Engineering Commons^™

Investigation Of Synergistic Effect Between Polystyrene And Polyethylene Under Conventional Thermal Heating And Microwave Heating, Thang Luong

Graduate Theses, Dissertations, and Problem Reports (ETD)

Single-use plastics (Low Density Polyethylene, LDPE; Polystyrene, PS; Polypropylene, PP) are increasingly used in the modern world, with their usage growing every year. An effective method to manage the resulting waste is urgently needed, as landfilling and incineration have proven harmful to the environment in the long term. Mechanical recycling may not maintain the desirable characteristics of the single-use plastics through several cycles. Pyrolysis emerges as a promising approach to address plastic waste. Given that single-use plastic waste often comes in a mixture, combining plastic in the feedstock is a viable solution to effectively convert these polymers altogether to gain …

Dynamic Load Identification Using Optimal Sensor Placement And Dynamic Condensation Methods, Iole Pecora

Graduate Theses, Dissertations, and Problem Reports (ETD)

Knowledge of excitation loads that structures experience during their service life is pivotal in different engineering fields, not only from a structural design optimization point of view but also as prevention of possible damages to the structures themselves. However, in case of dynamic events such as tornadoes, structures subjected to impulsive load due to their vicinity of explosions, the excitation load cannot be directly determined through direct measurements. In these scenarios, the inverse problem is used, and it is called load identification. This type of problem tries to determine the excitation load knowing the system response through a series of …

Application Of Predictive Control Strategies For Water-Gas Shift Membrane Reactors Using Data-Driven Models, Bernardo De Oliveira Vecchio

Graduate Theses, Dissertations, and Problem Reports (ETD)

As demand for more efficient processes keeps rising and more restrictive environmental legislation requires higher levels of both yield and purity, the process industry has now, more than ever, been looking for new ways to achieve these goals. One approach has been the implementation of Process Intensification (PI). PI aims to combine multiple unit operations into a single one, promoting efficiency gains on multiple levels. This combination, however, leads to complex process dynamics, and controlling such processes, particularly when setup as multi-input-multi-output (MIMO) systems, presents a great challenge due to highly interactive complex process dynamics and the imposition of many …

An Approach For Robotic Pollination That Utilizes Imitation Learning, Ronald Michael Butts Ii

Graduate Theses, Dissertations, and Problem Reports (ETD)

The global decline in pollinator populations poses a significant threat to agriculture, motivating the development of robotic pollination systems. Previous works demonstrated successful robotic pollination of bramble flowers using visual servoing; however, pollination was limited to specific flower orientations. As such, the objective of this work is to develop a robotic pollination system that is capable of pollinating a wider range of orientations.

This research introduces an imitation learning-based framework for robotic pollination that positions the manipulator to view chosen flowers in specific orientations. The developed model leverages object detection (YOLOv8) to identify individual flowers and a convolutional neural network …

Autonomous Object Search Planning In Large-Scale Environments, Matthew A. Collins

Graduate Theses, Dissertations, and Problem Reports (ETD)

The advancement of autonomous search holds significant promise for applications ranging from emergency response to planetary exploration. This thesis investigates strategies to enhance autonomous search performance in large-scale environments. The main contribution of this work is its practical application in real-world scenarios, where efficient search methods are essential for managing vast amounts of data, particularly in large environments. Effective search planning requires navigating complexities such as limited prior information and managing large state spaces, necessitating advanced strategies to plan with this limited information. Additionally, balancing exploration and exploitation is crucial for optimizing the search process, as it ensures thorough coverage …

An Investigation Of The Performance Of A 140 Kw Solar Panel In West Virginia, Rumana Subnom

Graduate Theses, Dissertations, and Problem Reports (ETD)

Solar panels are recognized as a viable technology for producing electricity from sunlight. The performance of a solar panel is influenced by factors such as solar irradiance, tilt angle, orientation, shading, panel age, degradation, and various environmental conditions including ambient air temperature, humidity, dust, soil, and snow.

In this research, a mobile solar panel testing system consisting of a mobile cart, a solar panel, and a portable power station was designed and fabricated to evaluate the performance of a solar panel. The battery is equipped with a thermal management system controlling its temperature and charging and discharging system. The current …

Changes In Psychiatric Diagnosis Associated With Sars-Cov-2 Infection And Predicting The Development Of New Psychiatric Illness In Covid Patients By Using Machine Learning Approach: A Study Using The Us National Covid Cohort Collaborative (N3c), Asif Rahman

Graduate Theses, Dissertations, and Problem Reports (ETD)

The enduring impact of COVID-19 extends beyond acute illness, with potential long-term psychiatric consequences raising significant concern among healthcare professionals and researchers alike. Emerging evidence suggests a multifaceted relationship between COVID-19 and the development of different psychiatric illnesses like Schizophrenia Spectrum and Psychotic Disorders (SSPD), Depression, Bipolar disorder, Personality disorder, Trauma, and a range of other mental health conditions. Considering these emerging connections, our study endeavors to rigorously assess the associations between COVID-19 and various psychiatric illnesses while simultaneously employing machine learning techniques to predict the development of new psychiatric disorders in individuals affected by the virus. Leveraging the extensive …

A Domain Adaptation Approach For Morphology-Independent Cell Instance Segmentation, Voke Rotimi Brume

Graduate Theses, Dissertations, and Problem Reports (ETD)

In recent years, there has been an upward trend of utilizing deep learning to automate cell segmentation processes. As global storage capacities grow exponentially, so have microscopy data collections become larger and more frequent. To benefit from them, accurate and precise quantitative analysis tools like cell instance segmentation have become necessary. However, the highly variable nature of these data collections necessitates retraining segmentation models to maintain high accuracy on new data collections. This process is time-consuming and labor-intensive since a user must annotate much of the new data, usually under the supervision of a medical professional. The problem is further …

Real-Time Cyber-Power Testbed Enhancement And Synchrophasor Data Generation For Anomaly Detection Using Physics-Informed Machine Learning, Vasavi Sivaramakrishnan

Graduate Theses, Dissertations, and Problem Reports (ETD)

Advanced sensing and automation are essential to managing the evolving electric power system with tight coupling of information and power system layer. However, this increasing number of cyber-physical devices brings vulnerabilities from cyber threats and extreme weather events can endanger the power system on a physical level as well. Advanced monitoring and control algorithms with human operators in the loop are needed to enable power system resiliency despite these increasing threats. These advanced algorithms require validation using a realistic test system that mimics real-world scenarios.

This work focuses on a) developing a realistic real-time cyber-power testbed with hardware-in-the-loop to generate …

Cellular Level Changes Induced In Cancer Cells Due To Microgravity, Sai Deepika Reddy Yaram

Graduate Theses, Dissertations, and Problem Reports (ETD)

The increase in human activity in space has revealed several kinds of physiological challenges brought on by the absence of Earth's gravitational pull. NASA observed that during spaceflight, astronauts experience a 1-1.5% monthly loss in the mineral density of weight-bearing bones, with rehabilitation efforts on Earth often proving ineffective. This issue extends to muscles, the neuro vestibular system, the cardiovascular system, and vision. Cancer has emerged as a significant cause of mortality among astronauts, with studies up to 2017 showing that 41.3% of natural cause deaths among U.S. astronauts were due to cancer, primarily due to space radiation exposure. Cancer …

Investigation Of Space Charge Effects On Co2 Electrocatalytic Reduction On Gd-Doped Ceria Via Scanning Kelvin Probe And Model-Based Bayesian Analysis, Alejandro Mejia

Graduate Theses, Dissertations, and Problem Reports (ETD)

In studying novel energy conversion and storage systems, such as high-temperature electrolysis, numerous underlying fundamental physical processes remain unclear or inadequately understood. Among these, the modeling and comprehension of surface reaction mechanisms, coupled with the intricate effects of space‑charge interfaces, remains an unclear and challenging area of research.

The work of this dissertation involves the development of a 2D finite element analysis model, leveraging the robust MOOSE framework from INL. This model, featuring inhomogeneous defect thermodynamics for near-surface chemistry, formulated through Poisson‑Cahn variational theory, has been exploited for studying the electrocatalytic reduction of CO₂ on gadolinia doped ceria. The …

Data-Driven Modeling Of Oxygen Kinetics In La0.6sr0.4co0.2fe0.8o3−Δ (Lscf) For High-Temperature Reduction Of Co2 In An Electrolysis Cell, Ferron Campbell

Graduate Theses, Dissertations, and Problem Reports (ETD)

Electrolysis systems are critical to several societal applications, particularly energy storage and conversion. Developing these systems requires a detailed knowledge of the chemistry and thermodynamics of the materials used in the electrolysis cell. This work focuses on using embedded scientific machine learning as an efficient way to build an interpretable model for the reaction and transport kinetics in the LSCF electrode, whose performance directly influences the electrolysis system’s performance. The models developed in this study are trained using the publicly available machine learning package, FoKL-GP. This package incorporates a robust Gibbs sampler that employs a forward variable selection process to …

Enhancing Robotic Exploration Through Semantically-Guided Sampling Strategies, Christopher Alexander Arend Tatsch

Graduate Theses, Dissertations, and Problem Reports (ETD)

From space and deep-sea exploration to disaster response and environmental monitoring, autonomous robots are essential for advancing science, improving safety, and addressing critical challenges. This dissertation introduces a novel open-source strategy for autonomous robotic exploration: the Semantically-Guided Exploration (SGE) framework. Designed for ground vehicles, SGE integrates semantic understanding into the autonomous exploration process, improving decision-making in complex environments. Specifically, the proposed sampling-based approach uses the information from the semantic segmentation of RGB images and depth images to guide the robot's selection of exploration goals. This method enables the robot to steer away from potential dangers such as large rocks and …

Dough Rheology And Its Influence On Sheeting Behavior, Najat Albarakati

Graduate Theses, Dissertations, and Problem Reports (ETD)

Dough is the starting material for a large number of baked products, including cookies, crackers and bread. In commercial food processing operations, it is desired to obtain the same product and with the same dimensions in a reproducible manner in order to minimize waste. In the case of dough, the flour used, and the nature and amount of ingredients employed depend on the specific product and the market served. This research was aimed at relating cracker dough rheology to sheeting behavior between two counter-rotating rollers. The sheet that is formed is used to punch out the crackers that are then …

Machine Learning-Assisted Multiscale Simulation And Design Optimization Of Composite Jackets Under Low-Velocity Impacts, Masoud Mohammadi

Graduate Theses, Dissertations, and Problem Reports (ETD)

This research presents the development of a data-driven machine learning-assisted approach to simulate and optimize the design of composite materials subjected to low-velocity impacts. It focuses on a specific type of hybrid composite comprised of fiberglass and Kevlar fabrics stitched with Kevlar threads. The study begins by creating a multiscale finite element simulation for the composite under a low-velocity impact, which operates across three scales: microscale, mesoscale, and macroscale. This simulation accepts various inputs, such as different layer configurations and orientations, and provides impact outputs including maximum load and energy absorption capacity and displacement at failure.

Python and MATLAB scripts …

Processing, Stability, And High-Temperature Properties Of Doped Lacro3-Based Refractory Ceramics And Composites For Harsh Environments Sensing Applications, Javier A. Mena

Graduate Theses, Dissertations, and Problem Reports (ETD)

In order to test and monitor the operational stability and conditions of various energy, transportation, and manufacturing systems and their components, accurate sensors capable of operating at temperatures over 1000 °C in various environments for long durations are required. In addition, many of these harsh environmental systems do not permit sensors to be directly inserted into the environment, so the sensors need to be embedded into the surrounding support or thermal protective materials. Some technological and industrial applications that require the use of harsh environment conditions sensing include nuclear and chemical reactors, jet engines, heavyduty gas turbines, rotating bearings in …

Development Of Dynamic Modeling And Estimation Techniques For Condition Monitoring Of Advanced Energy Systems, Vivek Saini

Graduate Theses, Dissertations, and Problem Reports (ETD)

The integration of renewable energy sources into the electric grid requires the current fleet of fossil-fired power plants to operate more flexibly, leading to frequent load changes that stress critical high temperature boiler components that were primarily designed for base load operations. The more complex operating scenarios can modify component damage, compromising reliability and increasing operational costs. To ensure efficient plant operations, adaptive condition monitoring tools generalizable for different plant configurations are essential for recognizing the impacts of load-following, improving safety, and preventing outages. This dissertation work is primarily focused on the development of advanced modeling and estimation techniques frameworks …

Fingerphoto Deblurring Using Wavelet Style Transfer, David Connard Keaton

Graduate Theses, Dissertations, and Problem Reports (ETD)

This work focuses on a deblurring network designed specifically for the task of deblurring contactless fingerprints, a.k.a fingerphotos. This network takes the general idea of style transfer, and applies it to the realm of deblurring. The standard use case for style transfer networks is artistic style transfer, which is used for recreational purposes. For this work, though, style transfer is used in the context of deblurring. Since style transfer can transfer artistic styles from one image to another, who's to say it can’t transfer clarity and sharpness as well? This is the focus of this work; taking a blurry fingerphoto, …

Static Response Of Frp Structural Systems – Piles, Platforms, And Poles, Manish Adhikari

Graduate Theses, Dissertations, and Problem Reports (ETD)

This study addresses the static response of three Fiber Reinforced Polymer (FRP) structural systems (piles, platforms, and poles) under static loads. This research aims to improve safety and sustainability in modern infrastructure by bridging the knowledge gap currently that exists between the experimental behavior and theoretical predictions.

FRP round piles (18-inch in diameter) were tested under axial compression, shear, four-point bending and fatigue. Both the load-deflection and stress-strain responses were analyzed. Coupon tests were conducted and related to the outcomes of full-scale test data. Two major differences were observed in the response of the bending test specimens with modulus of …

1d Geo-Mechanical Model Analysis Of The Mip 1s And Drilling Process Optimization In The Deep Appalachian Basin, Georges Brown Liwuitekong Dongho

Graduate Theses, Dissertations, and Problem Reports (ETD)

The proposed paper assesses the geological and geomechanical characteristics of the geothermal deep direct-use MIP 1S well in the Appalachian basin. The assessment utilizes a comprehensive suite of well logs, sidewall core analysis, and well injection tests to determine continuous elastic and rock strength properties. Stress and pore pressure profiling are conducted, and a validated 1D-geomechanical model is developed. This model undergoes analysis through wellbore stability assessments and comparisons with drilling events. The 1D-geomechanical model demonstrates a high degree of agreement with wellbore observations, revealing suboptimal execution of drilling practices, particularly utilizing mist air drilling up to 8868 feet. This …

Advancing Gfrp Column Design: Strength, Effective Lengths, And Failure Modes, Jack Alan Wykle

Graduate Theses, Dissertations, and Problem Reports (ETD)

Glass fiber reinforced polymer (GFRP) composites have become an increasingly popular choice in construction industry due to their higher strength-to-weight ratio, ease of manufacture including lower Embodied Carbon Factor, and better durability in harsh environmental conditions than conventional structural construction materials. Currently, GFRP composite column design lacks well-established design standards due to the material's unique properties such as lower bending and shear stiffness than steel, differing compressive and tensile moduli, which leads to complexities in computing buckling capacities under local effects such as flange or web buckling and even torsional buckling under off-centered compression loading. Therefore, GFRP columns will behave …

Investigating Critical Mineral Recovery And Carbon Mineralization Potential In Coal Fly Ash, Syabilla Cardosh

Graduate Theses, Dissertations, and Problem Reports (ETD)

Coal fly ash (CFA), a byproduct of coal combustion, represents an innovative opportunity to address the rising demand for critical minerals and the need to reduce CO2 emissions due to its significant concentrations of calcium and magnesium. By providing insights and preliminary data, this study aims to contribute to the foundational understanding necessary for future development.

A multidisciplinary approach was employed to assess CFA’s potential, including detailed chemical and mineralogical characterization using X-ray fluorescence (XRF), inductively coupled plasma mass spectrometry (ICP-MS), X-ray diffraction (XRD), and scanning electron microscopy (SEM). XRD analysis revealed crystalline phases in the CFA samples. At the …

A Multimodal Physical Fatigue Assessment Method Using A Biomarker And Accelerometer-Embedded Wearable Wristband, Md Hadisur Rahman

Graduate Theses, Dissertations, and Problem Reports (ETD)

Physically demanding tasks pose significant challenges to worker health, safety, and productivity across various industrial sectors in the United States. The construction industry is particularly affected due to the labor-intensive nature of its tasks and harsh environmental conditions. The industry suffers from unsatisfactory occupational health and safety records, with physical fatigue being a major contributor. Physical fatigue not only affects individual well-being and workplace safety but also influences productivity and the United States’ economy. Given the high incidence of injuries and accidents in the construction industry, assessing physical fatigue has become critical for improving worker safety and productivity. To address …

Machine Learning Based Intrusion Detection Framework For Can Bus Vulnerabilities In Modern Vehicles, Obinna C. Agbo

Graduate Theses, Dissertations, and Problem Reports (ETD)

The Controller Area Network (CAN) bus is a crucial communication backbone in modern vehicles, connecting various Electronic Control Units (ECUs). However, inherent design weaknesses such as the lack of encryption and authentication make CAN networks vulnerable to cyber-attacks, including spoofing, Denial of Service (DoS), and fuzzing attacks. This thesis thoroughly evaluates these vulnerabilities and the limitations of existing security frameworks like Message Authentication Codes (MACs) and encryption, advocating for the adoption of Intrusion Detection Systems (IDS) as a more practical solution for CAN bus security. The proposed IDS leverages advanced machine learning techniques to accurately detect intrusions, even under complex …

Recovery Of Natural Gas Equipment Emissions Into Gas Compression Engines For The Reduction Of Potential Greenhouse Gas Emissions, John Eric Casto

Graduate Theses, Dissertations, and Problem Reports (ETD)

Since the turn of the millennium, the United States (U.S.) oil and natural gas (ONG) industry has nearly doubled its natural gas production rate. As a result, the ONG industry has recently come under increasing scrutiny for its contributions to greenhouse gas (GHG) emissions. Consequently, various solutions to this problem have been proposed and formulated to reduce the impacts of GHG emissions on the environment. West Virginia University (WVU) have found it important to research the impacts of recovering vented gas streams into prime-mover engines. The U.S. Department of Energy (DOE) and National Energy Technology Laboratory (NETL) have granted WVU …

Polylactic Acid (Pla) Containing Talc Microparticles And Amorphous Polyhydroxyalkanoates (Aphas) For Improved Barrier And Mechanical Properties In Food Packaging, Mohammed Alfaifi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Polylactic acid (PLA) is a biobased and compostable polymer that is increasingly being used as an alternative to petroleum-based, non-biodegradable polymers for single-use food packaging due to its environmental benefits. It is also commercially available in large quantities, and it can be processed like polyethylene. However, it has a higher water-vapor permeability (WVP) as compared to polyolefins and polyethylene terephthalate that are the incumbent materials. This results in a competitive disadvantage in employing PLA for packaging baked goods since the shelf life of the food is likely to be reduced. In the past, barrier properties of PLA were improved by …

Evaluation Of Probable Maximum Precipitation (Pmp) For West Virginia To Predict Current And Future Pmp & Utilizing Acid Mine Drainage (Amd) Sludge In Reclamation, Grace Katherine Kerr

Graduate Theses, Dissertations, and Problem Reports (ETD)

This thesis includes two main topics: 1) evaluation of probable maximum precipitation (PMP) for West Virginia to predict current and future PMP, and 2) utilizing acid mine drainage (AMD) sludge as a reclamation plan.

Probable maximum precipitation (PMP) is essential for dam design as well as for the inspection, operation, maintenance, and repairs of these facilities. West Virginia Department of Environmental Protection Dam Safety utilizes the 6-hr, 10-mi² (26-km²) PMP established by Hydrometeorological Report (HMR) 51 based on the analysis of extreme rainfall. These PMP are outdated because there have been unaccounted for extreme rainfall events that …

Passive Wireless Corrosion And Temperature Detection In High-Temperature Environments, Noah Lane Strader

Graduate Theses, Dissertations, and Problem Reports (ETD)

This work focuses on the theory and development of LC sensors for high temperature and corrosion measurement for stainless steel and copper surfaces with power industry and general corrosion detection applications. The LC resonators were fabricated via screen printing an Ag inductor on an alumina substrate. The LC design was modeled using the ANSYS HFSS modeling package. The LC passive wireless sensors operate with resonant frequencies centered at 85-110 MHz. The wireless response of the LC sensor was interrogated and received by a radio frequency signal generator and spectrum analyzer at temperatures from 50-800 °C for copper ground planes and …

Prediction Of Anomalous Events With Data Augmentation And Hybrid Deep Learning Approach, Ahmed Shoyeb Raihan

Graduate Theses, Dissertations, and Problem Reports (ETD)

In this study, we propose a novel anomaly detection framework designed specifically for Multivariate Time Series (MTS) data, addressing the prevalent challenges in analyzing such complex datasets. The detection of anomalies within MTS data is notably difficult due to the complex interplay of numerous variables, temporal dependencies, and the common issue of class imbalance, where one category significantly outnumbers another. Traditional deep learning (DL) approaches often fall short in simultaneously tackling these issues. Our framework is designed to address these challenges through a two-phased approach. Phase I employs Conditional Tabular Generative Adversarial Networks (CTGAN) to create strategic synthetic data, setting …

Implementing Unmanned Aerial Vehicles To Collect Human Gait Data At Distance And Altitude For Identification And Re-Identification, Donn E. Bartram

Graduate Theses, Dissertations, and Problem Reports (ETD)

Gait patterns are a class of biometric information pertaining to the way a person moves and poses. Gait information is unique to each person and can be used to identify and reidentify people. Historically, this task has been achieved through the use of multiple ground-based imaging sensors. However, as Unmanned Aerial Vehicles (UAVs) advance, they present the opportunity to evolve the process of persons identification and re-identification. Collecting human gait data using UAVs at distances ranging from 20m to 500m and altitudes ranging from 0m to 120m is a challenging task. The current biometric data collection methods, primarily designed for …