Engineering Commons^™

Spatio-Temporal Deep Learning Approaches For Addressing Track Association Problem Using Automatic Identification System (Ais) Data, Md Asif Bin Syed

Graduate Theses, Dissertations, and Problem Reports

In the realm of marine surveillance, track association constitutes a pivotal yet challenging task, involving the identification and tracking of unlabelled vessel trajectories. The need for accurate data association algorithms stems from the urge to spot unusual vessel movements or threat detection. These algorithms link sequential observations containing location and motion information to specific moving objects, helping to build their real-time trajectories. These threat detection algorithms will be useful when a vessel attempts to conceal its identity. The algorithm can then identify and track the specific vessel from its incoming signal. The data for this study is sourced from the …

Motion Planning In Artificial And Natural Vector Fields, Bernardo Martinez Rocamora Junior

Graduate Theses, Dissertations, and Problem Reports

This dissertation advances the field of autonomous vehicle motion planning in various challenging environments, ranging from flows and planetary atmospheres to cluttered real-world scenarios. By addressing the challenge of navigating environmental flows, this work introduces the Flow-Aware Fast Marching Tree algorithm (FlowFMT*). This algorithm optimizes motion planning for unmanned vehicles, such as UAVs and AUVs, navigating in tridimensional static flows. By considering reachability constraints caused by vehicle and flow dynamics, flow-aware neighborhood sets are found and used to reduce the number of calls to the cost function. The method computes feasible and optimal trajectories from start to goal in challenging …

Analytical Heat Transfer Modeling Of The Microwave Heating Process: A Focus On Carbon Black, Craig Offutt

Graduate Theses, Dissertations, and Problem Reports

Electronic waste (e-waste) has become a significant environmental issue due to the rapid advancement of technology, increasing demand for electronic devices, and shorter lifespan of electronics. One critical step in processing the e-waste involves ball milling as a means of preparing the recycling e-waste for the recovery of critical materials. Ball milling is a technique that involves the mechanical crushing and grinding of electronic waste to reduce its size and improve its reactivity during recovery. Our focused recovery technique is based on a microwave recovery technique of these critical materials from e-waste. The size and distribution of the e-waste with …

Design And Validation Of An Aerodynamic System For A Formula Sae® Vehicle Using Vehicle Dynamic Simulation And Experimentation, Evan S. Cole

Graduate Theses, Dissertations, and Problem Reports

This thesis presents the design, simulation, and experimental validation for the aerodynamic system for a Formula SAE® vehicle. The Society of Automotive Engineers ® (SAE) hosts a collegiate competition annually called Formula SAE® where students design, fabricate, and test a small “formula style” vehicle. The vehicle performs in relatively slow maneuvers, around different courses and tests to evaluate the vehicle’s overall performance. Over the years, collegiate teams have put significant research into the design and manufacturing of the aerodynamics of these vehicles. In order to justify this undertaking for future teams at West Virginia University’s Formula SAE® program, a comprehensive …

Investigating The Change In Pavement Cracking Data Due To Automated Data Collection Methods, Faisal Quibria Chowdhury

Graduate Theses, Dissertations, and Problem Reports

Data collection on pavement surface cracks is crucial for the state Departments of Transportation (DOTs) to make informed decisions on maintenance, repair, and rehabilitation (MR&R) activities. The collected cracking data is translated into a pavement performance indicator to assess the condition of pavement sections and identify MR&R needs based on predetermined threshold values set by the state DOTs. State DOTs have transitioned from manual to automated data collection as automation offers many advantages over manual data collection, such as improved data collection rates, efficiency, cost reduction, and safety. As the state DOTs have integrated automated data into the pavement performance …

Investigation Of Oxidation And Corrosion Resistance Of Ni-Based Alloys And Stainless Steels Under Co2 Environments At Elevated Temperatures, Spencer Roy Fultineer

Graduate Theses, Dissertations, and Problem Reports

High mechanical strength integrity, high robustness towards oxidation, and high resistance to carburization under CO2 environments at elevated temperatures are usually required for metallic systems that are employed for power generation. INCONEL 625 is a nickel-based superalloy that started development in the 1950s. This material was designed with the distinct purpose of use in high-temperature and high-pressure systems. While various materials possess the physical properties to handle these conditions, the creation of IN625 addresses the need for a material to withstand the highly corrosive properties of these kinds of environments. In order to evaluate the oxidation and corrosion resistance of …

Modeling And Simulation Of A Process That Converts Ethane To Ethylene And Ethylene To Low Density Polyethylene, Ernest Bosire Mokaya

Graduate Theses, Dissertations, and Problem Reports

Ethylene is a critical feedstock and a major building block in the petrochemical industry that is used in synthesizing important products like polyethylene, ethanol, ethylene oxide, ethylene dichloride and ethylbenzene. With increasing demand of plastics, production of ethylene and subsequently polyethylene has increased globally. This thesis conducts the modeling and simulation of an integrated process that utilizes ethane as the primary feedstock to produce ethylene and the subsequent polymerization of ethylene to low-density polyethylene (LDPE). The process combines two different processes into one integrated process: (1) conversion of ethane to ethylene and (2) conversion of ethylene to LDPE. First, a …

Machine Learning Assisted Framework For Advanced Subsurface Fracture Mapping And Well Interference Quantification, Mohammad Faiq Adenan

Graduate Theses, Dissertations, and Problem Reports

The oil and gas industry has historically spent significant amount of capital to acquire large volumes of analog and digital data often left unused due to lack of digital awareness. It has instead relied on individual expertise and numerical modelling for reservoir development, characterization, and simulation, which is extremely time consuming and expensive and inevitably invites significant human bias and error into the equation. One of the major questions that has significant impact in unconventional reservoir development (e.g., completion design, production, and well spacing optimization), CO2 sequestration in geological formations (e.g., well and reservoir integrity), and engineered geothermal systems (e.g., …

A Comparative Analysis Of Coastdown Testing Methods From An Electric Drive Unit Engagement Perspective Using A Student-Designed Parallel Hybrid Electric Vehicle, Dawson Everett Dunnuck

Graduate Theses, Dissertations, and Problem Reports

Coastdown testing and road load determination are pivotal parts of the automotive design process. Vehicle manufacturers and independent companies perform and analyze road loads determined through a coastdown or similar method to determine a vehicle’s road load for modeling and EPA certification. For a traditional coastdown, the vehicle’s drivetrain must be disconnected through a clutch between the engine and the transmission while traveling at a high rate of speed to place the vehicle in neutral. This changes for hybrid and electric vehicles. Some hybrid, and most electric, vehicles delivered to customers do not have this clutch action to grant the …

Framework For Data Acquisition And Fusion Of Camera And Radar For Autonomous Vehicle Systems, Clay Edward Vincent

Graduate Theses, Dissertations, and Problem Reports

The primary contribution is the development of the data collection testing methodology for autonomous driving systems of a hybrid electric passenger vehicle. As automotive manufacturers begin to develop adaptive cruise control technology in vehicles, progress is being made toward the development of fully-autonomous vehicles. Adaptive cruise control capability is classified into five levels defined by the Society of Automotive Engineering. Some vehicles under development have attained higher levels of autonomy, but the focus of most commercial development is Level 2 autonomy. As the level of autonomy increases, the sensor technology becomes more advanced with a sensor suite which includes radar, …

Missile Modeling And Simulation Of Nominal And Abnormal Scenarios Resulting From External Damage, James Manuel Floyd Iii

Graduate Theses, Dissertations, and Problem Reports

This thesis presents the development of a six-degree-of-freedom flight simulation environment for missiles and the application thereof to investigate the flight performance of missiles when exposed to external damage. The simulation environment was designed to provide a realistic representation of missile flight dynamics including aerodynamic effects, flight control systems, and self-guidance. The simulation environment was designed to be modular, expandable, and include realistic models of external damage to the missile body obtained by adversarial counteraction.

The primary objective of this research was to examine missile flight performance when subjected to unspecified external damage, including changes in trajectory, stability, and controllability, …

Multimaterial, Core-Shell Direct Ink Writing Of Flexible Strain Sensors For Pneumatically-Actuated Soft Robotic Hinge Joints, John Michael Burke

Graduate Theses, Dissertations, and Problem Reports

Direct ink writing (DIW) provides for an expansive material library and the ability to print multiple materials with tailored functionalities in a controllable and single-step process. Particularly beneficial is the net shape printing under ambient conditions of a wide range of materials normally incompatible with one another. Coaxial DIW is a 3D printing technique that allows for two dissimilar inks to be extruded simultaneously in a co-flow manner. In this work, custom-designed coaxial nozzles were 3D-printed using a stereolithography printer. Composite inks comprised of thermoplastic polyurethane and silver were developed and studied. The coaxial nozzles were then used to co-extrude …

Frp Pedestrian Bridges, Joseph Ryan Virga

Graduate Theses, Dissertations, and Problem Reports

Advanced fiber-reinforced polymer (FRP) composites are being used as mainstream structural materials to build complex infrastructure systems. Such application of FRP composites can be attributed to their high strength-to-weight and stiffness-to-weight ratios, corrosion resistance, higher energy absorption, durability, and competitive life-cycle costs. FRP composites are increasingly being considered as suitable alternative structural materials to traditional construction materials such as timber, concrete, and steel.

In this work, detailed experimental investigation has been carried out on different types of glass FRP composite pedestrian bridges with FRP and/or timber deck. Four full-scale FRP pedestrian bridges, including 70`×8.5’ and 70’×10’ single-span bridges, a 16’×8’ …

Nonlinear Dynamic Analysis And Control Of Chemical Processes Using Dynamic Operability, San Quan Dinh

Graduate Theses, Dissertations, and Problem Reports

Nonlinear dynamic analysis serves an increasingly important role in process systems engineering research. Understanding the nonlinear dynamics from the mathematical model of a process helps to find the boundaries of all achievable process conditions and identify the system instabilities. The information on such boundaries is beneficial for optimizing the design and formulating a control structure. However, a systematic approach to analyzing nonlinear dynamics of chemical processes considering such boundaries in a quantifiable and adaptable way is yet to exist in the literature. The primary aim of this work is to formulate theoretical concepts for dynamic operability, as well as develop …

Dynamic Modeling, Data Reconciliation, Parameter Estimation, And Health Monitoring Of A Supercritical Power Plant, Katherine Grace Hedrick

Graduate Theses, Dissertations, and Problem Reports

With the introduction of a larger portion of renewable sources of power coming onto the U.S. power grid in recent decades, the operational strategy of coal-fired power plants has changed significantly to focus more on flexibility in response to the changing energy market. This has naturally led to different operational challenges. Many of these challenges are focused on the boilers within these plants, as they are producing more emissions and experiencing increased damage during load-following, which in turn leads to increased costs from penalties for not achieving emission standards or maintenance costs as boilers accumulate damage from the cycling behavior. …

Impacts Of Diverse Inflammatory Stimuli On Neutrophil Behavior: Extracellular Vesicles, E-Cigarettes, And Nanoparticles, Hunter T. Snoderly

Graduate Theses, Dissertations, and Problem Reports

Neutrophils are the body’s front-line defenders against foreign insult and are key players in a variety of inflammatory conditions. This body of work examines the role of neutrophils in promoting pathology in three distinct inflammatory contexts. In the pro-inflammatory state provoked by breast cancer, neutrophils decondense their nuclei and release cytotoxic web-like structures known as neutrophil extracellular traps (NETs). NETs form most commonly via histone modifications facilitated by the enzyme PAD4. NETs are known to be a harbinger of disease progression and promote metastasis through capture of circulating tumor cells. It was hypothesized that breast tumors release small particles known …

Investigating The Impact Of Demographic Factors On Contactless Fingerprint Interoperability, Aeddon David Berti

Graduate Theses, Dissertations, and Problem Reports

Improvements in contactless fingerprinting have resulted in contactless fingerprints becoming a faster and more convenient alternative to contact fingerprints. The interoperability between contactless fingerprints and contact fingerprints and how demographic factors can change interoperability has been challenging since COVID-19; the need for hygienic alternatives has only grown because of the sudden focus during the pandemic. Past work has shown issues with the interoperability of contactless prints from kiosk devices and phone fingerprint collection apps. Demographic bias in photography for facial recognition could affect photographed fingerprints. The paper focuses on evaluating match performance between contact and contactless fingerprints and evaluating match …

Ambient Ammonia Synthesis Via Microwave-Catalytic Materials And Plasma Chemistry, Siobhan Brown

Graduate Theses, Dissertations, and Problem Reports

Ammonia is critical to supporting human life on earth because of its use as fertilizer. The Haber-Bosch process to produce ammonia has been practiced for over 100 years. This process operates at high pressure and temperature to overcome the thermodynamic and kinetic limitations of the ammonia synthesis reaction thus researchers have tried to overcome it for decades. At present this process represents 1% of global energy usage and 2.5% of global CO₂ emissions. The proposed chemical looping ammonia synthesis approach seeks to reduce the environmental impact of this critical process and to elucidate microwave-catalytic principles.

This research aims to …

Spatiotemporal Trends In Particle-Associated Microbial Communities In A Chlorinated Drinking Water Distribution System, Madison Haddix

Graduate Theses, Dissertations, and Problem Reports

Bacteria can survive treatment and enter drinking water distribution systems (DWDSs), or enter DWDSs through intrusion or maintenance work on the system. DWDSs can also be suitable environments for bacterial regrowth. Many factors can affect the microbial community composition of DWDSs, including various spatiotemporal, hydraulic, and water quality parameters. Although most bacteria within DWDSs are harmless, opportunistic pathogens, such as Legionella pneumophila, Pseudomonas aeruginosa, and Mycobacterium avium, can inhabit DWDSs and premise plumbing and are the leading cause of waterborne disease outbreaks in developed countries. Previous studies have attempted to establish relationships between various parameters and microbial …

The Effect Of Different Fracturing Fluids On The Productivity Of Multi-Staged Fractured Marcellus Shale Horizontal Wells, Vida Gyaubea Matey-Korley

Graduate Theses, Dissertations, and Problem Reports

While hydraulic fracturing has undeniably improved the production from oil and gas reservoirs, this technology is not without limitations. The primary hurdles lie in the areas of proppant transport, fluid rheology, and stress management. Despite the extensive research conducted in this domain, there remains a considerable amount of work to be done for comprehensive solutions that account for the complex interactions among fracturing fluid, proppant distribution, and geomechanical conditions. Achieving this will then make room for a holistic and efficient hydraulic fracturing strategy.

This study addresses the above-mentioned problem by examining the impact of fluid type on proppant transport and …

Localization Of People In Gnss-Denied Environments Using Neural-Inertial Prediction And Kalman Filter Correction, Lauren N. Cash

Graduate Theses, Dissertations, and Problem Reports

This thesis presents a method based on neural networks and Kalman filters for estimating the position of a person carrying a mobile device (i.e., cell phone or tablet) that can communicate with static UWB sensors or is carried in an environment with known landmark positions. This device is used to collect and share inertial measurement unit (IMU) information — which includes data from sensors such as accelerometers, gyroscopes, and magnetometers — and UWB and landmark information. The collected data, in combination with other necessary initial condition information, is input into a pre-trained deep neural network (DNN) which predicts the movement …

Material Characterization Of Thermoplastic Polyurethane (Tpu) And Thermoplastic Elastomers (Tpe) For Development Of 3d-Printed Surrogate Organs For Medical Training, Anastasia Elizabeth Lucci

Graduate Theses, Dissertations, and Problem Reports

Cadaveric specimens are a necessary, albeit limited, resource for training medical students on basic surgical skills. The availability of surrogate 3D-printed organs would readily allow access to resources that could reduce or potentially eliminate the need for cadaveric specimens or, at a minimum, provide students the opportunity to practice with 3D-printed surrogates before transitioning to those specimens. This research focuses on determining which thermoplastic material most closely mimics mechanical properties such as hardness and stiffness of human organs and allows 3D printing surrogate organs to be used as safe, educational tools. Relatively “soft” materials such as thermoplastic polyurethanes (TPU) and …

Learning Representations For Novelty And Anomaly Detection, Ranya Almohsen

Graduate Theses, Dissertations, and Problem Reports

The problem of novelty or anomaly detection refers to the ability to automatically

identify data samples that differ from a notion of normality. Techniques

that address this problem are necessary in many applications, like in medical

diagnosis, autonomous driving, fraud detection, or cyber-attack detection, just to

mention a few. The problem is inherently challenging because of the openness of

the space of distributions that characterize novelty or outlier data points. This is

often matched with the inability to adequately represent such distributions due

to the lack of representative data.

In this dissertation we address the challenge above by making several …

Improving The Health And Safety Of Manufacturing Workers By Detecting And Addressing Personal Protective Equipment (Ppe) Violations In Real-Time With The Use Of Automated Ppe Detection Technology, Joseph Olufemi Fasinu

Graduate Theses, Dissertations, and Problem Reports

The Centers for Disease Control and Prevention (CDC) emphasized that Personal Protective Equipment (PPE) can significantly reduce the risk of occupational injuries and illnesses. However, improper use, failure to use, and other PPE-related violations can still result in injuries and fatalities. Eye and face protection violation has been one of the top 10 most frequently violated OSHA standards in fiscal years 2018, 2019, 2020, 2021 and 2022 consecutively. A common practice among safety professionals to ensure PPE compliance has been to physically inspect or monitor PPE usage among workers, which has been found to be unsustainable on a continuous real-time …

Techno-Economic Analysis And Optimization Of Hydrogen And Mechanical Energy Storage Systems, Pavitra Senthamilselvan Sengalani

Graduate Theses, Dissertations, and Problem Reports

The increasing significance of renewable energy sources is thrusting the load cycling of fossil-fueled power plants (FFPP), designed to operate under nominal-load conditions. Integration of energy storage systems (ESS) with the FFPPs such as hydrogen energy storage (HES) and mechanical energy storage facility such as compressed air energy storage (CAES) shows the potential to minimize the levelized cost of electricity during high demand scenarios and also minimize the negative impacts of off-design FFPP operation. The deployment of energy storage facilities at the FFPP level have considerable potential advantages as they can be exploited within the existing equipment items and facilities …

Generative Adversarial Network And Its Application In Aerial Vehicle Detection And Biometric Identification System, Moktari Mostofa

Graduate Theses, Dissertations, and Problem Reports

In recent years, generative adversarial networks (GANs) have shown great potential in advancing the state-of-the-art in many areas of computer vision, most notably in image synthesis and manipulation tasks. GAN is a generative model which simultaneously trains a generator and a discriminator in an adversarial manner to produce real-looking synthetic data by capturing the underlying data distribution. Due to its powerful ability to generate high-quality and visually pleasing
results, we apply it to super-resolution and image-to-image translation techniques to address vehicle detection in low-resolution aerial images and cross-spectral cross-resolution iris recognition. First, we develop a Multi-scale GAN (MsGAN) with multiple …

Physics Infused Lstm Network For Track Association Based On Marine Vessel Automatic Identification System Data, Tasmiah Haque

Graduate Theses, Dissertations, and Problem Reports

In marine surveillance, a crucial task is distinguishing between normal and abnormal vessel movements to timely identify potential threats. Subsequently, the vessels need to be monitored and tracked until necessary action can be taken. To achieve this, a track association problem is formulated where multiple vessels' unlabeled geographic and motion parameters are associated with their true labels. These parameters are typically obtained from the Automatic Identification System (AIS) database, which enables real-time tracking of marine vessels equipped with AIS. The parameters are time-stamped and collected over a long period, and therefore, modeling the inherent temporal patterns in the data is …

Advancing Medical Technology For Motor Impairment Rehabilitation: Tools, Protocols, And Devices, Matthew Yough

Graduate Theses, Dissertations, and Problem Reports

Excellent motor control skills are necessary to live a high-quality life. Activities such as walking, getting dressed, and feeding yourself may seem mundane, but injuries to the neuromuscular system can render these tasks difficult or even impossible to accomplish without assistance. Statistics indicate that well over 100 million people are affected by diseases or injuries, such as stroke, Parkinson’s Disease, Multiple Sclerosis, Cerebral Palsy, peripheral nerve injury, spinal cord injury, and amputation, that negatively impact their motor abilities. This wide array of injuries presents a challenge to the medical field as optimal treatment paradigms are often difficult to implement due …

Advancing Carbon Sequestration Through Smart Proxy Modeling: Leveraging Domain Expertise And Machine Learning For Efficient Reservoir Simulation, Iman Oraki Kohshour

Graduate Theses, Dissertations, and Problem Reports

Geological carbon sequestration (GCS) offers a promising solution to effectively manage extra carbon, mitigating the impact of climate change. This doctoral research introduces a cutting-edge Smart Proxy Modeling-based framework, integrating artificial neural networks (ANNs) and domain expertise, to re-engineer and empower numerical reservoir simulation for efficient modeling of CO₂ sequestration and demonstrate predictive conformance and replicative capabilities of smart proxy modeling.

Creating well-performing proxy models requires extensive human intervention and trial-and-error processes. Additionally, a large training database is essential to ANN model for complex tasks such as deep saline aquifer CO₂ sequestration since it is used as the …

Leveraging Artificial Intelligence And Geomechanical Data For Accurate Shear Stress Prediction In Co2 Sequestration Within Saline Aquifers (Smart Proxy Modeling), Munirah Alawadh

Graduate Theses, Dissertations, and Problem Reports

This research builds upon the success of a previous project that used a Smart Proxy Model (SPM) to predict pressure and saturation in Carbon Capture and Storage (CCS) operations into saline aquifers. The Smart Proxy Model is a data-driven machine learning model that can replicate the output of a sophisticated numerical simulation model for each time step in a short amount of time, using Artificial Intelligence (AI) and large volumes of subsurface data. This study aims to develop the Smart Proxy Model further by incorporating geomechanical datadriven techniques to predict shear stress by using a neural network, specifically through supervised …