, transport, and plugging efficiency. As the gel particles propagate through the fracture, continuous dehydration is often associated and causes the gel to concentrate and require high-pressure gradients to move. Dehydration might be desirable to a certain limit because it can help to form …

Investigation And Prediction Of Excessive Water Production In Bottom Water-Drive Naturally Fractured Reservoirs Using Machine And Deep Learning, Sami Abderraouf Belkhir

Theses

Naturally Fractured Reservoirs (NFRs) are characterized by dual-porosity and dual-permeability systems, posing significant challenges in managing water production due to highly conductive fracture networks that facilitate rapid water migration from bottom aquifers, often bypassing oil stored in the matrix, thus resulting in early water breakthrough and water channeling phenomena. The main objective of this thesis is to develop and validate deep learning and machine learning models to predict water production, water breakthrough time (tbt), and ultimate water cut (WCult) in NFRs, thereby enabling more effective reservoir management strategies. This work also aims to evaluate the sensitivity of water behavior to …

Experimental And Computational Study Of Slow Crack Growth Of High Density Polyethylene, Abdulla Fawzi Almomani

Dissertations

This dissertation investigates the slow crack growth (SCG) behavior of High-Density Polyethylene (HDPE) under various mechanical and environmental conditions. The study combines experimental analysis and computational modeling to enhance the understanding of SCG mechanisms in HDPE, particularly in pressurized pipes and under the exposure to hydrocarbons. A novel Crack Layer (CL) theory-based SCG model is developed and validated through experimental data, offering a predictive framework for HDPE failure assessment. The main objective of this dissertation is to quantify and model the viscoelastic-viscoplastic behavior of HDPE under monotonic and cyclic loading conditions while addressing SCG kinetics in structural applications. The study …

Utilizing Date Fruit Pomace As A Corrosion Green Inhibitor For Non Ferrous Alloys, Sardor Rustam Odilov

Theses

This thesis explores a novel green corrosion inhibitor derived from date fruit pomace extract (DFPE) for the protection of aluminum alloy 3003 in highly corrosive environments, specifically hydrochloric acid (HCl) and natural seawater. The central aim is to promote the sustainable reuse of agro-waste as an effective and eco-friendly alternative to conventional toxic inhibitors, aligning with environmental and industrial safety goals.

A comprehensive methodology was employed, including Soxhlet extraction (using both non-polar n-hexane and polar methanol-water solvents), rotary evaporation, and FTIR analysis to identify the active functional groups responsible for inhibition. Corrosion behavior was systematically evaluated using both mechanical (weight …

Constraining Nuclear Data Uncertainty Requirements For The 19F(A, N)22Na Reaction For Non-Proliferation Applications, Tyler R. M. Smith

Theses and Dissertations

This thesis explores the requirements on nuclear data uncertainties needed for the use of the ¹⁹F(α, n)²²Na reaction for nuclear non-proliferation applications. An overview of how neutrons are produced from alpha decays in a UF₆ medium is discussed. Calculation demonstrate the role nuclear data uncertainties effect the neutron yield and energy spectra as a function of enrichment.

How Argentina Won The 2022 Fifa Men's World Cup: A Data Story, Aniruddha Parthasarathy

Dissertations, Theses, and Capstone Projects

This project analyzes Argentina’s 2022 FIFA Men’s World Cup win using open-source football (soccer) data. The project evaluates the team’s performance at a micro-level across three domains: without possessing the ball, possessing the ball and the team’s in-game management tactics. A statistical framework, i.e., multiple linear regression modeling, was used to identify the five key defensive actions influencing the Argentinian team’s intensity of pressure applied, and visualized by heatmaps and time-segmented plots. More specifically, an Expected Threat (xT) analysis quantified the threat or danger from passes and progressive carries (moving the ball at least 10 meters), revealing that Lionel Messi’s …

War, Wounds, And Strategy: Patient Movement Lessons From The World Wars For Great Power Competition, Phillip R. Jenkins

Faculty Publications

This thesis examines the evolution of the U.S. military's patient movement system during World War I and World War II to evaluate how well it may perform under the conditions of future large-scale combat operations. It asks whether the United States can move, treat, and sustain wounded personnel at the scale and pace required to preserve combat power in a prolonged, high-intensity conflict. Using detailed case studies of the Meuse-Argonne Offensive and the Battle of the Bulge, the analysis focuses on how transportation platforms, organizational structure, and standard operating procedures (SOPs) shaped patient movement under conditions of attrition, disruption, and …

Building Services Engineering May/June 2025

Building Services Engineering

No abstract provided.

Hunting, Feiyang Zhuang

Masters Theses

This writing is about fragility and revelation of technological systems. It considers how brokenness, delay, and opacity are not flaws but openings—opportunities to reimagine our relationship to technology as something grounded, sensory, and continuous with the natural and material world.

Interaction Of Liquid Phase Diisopropyl Methyl Phosphonate (Dimp) With Material Surrogates For Components Of Soil And Combustion Products Of Metal Fuels, Khushi Sunil Patel

Theses

Combustion products of three different Al-based materials, Al-CaCO₃, Al-SiO₂, and Al-Fe₂O₃ , have been produced to understand their interaction with liquid diisopropyl methyl phosphonate (DIMP), a surrogate for chemical weapon agents. The purpose of this is to see which materials were more effective at DIMP adsorption and decomposition at different temperatures. Prepared materials were characterized using electron microscopy, x-ray powder diffraction, and nitrogen adsorption. Prepared powders were submerged in DIMP and heated in a thermal analyzer, tracking the mass changes as a function of temperature. Surfaces of the recovered materials were studied using …

Surface Resistivity Correlation To Nano-Defects In Laser Powder Bed Fused Molybdenum (Mo)-Silicon Carbide (Sic) Alloys, Andrew Mason, Larry W. Burggraf, Ryan A. Kemnitz, Nate Ellsworth

Faculty Publications

The integration of Silicon Carbide (SiC) nanoparticles into Laser Powder Bed Fusion (LB-PBF) Molybdenum (Mo) printing represents a significant advancement in refractory metal additive manufacturing. Our investigation examined how varying SiC nanoparticle sizes affect the microstructural and electrical properties of LB-PBF-printed molybdenum components while maintaining a 0.01 mass fraction of Mo. At an Linear Energy Densities (LED) of 1.8 J/mm, the addition of 80 nm SiC particles achieved a 46% reduction in porosity, while sheet resistance decreased by 6% at LED of 2.0 J/mm with 80 nm SiC particles. These performance improvements stem from several mechanisms: SiC particles serve as …

Mechanisms And Equation Improvement For Gas Seepage In Coal Seams Around Boreholes Subjected To High-Pressure Co2 Foam Fracturing, Pang Mingkun, Zhang Tianyu, Pan Hongyu, Song Xianfeng, Wu Shan, Zhang Tianjun

Coal Geology & Exploration

Objective The special low-porosity, low-permeability structures of high-gas-content coal seams restrict efficient gas drainage. To address this issue, this study accurately determined the seepage parameters of annularly fractured coals around boreholes subjected to CO₂ foam fracturing to enhance both the design accuracy of boreholes for gas pre-drainage from coal seams and gas drainage efficiency. Methods Using an independently developed apparatus for gas seepage experiments on fractured coals around boreholes, this study investigated the coals with pores and fractures distributed in an annular pattern around boreholes from the perspective of varying initial pore structures. Specifically, this study analyzed the evolutionary …

Diffusion Mechanisms Of Power-Law Grouts In Water-Rich Sand Layers During Permeation Grouting, Xie Bao, Cheng Hua, Wang Xuesong, Li Mingjing, Liu Xiangyang, Han Xueyu

Coal Geology & Exploration

Objective This study aims to clarify the spherical diffusion patterns of power-law grouts in water-rich sand layers during permeation grouting and their influential factors. To this end, permeation grouting experiments were conducted to gain insights into the quantitative impacts of varying grouting parameters on grout diffusion.Methods Using model experiments on spherical diffusion during permeation grouting, this study analyzed the macroscopic diffusion morphologies and microscopic infilling effects of grouts, as well as the trends of permeation and soil pressures during grouting. Then, based on the spherical diffusion equations for permeation grouting that consider multi-effect coupling, this study analyzed the factors …

Levels Of The Nicotine Analog 6-Methyl Nicotine As A Naturally Formed Tobacco Alkaloid In Tobacco And Tobacco Products, James F. Pankow, Wentai Luo, Kevin J. Mcwhirter, Mohana Sengupta, Robert M. Strongin

Civil and Environmental Engineering Faculty Publications and Presentations

S-6-methyl nicotine (S-6MN) has appeared as a nicotine substitute in commercial electronic e-cigarette products and pouches, including with the claim that such use is not regulated under current U.S. law. This work describes an analytical chemistry based search for the natural S/R presence of 6MN and three other MN compounds in additive-free cured leaf tobaccos and in multiple commercial tobacco products. The samples were extracted using 5 N NaOH, then methyl t-butyl ether. The extracts were analyzed using gas chromatography (GC) with mass spectrometric (MS) detection, and liquid chromatography (LC) with high resolution MS/MS detection. GC peaks with the correct …

An Improved Mp-Nmo Correction Method Based On Multiparameter Fitting And Its Application, Yang Xiaohui, Yu Pengfei, Zhang Jiawei

Coal Geology & Exploration

Objective and Methods Normal moveout (NMO) correction is a core step in seismic data processing. However, the conventional NMO correction method tends to cause wavelet stretching when processing wide-angle or large-offset seismic data, leading to degraded stacking quality and distorted amplitude variation with offset (AVO) attributes. Although the matching pursuit (MP)-NMO correction method can mitigate the stretching effect, it will cause lateral discontinuity due to overlapping seismic events. Therefore, this study developed an improved MP-NMO correction method based on multiparameter fitting. Specifically, during MP decomposition, cubic polynomial fitting was applied to the amplitude, frequencies, and phases of wavelets from the …

Retracted: Cipher Text To Secure Li-Fi System Using Hybrid Encryption Algorithm, Mohammed M. Ahmed, Satea H. Alnajjar

Iraqi Journal for Computer Science and Mathematics

It is important to pay attention to develop our security systems, due to the increase in cyberattacks and the development of their methods and the work to develop quantum computers capable of penetrating the solution of complex equations of encryption algorithms. The need to develop protection methods has emerged in line with the development of hackers to ensure the security and safety of users' data. In this research, work was done on the modern Li-Fi technology based on comparing the values with Kim's model and a distance of more than 13 km was reached in the fresh air. This technology …

A New Class Of Endo-R.B Module And Its Relationship With Modules, Mohammed Salman Murad, Buthyna Najad Shihab

Iraqi Journal for Computer Science and Mathematics

This paper gives a definition of a new class of T-module and T-submodule called an Endo-Restricted Bounded module (submodule) written shortly by Endo-R.B. module (submodule) and present some different approaches to connect this class of module with other types of modules such as: compressible modules, monoform modules, critically compressible modules, retractable modules, and quasi-Dedekind modules. One of the main purpose of this work is to introduce a few new conditions and reveal some properties and corollaries. This paper considered to be another solution or answer for Zelmanowitz’s problem. In fact, an Endo-R.B. T-module plays an important role to this problem …

The Antioxidant Potential Of Rosemary Leaf-Derived Nanovesicles, Shani Akila Griffin

Master's Theses

Human dermal fibroblasts are essential for maintaining skin homeostasis. However, exposure to exogenous and endogenous stressors can lead to fibroblast instability, extracellular matrix degradation, and excessive reactive oxygen species (ROS) production. These factors contribute to skin aging and ROS-induced skin disorders leading to hair loss. Adverse effects from synthetic treatments have driven interest in natural alternatives like plant extracts for skin therapy. However, the polyphenols in these treatments require an effective delivery system to ensure their stability and targeted application. Plant derived nanovesicles (PDNVs) are emerging as a promising natural alternative for therapeutic applications. Their biocompatibility, stability, and encapsulated compounds …

Dsa-Api: Data Standardization Automation Using Ai-Powered Apis, Andrew Asher Turner

Master's Theses

The common factor with current implementations of Artificial Intelligence (AI) is data. Companies are constantly looking for new ways to analyze data, but it comes in various formats: Text, Comma Separated Value (CVE), JavaScript Object Notation (JSON), Extensible Markup Language (XML), and Excel. How can AI be adapted to standardize formats for data analysis, integration, and digestion efficiently? Published research acknowledged that Machine Learning (ML) and AI can provide an automated method to speed up this process and limit the human decision-making error. With the advancement in AI, Application Programming Interfaces (APIs) prompt the idea that they can take in …

Bronconest, Jake Esperson, Andrew Collins, Anish Katragadda

Computer Science and Engineering Senior Theses

Selecting suitable housing is a critical yet often overwhelming aspect of the college experience, particularly for incoming students who lack access to transparent and meaningful information about residential life. Existing platforms, such as official university housing portals or external real estate websites, fail to capture the nuanced, day-to-day experiences that influence student well-being, including cleanliness, social atmosphere, and sense of community. This issue is further compounded by the growing prevalence of remote decision-making and scattered, unverified sources of housing feedback.

To address this challenge, we developed BroncoNest, a scalable, cross-platform mobile application designed to centralize and personalize the student housing …

A Data-Driven Approach To Smart Shopping: Optimizing Grocery Trips Using Geolocation And Store Inventory Data, Kien T. Giang

Honors Theses

This project presents a data-driven web-based application, Smart Shopping, designed to help customers optimize their grocery purchases based on location and store inventory information. The application allows users to add items to a shopping list and either enter an address or use their browser’s location services to identify nearby stores. It then retrieves product availability and prices from a mock database representing stores at user’s selected locations. The program compares prices across stores to provide users with two optimized options: the cheapest shopping bill from a single store, and the lowest individual item prices across multiple stores. Additionally, the …

Causation Analysis Of Crane-Related Accident Reports By Utilizing Chatgpt And Complex Networks, Yifan Wang, Junyu Chen, Bo Xiao, Shane T. Mueller, Jingjing Guo

Michigan Tech Publications

This study integrates ChatGPT and complex network (CN) techniques into an accident analysis framework designed to reduce manual effort in accident causation analysis. The proposed framework supports construction stakeholders in extracting causal factors (CFs) from accident reports and identifying both critical CFs and key causal paths. A multistep research design was adopted to develop and validate this novel framework for analyzing crane-related construction accident reports using ChatGPT and CN techniques. First, ChatGPT was prompted to extract CFs from a database of crane-related accident reports. Second, evaluation metrics and an expert questionnaire survey were developed to assess ChatGPT’s performance in CF …

Leveraging Reduced Order Models And High-Fidelity Simulations For Efficient Multifidelity Uncertainty Quantification Of Thermal Systems, Jakob G. Bates

Theses and Dissertations

Simulation-led design is becoming an important part of thermal systems design. Simulations of thermal systems continue to improve in their fidelity, but this comes with an increased computational cost. Additionally, uncertainty in simulation inputs, such as thermophysical properties, leads to uncertainty in simulation outputs. For simulations to be used rigorously for simulation-led design, this uncertainty must be quantified. Performing uncertainty quantification on thermal simulations is made difficult by their many uncertain parameters and high computational cost. Multifidelity uncertainty quantification is a set of methods that reduce the cost of uncertainty quantification by leveraging high-fidelity, high-cost simulations with low-fidelity, low-cost simulations. …