Digital Commons Network^™

Radio Frequency Wave Propagation Modeling Within Obstructed Underground Mining Environments For Effective Miner Localization During Mine Emergencies, Emmanuel Atta Antwi

Doctoral Dissertations

The reliability of underground wireless communication systems remains a significant challenge, particularly during emergencies when the mine environment becomes severely obstructed by debris, dust, and humidity. These environmental and geometric conditions result in significant attenuation of electromagnetic (EM) waves and multipath effects that undermine miner localization and rescue operations. Existing Vector Parabolic Equation (VPE) models are efficient for straight or mildly curved tunnels but fail to account for the random and obstructive conditions typically encountered during underground emergencies. This research develops a novel radio propagation model for EM wave behavior in underground mine drifts under geometrically obstructed conditions. The model …

Innovative Air Convection Embankment For Cold/Arctic Region Low-Volume Roads, Hanli Wu, Jenny Liu, Xiong Zhang, Steve Saboundjian

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Roadbed thaw settlement is a unique challenge for the durability of low-volume roads (LVRs) in permafrost regions. Air convection embankment (ACE) is an effective technique that acts as a semi-heat-transfer system to control temperature variation and reduce the thaw depth of subsoil. However, limited by the shortage of the necessary crushed rocks within a short distance, building an ACE in Alaska, U.S., is prohibitively expensive. Previous studies identified the feasibility of using cellular concrete for ACE and determined the optimized thickness of the cellular concrete aggregate interlayer for ACE. However, the economic efficiency and thermal and mechanical performance of the …

Material Suppliers’ Perspective On Collaboration In Industrial Construction Projects, Seogjae Choi, William J. O'Brien

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Material suppliers' involvement in construction project planning has been recommended as an effective measure to improve project performance by using their expertise. However, the recommendation is not universal, and some researchers disputed the value of early involvement of suppliers depending on material type. Moreover, prior studies considered main contractors' and owners' perspectives mostly in examining how to increase the involvement of suppliers. To add material suppliers' perspective, this study conducted interviews with experienced professionals from 16 material suppliers including standardized, make-to-order, and custom products. The results are specified by separating the type of materials and sub-phases of planning. The results …

Extended S-Parameter Model Of The Power Distribution Network For Rapid Coupling Predictions, Cody Goins, Aaron Harmon, Mckennan Starkey, Kristen Donnell, Victor Khilkevich, Daryl Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Power and return planes are part of the power delivery network of almost all modern high frequency printed circuit boards. These power and return planes can form the basis of unintended radiated emissions from, or radiated coupling to, these boards. Predicting coupling to complex systems is a difficult problem and typically reserved for full wave simulations. Recent works have introduced segmentation approaches that are able to predict coupling to complex printed circuit board designs by using pre-rendered segments and cascading these segments through a circuit solver approach. The extended S-parameter models used by the segmentation approach currently do not include …

Modeling Of Slot-Backed Microstrip Line For Emi Applications, Jongsuk Hyun, Wenchang Huang, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Radiated emissions from the noise-generating components in modern electronic devices are a significant concern for both electromagnetic interference and RF interference. Shielding cans are commonly used to suppress emissions from noise sources, but accurate shielding effectiveness evaluation requires a clean, well-defined radiation source that can reliably mimic real emissions for repeatable measurements. Slot-backed microstrip antennas provide a practical alternative to loop antennas, offering zero height, low parasitic radiation, and seamless printed circuit board integration. This article proposes an analytical model for estimating the magnetic dipole moment of slot-backed microstrip structures. The model captures both the discontinuity effects and radiated characteristics …

Artificial Intelligence For Digital Deception: A Study On Detection, Generation, And Evaluation, Tasnim Akter Onisha

College of Graduate Studies: Theses & Dissertations

The rapid advancement of artificial intelligence has significantly influenced digital media, enabling both the detection and generation of synthetic content. This thesis, titled Artificial Intelligence for digital deception: A Study on Detection, Generation, and Evaluation, explores AI’s role in digital deception through three distinct studies focused on facial expression analysis for deepfake detection, machine learning-based spam classification on cloud platforms, and the evaluation of generative AI state-of-the-art text to video models. The first study investigates the effectiveness of facial expression analysis in distinguishing between deepfake and genuine videos. Using Noldus FaceReader 7, participant’s emotional responses were analyzed while viewing deep-fake …

Enhancing Ai-Driven Automation For Object Detection And Computer Vision, Nafeeul Alam Walee

College of Graduate Studies: Theses & Dissertations

In recent years, AI-driven automation has revolutionized the field of object detection and computer vision, enabling sophisticated and efficient solutions across various industries. This research explores the latest advances and techniques in improving AI-driven automation for object detection and computer vision applications. We examine state-of-the-art deep learning models and frameworks that have contributed to significant improvements in accuracy and speed and highlight the generative results. The focus is on exploring the real-time processing capabilities that have expanded the applicability of these technologies in real-world scenarios. Furthermore, we investigate image integration and video data to improve precision detection and contextual understanding. …

Pulsed Arc Additive Manufacturing Of A Functionally Graded Er2209 Duplex Stainless Steel And Hsla-100 Structure: Morphology, Characterization, And Mechanical Performance, Stevens G. Hill Jr

College of Graduate Studies: Theses & Dissertations

Wire arc additive manufacturing is a process well suited to the efficient production of large structures. Duplex stainless steel exhibits high corrosion resistance and good strength which can be highly beneficial for industrial use. However, its use is limited due to its cost and complexity in controlling microstructure to achieve desired properties. In many cases, it can be highly beneficial to manufacture a component which uses specialty steel grades such as duplex stainless steel only where necessary, and utilizes more affordable, commonly available steels for reinforcement or bulk structural support. A functionally graded material satisfies these requirements by providing a …

Multiphysics Modeling Of Solid Oxide Fuel Cells For Gradient Minimization And Inductive Loop Analysis In Impedance Spectroscopy Using Machine Learning-Based Microstructural Property Estimation, Muhammad Usman Khan

College of Graduate Studies: Theses & Dissertations

Solid oxide fuel cells have significant advantages in renewable energy utilization due to their high efficiency, fuel flexibility, and low emissions. However, despite the numerous efforts of technology, thermal and current density gradients and impedance behavior fluctuations are still causing performance degradation. A combined computational framework that integrates machine learning and three-dimensional Multiphysics modeling is needed to investigate and optimize the performance of solid oxide fuel cells. A machine learning model, trained on synthetic microstructure data by percolation analysis, is used to predict important microstructural parameters like triple phase boundary density and geometric tortuosity. These are then employed in a …

Computational Investigation Of Underbody Slant Angle Variation Effect On A Hatchback Vehicle, Nufile Uddin Ahmed

College of Graduate Studies: Theses & Dissertations

Electric Vehicles, despite many advantages over their gasoline-powered counterparts, have the following main challenges towards mass adoption – the charging infrastructure and the range of the vehicle. Among the myriads of factors affecting the range, the coefficient of drag and the required power to overcome it are noteworthy. This study aims to investigate the effect of rear underbody slant angle on a common, simplified hatchback-shaped Electric Vehicle. The rear underbody slant angles (upward) assessed were 0°, 5°, 10°, and 15° and they were subjected to three freestream velocities representative of urban (16 m/s), highway (25 m/s) and interstate (40 m/s) …

Synthesis And Assessment Of Biobased Acrylated Epoxidized Soybean Oil Resins For Stereolithography 3d Printing Of Microfluidic Devices, Natalie S. Romero Figueroa

College of Graduate Studies: Theses & Dissertations

This research focuses on the development and characterization of a biobased photocurable resin synthesized from soybean oil for use in stereolithography (SLA) 3D printing of microfluidic devices. The study explores a sustainable alternative to petroleum-based resins by performing an acrylation reaction on epoxidized soybean oil (ESO) to produce acrylated epoxidized soybean oil (AESO), which was then formulated into a photocurable resin with the addition of a photo initiator. The fabrication process involved designing microfluidic molds in SolidWorks and printing them using an Elegoo Mars 4 SLA printer under various exposure and layer thickness parameters. The printed samples consisted of microchannels …

A Comprehensive Analysis Of Climate Resilience Strategies For Small Island Developing States, Ashley-Ann Davis

Doctoral Dissertations

Small Island Developing States (SIDS) face unique and disproportionate challenges in their efforts to achieve climate resilience due to their geographic vulnerabilities, limited resources, and systemic economic and social constraints. This dissertation provides a comprehensive analysis of climate resilience strategies tailored to SIDS, addressing critical systemic issues and exploring interdisciplinary solutions. It synthesizes findings across four interconnected studies, including an analysis of disaster preparedness and response mechanisms in developing countries to identify gaps and opportunities for improving resilience in extreme events. The research investigates economic factors influencing energy portfolio transitions in the Caribbean, emphasizing the complexities of renewable energy adoption. …

Ceramic Dielectrics For High Temperature Capacitor Applications, Alan Daniel Devoe

Doctoral Dissertations

Technical progress in microelectronics is allowing operation in environments that were previously considered impossible. Building complete electronic circuits for applications above 450 degrees C, such as the planned NASA missions to Venus, require a variety of active and passive components, including multilayer ceramic capacitors (MLCC).

This study explores calcium zirconate CaZrO3 and magnesium oxide MgO based dielectric compositions for MLCC applications that are capable of operating at extreme temperatures between 450 degrees C and 600 degrees C. Both materials were characterized with respect to impurities, dopants, crystal structure and microstructural development. Dielectric properties were measured to determine permittivity, dissipation factor, …

Novel Nano-Formulations Based On Flash Nanoprecipitation For Ocular Drug Delivery, Lin Qi

Doctoral Dissertations

Effective ocular drug delivery has always been a challenge for clinical and research. Although many nanotechnology-based formulations have been developed and showed great potential in ocular drug delivery, this is far from enough to meet clinical requirements. These studies aimed at the design and synthesis of novel nanoparticles using multi-inlet vortex mixer (MIVM) to improve ocular drug delivery efficiency. The first project involves packaging two different anti-glaucoma drugs, brimonidine (BM) and betaxolol (BX), into solid drug nanoparticles (SDNs) by MIVM, which can achieve both functions, reducing aqueous humor production and promoting aqueous humor efflux. The studies demonstrate that the SDNs …

Supporting Human-Ai Interaction From User Expectations To Mental Models, Harishankar Vasudevanallur Subramanian

Doctoral Dissertations

Explainable AI (XAI) aims to unravel the "black box" nature of AI systems and provide insights into the inner workings that lead to a prediction. However, the best XAI communication varies depending on the individual, task, and broader context. It is challenging to anticipate the best XAI for a particular use case. One strategy is for users to build an appropriate mental model of AI with both prediction and system level XAI. To date, little research has focused on quantitatively measuring users interacting with system-level XAI. This dissertation has three primary contributions. The first contribution is a scoping review paper …

Enhanced Optimization Of Mass Transfer For Carbon Capture And Wastewater Remediation In Algal Systems Through Algorithmic And Bioprocessing Techniques, Peter Ofuje Obidi

Doctoral Dissertations

The scalability and industrial deployment of algal cultivation systems are limited by suboptimal mass transfer, constraining their effectiveness in carbon capture and wastewater remediation. This research investigated these challenges through integrated optimization methodologies that combine algorithmic frameworks with enhanced bioprocessing techniques to enhance efficiency, economy, and scalability. A System-of-Systems (SoS) meta-architecture was developed using genetic algorithms and fuzzy assessor functions to demonstrate a pathway toward cost reduction. Rigorous mechanical and chemical characterizations were quantitatively analyzed to reveal existing optimization strategies and further evaluated the best strategies to use in enhancing mass transfer for improved biomass yield. The work also integrates …

Nutrient Fate, Mass Balance, Species Selection, And Plant Management Strategies With Floating Treatment Wetlands, Carla Campbell

Doctoral Dissertations

Excess nutrients in shallow urban ponds can lead to harmful algal blooms, low dissolved oxygen, and internal phosphorus cycling. These effects can compromise municipal water supplies and cause negative impacts on fisheries and recreation. Floating treatment wetlands (FTWs) show promise to mitigate surface water nutrient pollution. However, despite recent research, many aspects of FTWs remain poorly characterized. The contribution of FTW components to nutrient removal, local species selection, and plant management strategies were the focus of this dissertation. Mesocosm experiments revealed that the combination of plants and coir fiber growth media in FTWs appeared to positively affect plant biomass gain …

Drone-Based Multimodal Sensing On Vegetations And Data Analytics For Early Detection Of Gas Leakage From Underground Pipelines, Pengfei Ma

Doctoral Dissertations

"This study explored the feasibility of using multimodal remote sensors in the early detection of natural gas leaks from underground pipelines, as vegetation situated above pipelines can discern microbial changes in soil when affected by gas and exhibit physiological stress symptoms on leaves. Three sensors (RBG, thermal, and hyperspectral cameras) were utilized to monitor vegetation stress as an indicator of gas leaks. A laboratory experiment was conducted to evaluate the workability of vegetation for gas leak detection. Regular hyperspectral imagery was collected from test vegetations to identify gas stress and distinguish it from other environmental stressors such as salinity impact, …

Processing And Densification Of Multi-Phase High-Entropy Ceramics, Steven Smith

Doctoral Dissertations

"This work focuses on the processing and densification of multiphase, high-entropy ceramics to promote their use in friction stir welding technologies. Several high-entropy systems including high-entropy borides, carbides, and their composites were produced. Boro/carbothermal and carbothermal synthesis were used to produce high-entropy powders from oxide powder mixtures. Composites of high-entropy borides and high-entropy carbides were produced using a sequential approach to produce both phases. The carbide was first produced using carbothermal reduction, then ZrH2 and B4C were added to the carbide powder to produce the high-entropy boride phase. The resulting powder was densified by spark plasma sintering and pressureless sintering, …

Investigation Of The Transport And Plugging Behavior Of Preformed Particle Gels (Ppgs) In Fractures For Conformance Control In Carbonate Reservoirs, Abdulaziz A. Almakimi

Doctoral Dissertations

This study aims to systematically evaluate the performance of preformed particle gels (PPGs) in fractured carbonates mainly through a series of core flooding experiments. Carbonate reservoirs exhibit unique features of heterogeneity and pore geometry, while (PPGs) are known for their plugging efficiency, deformability, and dehydratable nature. The main goal of gel injection in fractured reservoirs is to place a gel pack appropriately into the fracture, diverting injected fluid to the oil-bearing matrix and reducing excessive water production. However, considerable dehydration of (PPGs) is possible at the adjacent matrix and within the fracture, which could lead to a filter-cake formation and/or …

Transfection Of Ionizable Lipid Nanoparticles On Raw 264.7 And Mda-Mb-231, Lavanya Bhargava

Masters Theses

"This thesis investigates the preparation, characterization, and transfection efficiency of various ionizable lipid nanoparticles (LNPs) formulated for the delivery of mRNA encoding enhanced green fluorescent protein (EGFP) in RAW 264.7 macrophages and MDA-MB-231 breast cancer cell lines. The ionizable cationic lipid studied are ALC-035, C12-200, C14-4, PPZ-A10, DLin-MC3-DMA. The study addresses the need for effective gene delivery systems to provide a safe and versatile platform that protects and transports nucleic acids into target cells. LNPs were synthesized using microfluidic mixing methods, incorporating lipid components such as the cationic lipids, DSPE, DOPE, cholesterol and PEG lipids to achieve controlled particle sizes, …

Modeling Of Slot-Backed Microstrip Line For Emi Applications, Jongsuk Hyun

Masters Theses

Radiated emissions from printed circuit boards (PCBs) are a significant concern in electromagnetic interference (EMI) and radio frequency interference (RFI). Shielding cans are widely used to mitigate these emissions but evaluating requires accurate characterization of equivalent noise sources. Slot-backed microstrip antennas are employed for this purpose due to their near-zero height, low parasitic radiation, and PCB-compatible structure, offering a practical alternative to conventional loop antennas. This paper presents a physics-based analytical model that integrates both the discontinuity effects and radiated characteristics of slot-backed microstrip structures within a unified circuit framework. An analytical expression for the dipole moment is proposed based …

Frequency-Tracker And Power Supply For Piezoelectric Lunar Dust Removal Actuator, Praneeth Uddarraju

Masters Theses

"This work presents a reconfigurable phase-locked loop (PLL)-based control system for the resonant excitation of piezoelectric actuators aimed at automated removal of particulate contaminants from photovoltaic (PV) surfaces—particularly in extraterrestrial environments such as the lunar surface. Regolith or lunar dust buildup on solar panels is a serious hazard to the effectiveness of energy harvesting on extended missions. By using high-frequency structural excitation and inertial forces the suggested system removes surface impurities. Tunable Sallen-Key low-pass filters for reliable feedback conditioning are used in conjunction with a digitally implemented PLL on an FPGA (XLR8 platform) to precisely lock the drive frequency to …

Enabling Drone-Integrated Active Microwave Thermography Via A Slot Antenna Design, Alec P. Fitzmaurice

Masters Theses

Civil infrastructure inspection quality and inspector safety may be enhanced from the advancement in the capabilities of nondestructive testing and evaluation of remote or otherwise hard-to-reach areas such as nuclear power plants, wind turbines, bridges, or other civil infrastructure using drone-based Active Microwave Thermography (AMT). AMT is a nondestructive testing technique that utilizes high frequency energy (often radiated from an antenna) to induce heating in a specimen. Following this thermal excitation, an infrared camera is used to measure the resulting surface thermal profile. From this, defect indications may be detected. To enable drone-based deployment of AMT, where the antenna size …

Perspectives Of Corporate Instructional Design Experts On Effectiveness, Personal Traits And Attributes, And Technology, Thomas A. Gant

Theses and Dissertations

This qualitative phenomenological descriptive study explored corporate instructional design experts' perspectives on effectiveness, personal traits and attributes, and technology that enhance their expertise. Three central themes emerged: "Mastering Instructional Design: The Journey of Continuous Learning and Skill Development," highlighting the importance of mentorship, lifelong learning, and professional development; "Accessing Instructional Design Expertise Through Individual Strengths," emphasizing adaptability, problem-solving, and empathy; and "Navigating Technological Integration and Innovation in Instructional Design," showcasing the transformative role of tools such as virtual reality, learning management systems, and authoring software. Semi-structured interviews conducted via Zoom with 10 corporate instructional designers with at least 10 years …

A Compact Frequency Comb Generator For Large-Format Superconducting Microwave Kinetic Inductance Detectors, Sungyoun Seo

Open Access Master's Theses

Microwave Kinetic Inductance Detectors (MKIDs) are promising superconducting detectors that achieve superior sensitivity to silicon-based photo detectors by leveraging a small bandgap of superconductors. They are advantageous for sensitive imaging instruments, particularly space telescopes. However, a large-format array with several hundreds of thousands of detectors is required for large-scale observations in space, and it encounters multiple challenges. The biggest challenge is the absence of compact, energy-efficient, and radiation-tolerant readout solutions. Of multiple functions in the MKID readout, the new frequency comb generator is presented in this thesis. It features a low on-chip memory requirement while promising the relaxed frequency resolution …

Nanotube Spectral Fingerprinting And Machine Learning For Optimized Bioimaging/Sensing And Disease Detection Applications In Als, Rodrigo Monroy Lopez

Open Access Master's Theses

Single-walled carbon nanotubes (SWCNTs) possess unique physicochemical and optical properties that make them ideal candidates for biomedical imaging, biosensing, and disease diagnostics. This thesis explores the potential of SWCNT-based spectral fingerprinting combined with ML (Machine Learning) algorithms to optimize bioimaging, disease detection and prediction, with a specific focus on differentiating between healthy and amyotrophic lateral sclerosis (ALS) lymphoblastic patient samples. By functionalizing SWCNTs with single-stranded DNA, we enhance their stability and target specificity, enabling their application in serum patient samples.

A comprehensive spectral analysis of DNA-SWCNTs was conducted using near-infrared fluorescence spectroscopy and other characterization techniques, including UV-Vis-absorption spectroscopy. The …

Impacts Of A Multi-Layered Acousto-Elastic Bottom On Sound Propagation In A Seamount Environment, Haley H. Green

Open Access Master's Theses

The New England Seamounts Acoustics (NEMSA) experiment is a comprehensive oceanographic field study aimed at investigating underwater acoustic propagation and scattering effects within a complex marine environment. The primary objective of this research is to assess the influence of seafloor and sub-bottom geoacoustic properties on acoustic propagation, signal reflections, and transmission loss at Atlantis II Seamount. Two acoustic models, BOUNCE and BELLHOP, were employed to incorporate elastic wave effects within the sub-bottom layers and facilitate the analysis of range-dependent bathymetric features. Two model scenarios were analyzed and compared, one with a layered elastic bottom and another with a fluid bottom …

Psychosocial Determinants Of Public Transportation Use Among Brazilian And American Users: An Integrated Modeling Approach, Ingrid Luiza Neto, Hartmut Günther, Bryan E. Porter, Taciano L. Milfont, Pastor Willy Gonzales Taco, Caroline Cardoso Machado

Psychology Faculty Publications

Overreliance on cars can promote individual, environmental, economic and social problems, requiring the development of measures to reduce car use and encourage the use of more sustainable transport options. Contributing to this call, here we report a cross-cultural study conducted in Brazil (n = 312) and the United States (n = 518) investigating the applicability of the model of Bamberg and Möser in predicting the use of public transport. Results indicated the model is equivalent across samples, regarding both the measures and the relations between the variables of the model. Intention strongly predicted self-reported public transport behaviour, explaining 70% of …

Investigation Into Finops Techniques To Optimise Cost In Aws Cloud Deployments, Denis Parker, Kevin Bayliss

Academic Poster Collection

Investigation Into FinOps Techniques To Optimise Cost in AWS Cloud Deployments