Digital Commons Network^™

Collection Of Instructional Slides From Molten Salt Electrochemistry Symposium (Moses), Devin Rappleye, Carlos Mejia

Faculty Publications

During the Molten Salt Electrochemistry Symposium (MoSES) on July 30-31, 2025, interactive instruction was given to the attendees including live demonstrations. These slides contain the introductory instructions given for each learning module at MoSES 2025. Please visit https://pyro.byu.edu/moses for more information.

A Novel, Metal-Based Approach To Identify Residences With Lead Service Lines, Danielle Land, Grant D. Brown, David M. Cwiertny, Marc A. Edwards, Mona Hanna, Drew E. Latta, Michelle M. Scherer

Michigan Tech Publications

There is an urgent need for rapid, cost-effective approaches to identify residences with lead service lines (LSLs). We evaluated whether analyzing water for corrosion-related metals could accurately identify residences with LSLs without relying on potentially inaccurate property records. We applied principal component analysis logistic regression (PCA-LR) and classification tree models using 28 analytes per bottle (including Pb, Cu, Zn, Fe, Al, and others) measured in 216 water samples collected in Flint, Michigan, in August 2015. The PCA-LR model achieved 87% accuracy (AUROC = 0.93) with 81% sensitivity and 90% specificity, while the classification tree model achieved 80% accuracy (AUROC = …

Predicted Inelastic Response Of Conventional And Ductile Steel Concentrically Braced Frame Buildings Under Wind Loads, Conrad Hamblin Belshe

Theses and Dissertations

The inelastic response of three-story steel concentrically braced frame buildings under wind loads was simulated to determine the applicability of ductile braced frame design to wind load applications. This study examined three types of steel concentrically braced frames: a conventional braced frame, a ductile braced frame, and a ductile braced frame with a reduced beam requirement. Braced frames were designed for four design wind speeds (220 mph, 156 mph, 127 mph, and 110 mph), for a total of nine unique braced frame designs. Nonlinear static pushover analysis was used to determine system overstrength and ductility under wind loads. Eigenvalue vibration …

Investigation Into Intraocular Pressure Distribution Via Computer Aided Engineering (Cae), Madison Maureen Hinman

Masters Theses

The leading cause for irreversible blindness and vision loss is glaucoma - an eye condition associated with elevated intraocular pressure (IOP). Increased IOP is also seen during other pathological conditions like spaceflight-associated neuro-ocular syndrome (SANS), and non-pathological conditions as when playing a wind instrument. The study aimed to describe the influence of different vitreous cavity size as well as vitreous fluid viscosity on the IOP as measured at the back of the eye on the retina. Improved understanding of eye pressure transmission can aid in a better understanding of eye diseases. The experiment conducted included cavities of varying size and …

Wireless Sensor Networks In Renewable Energy Monitoring: A Comprehensive Survey Of Protocols And Applications, Atheer Yousif Oudah, Lina M. Shaker

AUIQ Technical Engineering Science

The global shift to sustainable energy has heightened the demand for smart, robust, and efficient monitoring systems. Wireless Sensor Networks (WSNs) play a key role by enabling real-time data collection, decentralized control, and flexible communication in renewable energy applications. This review presents a comprehensive analysis of WSN architectures, routing protocols, and deployment strategies tailored to photovoltaic (PV) arrays, wind energy systems, hydroelectric plants, and smart microgrids. Core operational challenges are examined through a critical evaluation of energy-aware routing protocols including LEACH, PEGASIS, TEEN, ZRP, and advanced variants like EE-OLEACH and PT-Hybrid. Real-world applications, such as offshore wind farms, rooftop PV …

Corneal Elevation Maps Patterns Classification Using Correlation Method, Sura M. Ahmed, Nebras H. Ghaeb, Salman Yussof, Noor T. Al-Sharify, Husam Yahya Nser, Zainab T. Al-Sharify, Ong Hang See, Leong Yeng Weng

Iraqi Journal for Computer Science and Mathematics

The ophthalmologist uses various techniques to diagnose corneal abnormalities, including corneal topography and tomography devices. Currently generated color corneal elevation surface maps from topographic imaging devices are essential for detecting ocular diseases, while accurately classifying these maps to differentiate between different shapes remains an issue. This study aims to assess and compare parameters of the front and back corneal surface elevation map patterns of normal/abnormal corneas. Two hundred cases were randomly taken (100 normal and 100 abnormal) with a single normal reference image, and then an additional 25 cases were added later for the optimization process. The preprocessing of all …

Retracted: Comparative Study Based On Continuous Analysis Of Autism Spectrum Disorder Using Advanced Deep Learning With Model Interpretability Insights, Ayan Sar, Hussain Falih Mahdi, Sumit Aich, Pranav Singh, Tanupriya Choudhury

Iraqi Journal for Computer Science and Mathematics

Hysterical conversion has similar cognition and behaviours to those in the case of ASD; it is, therefore, complex when diagnosing and classifying the condition. The majority of employed diagnostic tests are cross-sectional and fail to describe the developmental and clinical features of ASD; for this reason, they are pretty inaccurate in the diagnosis of ASD and thus cause disparities in the efficiency of the therapeutic interventions used. The present study's research contribution is a new application of deep learning that aims to analyse the spectrum of ASD with gradient-based classifications. In this case, we use a DL model trained on …

Predicting Leakage From Nuclear Material Containers At Los Alamos National Laboratory Through Drop Testing, Leak Testing, Finite Element Analysis And Digital Image Correlation, Jude M. Oka, Yu-Lin Shen, Osman Anderoglu, Pankaj Kumar, Rajendra Vaidya

Mechanical Engineering ETDs

Los Alamos National Laboratory (LANL) relies on containment vessels to safely manage special nuclear material. These containers are subject to rigorous testing—such as drop, fire, and water ingress testing—to ensure integrity under adverse conditions. While elastomer-based seals are well studied, metal-to-metal sealing mechanisms remain under investigation, particularly under dynamic loading. This research focuses on the relationship between container mating surfaces and impact loading through drop testing. Finite Element Analysis (FEA) models were developed and validated using Digital Image Correlation (DIC) to measure strain during impact. Drop tests at varying heights showed strong correlation between FEA and DIC results, confirming the …

Networked Systems: Synchronization, Decomposition And Transient Dynamics, Amirhossein Nazerian

Mechanical Engineering ETDs

This dissertation investigates synchronization, transient dynamics, control, and signal amplification in networked dynamical systems. First, it examines complete and cluster synchronization, including cases with large parametric mismatches, in both natural (e.g., brain networks, fireflies) and technological systems (e.g., power grids, robotics). Second, it studies transient dynamics in consensus processes, designing synchronization strategies that link reactivity, contraction theory, and Lyapunov exponents. Third, it addresses the computational limits of Model Predictive Control (MPC) for large networks by introducing an algebraic decomposition method that enables parallel online computation of smaller subproblems, enhancing MPC performance under hardware constraints. Finally, it analyzes the structural role …

Instability Analysis In Cylindrical Thin Film–Compliant Core Structures: Numerical Simulations And Effects Of Inelastic Deformation, Md Al Rifat Anan

Mechanical Engineering ETDs

When a thin film bonded to a thick compliant substrate is subject to in-plane compression, wrinkles can develop if the critical state for instability is reached. In various applications the film/substrate system may also take the form of cylindrical fibers, where an axial compressive loading can trigger axisymmetric wrinkles. A straightforward computational approach to simulate such wrinkling behavior is needed for material design, to either prevent wrinkling or to exploit its benefits for flexible device applications. In this work a comprehensive numerical study is undertaken by employing the finite element method. The embedded imperfection approach used previously for planar structures …

Multiscale And Multi-Model Studies Of Metal Plasticity, Luo Li

Mechanical Engineering ETDs

Plastic deformation is the process in which the material deforms permanently due to external effects. Twinning and slip are two main mechanisms of plastic deformation in metallic materials. The prominent mechanism of plastic deformation in metals that have FCC crystal structures is slip or gliding movement of dislocations, which is mainly focused on here. In the current study, frameworks for investigating plasticity phenomena of metals at different scales ranging from microscale to macroscale are demonstrated. Specifically, the macroscale modeling of plastic response of metallic materials induced by indentations are emulated by nonlinear FEA simulations. Simulation results of macroscale modeling are …

Understanding The Metallic And Oxide Phases In Platinum-Based Bimetallic Heterogeneous Catalysts After High-Temperature Oxidation, Stephen John Porter Jr

Nanoscience and Microsystems ETDs

Platinum (Pt) and palladium (Pd) are critical components in diesel emission control systems, enabling the conversion of harmful pollutants under demanding conditions. However, Pt’s effectiveness is hindered by sintering under high-temperature oxidizing environments. This dissertation investigates how Pt and Pd evolve under oxidizing conditions at 800°C, highlighting their distinct thermodynamic behaviors and interactions. Using TEM, EDS, EELS, XRF, XRD, and EXAFS, we show that Pd suppresses Pt sintering by reducing the volatility of PtO₂, leading to the formation of stable particles. Both Pt and Pd are present in metallic and oxide states, forming biphasic 'Janus' particles with conjoined metal and …

Improving Infiltration Model Performance In Arid And Urban Regions, Samuel Stephen Coulter

Civil Engineering ETDs

Flooding in arid regions is infrequent but damaging and limited historical data makes flood modeling an important tool for flood infrastructure design. This study improves flood modeling guidance by using plot-scale tests to determine the impact of slope, compaction, gravel mulch and landscape fabric on infiltration and runoff rates in sandy soil types. This data will be used as guidance for the linear and constant model. The performance of this model was compared with the curve number model for a hypothetical 100-year design storm. Results showed that gravel mulch increased infiltration rates by 66% and reduced erosion on steep and …

Advancements In Microarray Manufacturing Enable Emerging Technologies, Kendall Hoff

Biomedical Engineering ETDs

Significant advances in manufacturing technologies have enabled the production of new DNA microarrays for use in emergent technology. Photolithography, wafer scale manufacturing, and improvements in synthesis chemistry and design enable high-throughput production of extremely high-quality arrays. These new arrays offer extremely high oligonucleotide densities, in the range of tens of thousands of oligonucleotides per square micron. They also offer smaller features sizes, with millions of features per square centimeter. Furthermore, they can be manufactured with the DNA tethered at either end to the surface, leaving either the 5’ or 3’ end free and available for use in enzymatic reactions; and …

Optimization And Model Averaging Of Histogram-Based Place Cell Firing Rate Maps Using The Point Process Framework, Murat Okatan

Turkish Journal of Electrical Engineering and Computer Sciences

The firing rate of hippocampal place cells depends on the spatial position of the organism in an environment. This position dependence is often quantified by constructing spike-in-location and time-in-location histograms, the ratio of which yields a firing rate map. The purpose of this study is to present a new method for optimizing the spatial resolution of histogram-based firing rate maps. It is pointed out that histogram-based firing rate maps are conditional intensity functions of inhomogeneous Poisson process models of neural spike trains, and, as such, they can be optimized through model selection within the point process framework. The point process …

Isar Imaging Of Drone Swarms At 77 Ghz, Remzi̇ye Büşra Çoruk, Ali̇ Kara, Eli̇f Aydin

Turkish Journal of Electrical Engineering and Computer Sciences

The proliferation of easily available, internet-purchased drones, coupled with the emergence of coordinated drone swarms, poses a significant security threat for airspace. Detecting these swarms is crucial to prevent potential accidents, criminal misuse, and airspace disruptions. This paper proposes a novel inverse synthetic aperture radar (ISAR) imaging technique for high-resolution reconstruction of drone swarms at 77 GHz millimeter wave (mmWave) frequency, offering a valuable tool for military and defense anti-drone systems. The key parameters affecting down-range and cross-range resolution (0.05 m), ultimately enabling the generation of detailed ISAR images are discussed. Here, we create diverse scenarios encompassing various swarm formations, …

Rescon: Residual Consistency For Real-World Super-Resolution, Erdi̇ Saritaş, Hazim Kemal Ekenel

Turkish Journal of Electrical Engineering and Computer Sciences

Real-world super-resolution is a highly challenging problem in the field of computer vision. Besides enhancing image resolution and improving visual details, information loss due to complex real-world degradations is desired to be restored. One of the primary hardness of this problem is finding sufficiently large paired datasets for training. Researchers have developed techniques that generate synthetic low-resolution pairs using high-resolution images with a generative adversarial network-based degradation generator to address this issue. In these approaches, the degradation generator is trained by utilizing real-world low-resolution images as the target domain, generating a degraded low-resolution counterpart of the high-resolution input. However, in …

Flight Instructor Enhanced Qualification Training Program, Brendan Aug

Aviation Student Publications

Due to December 2024 regulatory changes made to 14 CFR Part 61.195(h)— Qualifications to provide ground or flight training to initial flight instructor applicants—a new training program, titled the Flight Instructor Enhanced Qualification Training Program (FIEQTP), must be developed under 61.195(h)(3).

The purpose of this packet is, in response to regulatory changes, to conduct a thorough training needs analysis, and utilizing its conclusions, develop a new 14 CFR Part 141 course and assessment plan that meets the requirements of Part 61.195(h)(3) Flight instructor enhanced qualification training program.

A Multi-Scale Numerical Analysis Of Wave Propagation Through Coastal Vegetation Using Proteus & Xbeach, Cole M. Statler

LSU Master's Theses

Coastal vegetation attenuates waves in the nearshore zone and protects shorelines from storm surge and wave action. It also traps nutrients and sediment, and participates in the formation of land over longer time scales. These features of vegetation make it a common component of nature-based engineering projects. Interaction of water waves and flow with vegetation, however, can involve unsteady and turbulent flow, non-hyrdostatic pressure effects, and air entrainment that can hinder the use of simple parametric representations of vegetation drag. XBeach, a one- and two-dimensional production model applies reduced-order methods, prioritizing computational efficiency. Vegetation is represented in XBeach as a …

Optimal Water Hammer Protection Strategies For Low-Head Hydraulic Systems: A Case Study Using Bentley Hammer, Ahmed A. Abdel-Naby, Mostafa A. Abdel-Moaty, Eslam R. Lotfy

Mansoura Engineering Journal

The analysis of water hammer in low-head hydraulic systems holds significant importance compared to that in high-head systems, particularly given instances where Thorley’s equation may fall short in providing accurate pump inertia values. In situations where manufacturer data are unavailable, proactive measures to mitigate potential hammering incidents become imperative. While Bentley HAMMER software provides robust simulation capabilities, optimal protection strategies for low-head systems remain underexplored. This case study focuses on a scenario involving multistage centrifugal pumps that lift water from the basement floor of a building to its roof via a polypropylene pipeline. The investigation revealed a novel configuration: relocating …

Detection Of Oil Pollution On The Tigris River In Iraq Using Fluorescence And Reflecting Techniques, Ahmad K. Ahmad, Thamer M. Mohammed

Karbala International Journal of Modern Science

In this study, a broadband light source (visible and ultraviolet) was used to name minerals via fluorescence spectra and estimate slick oil thickness, ranging from sub-millimetres, using the reflecting spectrum technique. Using a fluorescent technique, we obtained fluorescence spectra of the samples, converting and processing the signals to produce high-resolution data, which enabled the identification of the types of dissolved elements and oil slicks in the Tigris River, highlighting pollution sources and potential control measures. This system aims to show the faint signal in fluorescence samples collected from the cooling system outlet water throughout the refining process from AL-Dora (Baghdad) …

Multi-Scale Color Correction And Contrast Enhancement Via Leaf In Wind Optimization For Improved Weld Defect Detection In Non- Destructive Testing, Senthil Anand N Mr

Theses and Dissertations

Image enhancement is an essential process in numerous fields, including industrial inspection, medical imaging, remote sensing, and photography, as it improves image quality for accurate analysis and interpretation. Among the advanced image enhancement techniques, Focused Super Resolution (FSR) with Self-Attention Single Candidate Optimizer-based Generative Adversarial Networks (GANs) is specifically designed for weld defect detection, while Advanced Image Enhancement through Multi-scale Color Correction and Contrast Stretching using Leaf in Wind Optimization focuses on enhancing the overall visual quality of images. Although both approaches aim to improve image quality, they differ significantly in their objectives and application areas. The FSR method concentrates …

Efficient Small Tool Detection In Construction Via Lightweight Deep Neural Networks, Maryam Soleymani

LSU Master's Theses

Construction sites are dynamic and inherently hazardous environments, where small hand tools—although essential—pose serious safety risks due to their frequent use, portability, and tendency to be misplaced or dropped. This study introduces a novel and lightweight deep learning-based architecture, Lightweight Small Tool Detection (LSTD), specifically designed for fast detection of small tools in unstructured and challenging construction environments. Recognizing that small object detection remains a persistent limitation in existing computer vision models, particularly under poor lighting or cluttered backgrounds, LSTD integrates advanced modules for enhanced feature extraction, fusion, and classification. It achieves notable improvements in accuracy, recall, and computational efficiency …

Stead: Spatio-Temporal Efficient Anomaly Detection For Time And Compute Sensitive Applications, Andrew Gao

Master's Theses

This paper presents a new method for anomaly detection in automated systems with time and compute sensitive requirements, with unparalleled efficiency. As these systems become increasingly popular, ensuring their safety has become more important than ever. Therefore, this paper focuses on how to quickly and effectively detect various anomalies in the aforementioned systems, with the goal of making them safer and more effective. Many detection systems have been developed with great success under spatial contexts; however, there is still significant room for improvement when it comes to temporal context. While there is substantial work regarding this task, there is minimal …

Quantum Algorithm Emulation Using Fpgas, Samuel Petruescu

Master's Theses

Field Programmable Gate Arrays (FPGAs) have been used in most of the physics sub-fields for various unique purposes. This includes particle physics, quantum optics, and, more recently, quantum computing. FPGAs boast many benefits over previous experimental and computational setups. They are versatile, easy to program, and cost-effective, leading to an understandable desire to incorporate them into the new field of quantum computing. While FPGAs have been used to help control the readout and control of physical qubits, they can also be a good tool for improving algorithm simulations, which is the focus of this paper. Different algorithms have different computational …

Using Facial Recognition For Selective Pose Detection, William J. Parker

Master's Theses

Pose detection involves locating and identifying key body points for all individuals within a frame. This enables the ability to convert the pose into a digital format, which can then be recorded and analyzed for a variety of purposes. Advancements in the field have already opened applications in areas such as digital fitness coaches, fall detection, and virtual reality. Existing approaches primarily focus on tracking all detected individuals, which limits the practical applications when attempting to analyze a single or specific subject when there are other people in frame. Previous work has discussed integrating identification, but these approaches use identification …

Sirilla: Predicting Traffic Flow Via Stacked Decentralized Federated Learning, Andrew Selvia

Master's Theses

Billions of people today rely on traffic predictions to optimize their travels. Digital mapping services deliver accurate predictions by learning from vast troves of historical data. Impressive as these systems are, their assumptions do not always apply. They depend on an endless flow of sensitive user data to a central authority, a stable Internet connection, and trustworthiness on both sides of the traditional client-server model. This thesis explores a novel architecture which bucks those assumptions. In the proposed model, traffic data remains on edge devices which individually train models via federated learning. Beyond the obvious privacy benefits, this architecture enables …

Sbv_Dps: A Stacking-Bagging-Voting Nested Ensemble Based Diabetes Prediction System Using K-Fold Cross Validation, Sourabh Shastri, Sachin Kumar, Paramjit Kour, Vibhakar Mansotra

Mansoura Engineering Journal

With the advancement of machine learning techniques, the introduction of the most accurate model has become a necessity. In real-world scenarios, every model has some constraints and assimilates errors, so their performance is not always highly efficient; this sparked the development of ensemble learning. The ensemble approach aims to consolidate the strengths of existing approaches and minimize their weaknesses or decision-making risks. The proposed diabetes prediction system encases a resampling filter, applied to balance the dataset and model builder method, i.e., without the SBV ensemble and with the SBV ensemble method. The model is initially built without using the SBV …

Investigating The Impact Of Agent Openness On Planning In Multi-Agent Systems, Bala Subramanyam Duggirala

School of Computing: Dissertations, Theses, and Student Research

Multi-agent systems (MAS) possess significant potential for modeling real-world scenarios requiring coordinated actions (like wildfire fighting or ridesharing) among autonomous entities or agents (e.g., wildfire fighting agents) in complex, dynamic environments. Effective decision-theoretic planning (where each agent must carefully consider both the immediate and the future situations or states, and coordinate with the other agents (neighbors) to evaluate what needs to be done at present) within MAS, especially multiagent planning, where the planning agent directly models its neighbors in order to estimate their optimal actions, is critical, yet challenged by factors like partial observability, openness, and diverse agent types with …

Dynamic Sparsification In Secure Gradient Aggregation For Federated Learning, Bikash Samanta

Master’s Dissertations

Secure aggregation is a critical component of privacy-preserving federated learning. However, existing fixed-sparsity approaches often incur unnecessary communication overhead. We present DynamicSecAgg, a novel framework that introduces dynamic sparsity while preserving coordinate-level privacy. Our method achieves significant improvements in communication efficiency while maintaining — and in some cases improving — model accuracy across both IID and non-IID user distributions. The framework maintains information-theoretic privacy guarantees via adaptive gradient thresholding and polynomial-based aggregation, proving particularly effective under heterogeneous data settings. These results establish dynamic sparsity as a key optimization for efficient and privacy-preserving federated learning.