Effect Of Gluconate Molecules On The Reaction Kinetics Of C-(N)-A-S-H And N-A-S-H Gel Formation, Jiafeng Kong, Chao Sun, Zuhua Zhang, Chenglong Cai, Yubin Cao, Yanru Wang, Hongyan Ma, Xuesen Zeng, Hao Wang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Organic ligands are widely used to regulate setting in cementitious binders, yet their chemistry-selective action in geopolymers (GPs) remains unclear. Here we isolate the role of sodium gluconate (SG) in early reaction kinetics across a Ca-rich GP that forms a calcium-(sodium)-aluminosilicate hydrate (C-(N)-A-S-H) gel and a Ca-poor GP that forms a sodium-aluminosilicate hydrate (N-A-S-H) gel. Four GPs spanning Ca/Si ≈ 1.01 to 0.01 were prepared with identical activator chemistry and dosages of SG up to 5 wt.% of precursors. Setting time, isothermal calorimetry, pore-solution speciation (TOC, ICP-OES, and pH), selective dissolution (reaction extent), low-field¹H NMR, XRD, FTIR, SEM-EDS, …

Extending The Applicability Of Thermal Protection System Ballistic Limit Equations Beyond The Testable Regime, William P. Schonberg, Michael D. Squire

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Spacecraft use thermal insulation in their design, which is usually placed on their exterior. As such, it is susceptible to high-speed impacts by meteoroids and orbital debris, which can damage it to a point where the protection it offers is below acceptable limits. It is important to be able to characterize expected levels of damage stemming from such high-speed impacts. In this paper, we extend the applicability of a previously developed ballistic limit equation (BLE) for one such thermal insulation material using the results of a series of Smooth Particle Hydrodynamics Code (SPHC) impact simulations at velocities in excess of …

Reevaluating The Van’T Hoff And Arrhenius Equations: How Temperature And Pressure Affect Chemical Reaction Thermodynamics, Equilibrium, And Kinetics, Jianmin Wang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The van’t Hoff equation, which is used to calculate the effect of temperature on equilibrium constants, was derived from the Gibbs – Helmholtz equation that relates the molar Gibbs free energy to the molar enthalpy of a chemical reaction. However, the Gibbs – Helmholtz equation was developed for systems that do not consider contributions of Gibbs free energy from chemical species. Consequently, the van’t Hoff equation and the Arrhenius equation derived from it are technically incomplete.

By employing Hess’s law and the appropriate Gibbs free energy equation for chemical reaction systems, this investigation develops theoretical equations to calculate the effects …

On High-Speed Breakup Of Water Droplets Behind High Mach Number Shocks, Sydney M. Briggs

Graduate Thesis and Dissertation post-2024

Water droplet breakup in high-speed flow is a relatively popular experimental study to analyze breakup mechanisms. There is a plethora of experiments performed at low Mach number and low Weber number, but studies with higher speed flows and higher Weber numbers are less common. In this study, water droplet breakup is assessed using high-speed shock waves (Mach 2.3-above Mach 5) in a shock tube. Multiple methods are used to introduce droplets, and multiple different water purity levels are considered. An assessment was made into whether cavitation played a role in the breakup process physically, as this has been a budding …

Development Of Generalizable Data-Driven Traffic State Prediction Solutions: A Comprehensive Approach, Md Mobasshir Rashid

Graduate Thesis and Dissertation post-2024

Increased urbanization and population growth lead to more traffic in the transportation system, causing severe congestion. Particularly during disruptive events such as hurricanes or traffic incidents, the traffic flow in the network worsens significantly. As a result, there is a need for data-driven traffic prediction models to reduce congestion in real-time, and the prediction model should be generalizable to be applicable across different dynamic scenarios. Additionally, a robust and adaptable traffic prediction model can help traffic managers to take proactive actions to optimize traffic flow. However, the majority of data-driven traffic prediction models suffer from limited applicability as they are …

Deep Reinforcement Learning-Based Optimal Takeoff Trajectory Design Of An Evtol Drone, Nathan M. Roberts, Bingling Huang, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The continuing development of electric vertical take-off and landing (eVTOL) aircraft presents promising opportunities to alleviate transportation congestion. However, designing and executing takeoff trajectories that optimally balance energy usage, passenger comfort, and aircraft constraints remains challenging. Conventional design optimization provides a solution for pre-defined flight conditions and environments but is not ideal in real-world applications. In contrast, deep reinforcement learning (DRL) implements optimal policy making real-time decisions with no assumption of mathematical models. Seeing the lack of literature on DRL-based takeoff trajectory design of eVTOL aircraft, we implement and conduct DRL-based optimal takeoff trajectory designs for the Airbus³ Vahana …

Industry 5.0, Human–Machine Interface, And Smart Manufacturing In Additive Manufacturing—A Recent Trend, Atiqur Rahman, Md Hazrat Ali, Muhammad Arif Mahmood, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The emergence and importance of Industry 5.0 are transforming production by integrating smart technology with human creativity and intelligence, especially in advanced additive manufacturing. This critical review precisely analyzes the function of human–machine interfaces (HMIs) in enhancing additive processes, emphasizing their incorporation into smart manufacturing systems and hybrid manufacturing methods, including material extrusion (MEX), laser powder bed fusion (LPBF), and directed energy deposition (DED). It also evaluates artificial intelligence (AI), the Internet of Things (IoT), and cybersecurity, which enhance HMIs in process monitoring, operation, and system adaptability. This study aims to provide a critical analysis and future research direction on …

Anisotropic Third-Harmonic Vortex Beam Generation With Ultrathin Germanium Arsenide Fork Gratings, Jayanta Deka, Jie Gao, Xiaodong Yang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Optical vortices have the tremendous potential to increase data capacity by leveraging the extra degree of freedom of orbital angular momentum. On the other hand, anisotropic 2D materials are promising building blocks for future integrated polarization-sensitive photonic and optoelectronic devices. Here, highly anisotropic third-harmonic optical vortex beam generation is demonstrated with fork holograms patterned on ultrathin 2D germanium arsenide flakes. It is shown that the anisotropic nonlinear vortex beam generation can be achieved independent of the fork grating orientation with respect to the crystallographic orientation. Furthermore, 2D fork hologram is designed to generate multiple optical vortices having different topological charges …

Thermo-Rheological And Tribological Properties Of Low- And High-Oleic Vegetable Oils As Sustainable Bio-Based Lubricants, Abiodun Saka, Tobechukwu K. Abor, Anthony C. Okafor, Monday U. Okoronkwo

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Vegetable oil-based lubricants have attracted increased research attention in recent decades as sustainable alternatives to conventional petroleum-based lubricants in metal machining. However, more studies are required to fully elucidate the thermo-rheological and tribological properties. This study presents an investigation of the thermo-rheological and tribological properties of different vegetable oils, including low- and high-oleic soybean oil, high-oleic sunflower, safflower, and canola oils. The lubricity, and evolution of viscosity and thermodynamic properties as a function of temperature were investigated to obtain important parameters including the viscosity index, flow behavior index, flow activation energy, specific heat capacity, thermal conductivity, coefficient of friction, contact …

Generative Adversarial Networks For Dimensionality Reduction In Evtol Aircraft Takeoff Trajectory Optimization, Samuel Sisk, Farzaam Khorasani-Gerdehkouhi, Abdulaziz Abutunis, K. Chandrashekhara, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft play a key role in urban air mobility (UAM), which aims to alleviate traffic congestion in urban areas. Despite their value, eVTOL aircraft suffer from battery energy consumption, which affects their range and endurance in real world flight tasks. Especially, the takeoff process has been identified for excessive power demands. Multidisciplinary analysis and optimization manage to discover optimal takeoff trajectories with minimum energy consumption while balancing multidisciplinary trade-offs, such as short distance takeoff and passengers' comfort. However, conventional parametrization methods (such as B-spline curves) leverage an empirically high-dimensional design space to include real …

Ai-Powered Image-Based Assessment Of Pressure Injuries Using You Only Look Once (Yolo) Version 8 Models, Mehedi Hasan Tusar, Fateme Fayyazbakhsh, Niloofar Zendehdel, Eduard Mochalin, Igor Melnychuk, Lisa Gould, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Objective: The primary objective of this study is to enhance the detection and staging of pressure injuries using machine learning capabilities for precise image analysis. This study explores the application of the You Only Look Once version 8 (YOLOv8) deep learning model for pressure injury staging. Approach: We prepared a high-quality, publicly available dataset to evaluate different variants of YOLOv8 (YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, and YOLOv8x) and five optimizers (Adam, AdamW, NAdam, RAdam, and stochastic gradient descent) to determine the most effective configuration. We followed a simulation-based research approach, which is an extension of the Consolidated Standards of Reporting Trials …

Hands-Free Uav Control: Real-Time Eye Movement Detection Using Eog And Lstm Networks, Niloofar Zendehdel, Khosro Ghorbani Zadeh, Haodong Chen, Yun Seong Song, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Industry 4.0 has created a growing need for effective human-robot collaboration (HRC). As robots and humans work more closely together, efficient communication becomes essential for coordinating their actions seamlessly. While speech may seem like the obvious choice for communication, noisy factory environments can render it impractical. Additionally, workers often have their hands occupied with assembly tasks, making hand-controlled interfaces less practical for controlling robots. To address these challenges, this paper presents a novel, hands-free method for robot control using electrooculography (EOG) signals–specifically, eye movements and blinks–with unmanned aerial vehicles (UAVs) used as the demonstration platform. We developed a real-time system …

Correction: Advancing Cislunar Space Domain Awareness Through Robust Optimization Framework For Optical Sensors-Based Autonomous Satellite Systems (American Institute Of Aeronautics And Astronautics Inc, Aiaa), Smriti Nandan Paul, Siwei Fan, Igor Panfil

Mechanical and Aerospace Engineering Faculty Research & Creative Works

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Study On Field Emission Characteristics Of Carbon Nanotube Arrays Patterned Via Laser Welding Of Dissimilar Materials, Hung Yin Tsai, Yi Hung Chen, Kuan Ching Wang, Paul W. Leu, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper describes a new method of growing carbon nanotube (CNT) arrays using laser welding of a catalyst metal onto the surface of a quartz substrate, followed by CNT growth through the chemical vapor deposition (CVD) process. A major advantage of this method is its ability to pattern the catalyst before growing the CNTs, thus allowing for the formation of CNTs at specific locations. The laser pre-treatment method minimized structural damage to CNTs in comparison to the laser post-processing method, achieving a lower ID/IG value of 0.72 in Raman spectroscopy analysis. Using hexagonally patterned CNT arrays on quartz, we achieve …

Development And Validation Of A Subject-Specific Integrated Finite Element Musculoskeletal Model Of Human Trunk With Ergonomic And Clinical Applications, Farshid Ghezelbash, Amir Hossein Eskandari, Amir Jafari Bidhendi, Aboulfazl Shirazi-Adl, Christian Lariviere

Études primaires

Biomechanical modeling of the human trunk is crucial for understanding spinal mechanics and its role in ergonomics and clinical interventions. Traditional models have been limited by only considering the passive structures of the spine in finite element (FE) models or incorporating active muscular components in multi-body musculoskeletal (MS) models with an oversimplified spine. To address those limitations, we developed a subject-specific coupled FE-MS model of the trunk and explored its applications in ergonomics and surgical interventions. A parametric detailed FE model was constructed, integrated with a muscle architecture, and individualized based on existing datasets. Our comprehensive validation encompassed tissue-level responses, …

Using Data Science And Sustainability Assessment Tools To Evaluate Wastewater Treatment Technologies, Haidar Shakuir Aldaach

Graduate Theses, Dissertations, and Problem Reports (ETD)

Wastewater management in small communities has faced numerous challenges in recent years, including population growth, limited budgets for operation and maintenance, and stringent effluent standards required by environmental regulations. These challenges motivate enhancing wastewater treatment processes to protect water quality. Wastewater treatment performance can be improved in small towns and rural regions by implementing data-driven strategies. Data science, life cycle assessment (LCA), and life cycle cost analysis (LCCA) are three data-driven decision-making tools that require data collection, modeling, computational models, and statistical analysis that could be utilized to improve wastewater treatment efficiencies. In this study, these three tools were adopted …

Rfid Occupied Advanced Framework For Specialized Vehicle Access, Operating System, And Wireless Data Transmission Without Human Intervention, Abdullah Al Mamun Anik, Mosammet Sadia Akter Moon, Fahim Faysal Arnob, Mehedi Hasan, S. A. Naimal Hoque, Mohammad Mashhunar Rahman, Tahzin Bin Ahmed, Tonmoy Barua

Mechanical Engineering Faculty Publications and Presentations

Radio frequency identification system (RFID) tags are tiny electronic devices that include a distinctive code that can be detected by a reader that supports RFID. The string of characters is used for recognizing and monitoring the object to which the tag is connected. RFID tags interact with RFID readers using radio frequency. While the tag comes into close proximity to the scanner, that device sends a radio signal that triggers the tag. The tag then responds by sending its unique identity. RFID pinpointing ability is verified experimentally in two different techniques, one utilizing radar and the other a photosensitive transition. …

Cultivating Plain Language Skills For Engineering Students, Catherine Wong, Cynthia Carlson

Faculty Publications

While engineers are learning the vocabulary of the profession, understandably, they want to practice, and perhaps show their professors that they are proficient. This leads to student writing that is overly complicated and full of jargon. This is not the type of document that would be clear to the public, or even to a professional outside of the narrowly focused field of the particular engineer. After graduation, engineers’ writing becomes exponentially more important. Often approval of projects relies on residents’ or clients’ understanding of engineers’ work. For example, an engineering firm completing an investigation of an important health concern such …

Deep Learning-Driven Biometric Security: Advancing Liveness Detection And Anti-Spoofing Techniques, Banafsheh Adami

Graduate Theses, Dissertations, and Problem Reports (ETD)

Biometric authentication has become a key part of our everyday lives—from unlocking smartphones with a fingerprint or face to verifying identities in banks and airports. These systems rely on our unique physical or behavioral traits, making them both convenient and secure. Unlike passwords, biometrics cannot be forgotten or stolen in the traditional sense. However, they are not without risk. One of the biggest concerns is spoofing: attempts by attackers to fool systems using fake biometric traits, such as silicone fingerprints or AI-generated videos.

As generative AI tools become more powerful and accessible, the ability to create convincing fake biometric data …

Multi-Scale Dynamic Modeling, Validation, And Uncertainty Quantification Of Radial Flow Fixed Bed Contactors For Co2 Capture, Ana Flávia De Alencar Arraes Monteiro

Graduate Theses, Dissertations, and Problem Reports (ETD)

One of the key sources of carbon dioxide emissions to the environment is fossil fuel combustion for power generation. Post-combustion CO2 capture using amine-based solvents is currently the most matured process. However, amines are corrosive and lead to degradation products at even moderate temperatures generating environmental pollutants, and require high energy for regeneration. Solid sorbents are a promising alternative. They possess lower regeneration energy, thermal stability, and have highly tunable porous structures with large surface area that can help in achieving high loading and high adsorption rates. This work focuses on mathematical modeling of CO2 adsorption/desorption processes using solid sorbents. …

Framework For Development Environment Selection In Digital Twin Applications, Carlos Dodero Fernandez

Graduate Theses, Dissertations, and Problem Reports (ETD)

Digital Twin (DT) technology, a cornerstone of Industry 4.0, facilitates real-time synchronization between virtual models and physical manufacturing systems, enhancing operational efficiency and decision-making. However, its widespread adoption is hindered by the absence of standardized methods for selecting Development Environments (DEs) for DTs, compounded by challenges in cost, interoperability, and connectivity with Industrial Internet of Things (IIoT) protocols. This thesis proposes a Systematic Selection Framework to address this gap, offering a structured methodology to evaluate DEs based-on visualization quality, scalability, interoperability, and cost-effectiveness for manufacturing applications. The framework categorizes and compares sixteen DEs into Game Engines, Robotics Engines, and Simulation …

Efficient And Test-Time Adaptive Visual Object Tracking In The Wild, Ram J. Zaveri

Graduate Theses, Dissertations, and Problem Reports (ETD)

Tracking a single object, given the location at the first frame, has been an ongoing challenge in the vision community for decades. Most recent approaches provide reasonably good performance, especially when benchmarked on in-distribution (ID) datasets, i.e., on the testing portion of the same datasets used for training. However, they incur high computational costs and hardware constraints, making their deployment in the wild for mobile, autonomous, and IoT applications still challenging. Efficient visual trackers address the efficiency aspect of such bottlenecks; however, they tend to overfit to their training distributions and lack generalization abilities, resulting in them performing well on …

Design And Simulation Of An Ai-Powered Autonomous Quadrotor Framework For Search And Rescue Operations, James J. Shope

Graduate Theses, Dissertations, and Problem Reports (ETD)

Unmanned aerial vehicles (UAVs), particularly quadrotor platforms, have proven to be indispensable tools for search and rescue (SAR) teams due to their maneuverability, rapid deployment, and affordable operation. The current SAR use cases of quadrotors span from aerial surveillance to mission planning and strategic deliveries. However, most SAR applications remain passive or semi-autonomous, such that they rely on human-operated control or data assessment. Advancements in autonomous control strategies bring about a future where a single SAR operator can program and deploy several UAVs. This thesis details the development and simulation of a fully autonomous, AI-powered quadrotor framework capable of detecting …

Neural Network-Based Image Compression, Atefeh Khoshkhahtinat

Graduate Theses, Dissertations, and Problem Reports (ETD)

The rapid advancement of information technology and the exponential growth of digital communication have significantly increased the demand for efficient data compression techniques that reduce storage requirements, minimize bandwidth consumption, and accelerate data transmission—without substantially compromising data quality. This dissertation addresses these challenges by investigating and developing advanced learned image compression (LIC) methods, with a particular focus on lossy compression for both natural images and scientific imagery obtained from NASA’s Solar Dynamics Observatory (SDO) mission. Traditional image compression standards—such as JPEG, JPEG2000, BPG, and HEVC—rely on manually engineered transforms and heuristic rules, which often lack the adaptability required to accommodate …

Assessing And Predicting The Impact Of A Retrofitted Methane Mitigator On Non-Road Large Natural Gas Engines Using Artificial Neural Networks, Augustine Thomas Ojo

Graduate Theses, Dissertations, and Problem Reports (ETD)

Abstract

ASSESSING AND PREDICTING THE IMPACT OF A RETROFITTED METHANE MITIGATOR ON NON-ROAD LARGE NATURAL GAS ENGINES USING ARTIFICIAL NEURAL NETWORKS

Augustine Thomas Ojo

Methane emissions from the oil and gas sector present a pressing environmental and economic challenge, given methane’s high global warming potential and the considerable volumes of unutilized gas lost from industrial processes. This study investigates the impact of a retrofitted methane mitigation system, the Methane Mitigator (M²), on fuel consumption and engine-out emissions in non-road, four-stroke natural gas-powered, lean-burn engines and develops predictive Artificial Neural Network (ANN) models to estimate the resulting engine-out emissions and fuel …

Parametric Analysis Of Proppant Selection Impact On The Hydraulic Fracture And Productivity Of Extended-Reach Marcellus Shale Wells, Nicholas Hunter Lapinski

Graduate Theses, Dissertations, and Problem Reports (ETD)

Hydraulic Fracture Proppant is the gateway to reservoir connectivity, allowing for decades of natural gas production from hydraulically fractured wells in the Marcellus Shale. The proper selection of proppant can have major ramifications on the productivity of the extended-reach Marcellus shale wells. The proppant penetration into the induced fracture attempts to close the gap between the realistic non-uniform fracture conductivity and the idealistic uniform fracture conductivity. Consequently, the more proppant residing within these fractures, the more likely the proppant is to resist crushing due to the compaction. Phenomena, Advancements have been made to create more durable proppant types or proppant …

Modeling And Simulation Of A Process For Upcycling Of Low-Density Polyethylene Plastic Waste To Ethylene, Xiaoyan Wang

Graduate Theses, Dissertations, and Problem Reports (ETD)

Ethylene is one of the most widely produced petrochemicals, with an estimated global output of 180 million metric tons in 2022. Approximately 82 million metric tons of ethylene are used annually for plastic production, primarily for polyethylene (PE), as well as polypropylene (PP) and polyvinyl chloride (PVC). The CO₂ emissions associated with PE production were approximately 14 million metric tons in 2022. Globally, an estimated 70 million metric tons of PE are produced and consumed each year, with the majority (~79%) ending up in landfills or the environment.

This project proposes a novel process in which waste low-density polyethylene (LDPE) …

Fundamental And Applied Investigation Of Ammonia Combustion: Characteristics And Emissions At Relevant Ic Engine Conditions, Luis Fernando Alvarez Correa

Graduate Theses, Dissertations, and Problem Reports (ETD)

Ammonia (NH3) is regarded as a promising fuel for future carbon-free power and propulsion systems due to its high hydrogen content, ease of storage, and existing infrastructure. Despite these advantages, NH3 exhibits inherently poor combustion characteristics, including low laminar burning velocity, high ignition energy, narrow flammability limits, and sluggish chemical kinetics. These limitations were solved in prior research by blending NH3 with hydrogen (H2) or hydrocarbons, which improved reactivity but introduced trade-offs such as increased complexity, safety concerns, or carbon emissions. Consequently, there remains a significant lack of fundamental and applied research on neat NH3 combustion, particularly under engine-relevant conditions …

Evaluation Of Small Unmanned Tailsitter Hybrid Air Vehicles Via Full Flight Simulation, Andrew Spencer Winters

Graduate Theses, Dissertations, and Problem Reports (ETD)

Small Unmanned Aerial Vehicles have exploded in popularity in the past 15 years among researchers and for industrial uses such as agriculture, search and rescue, and infrastructure inspection. Fixed wing and multirotor designs present two major paths that can be taken with these technologies. Fixed wing platforms have superior aerodynamic efficiency but require large areas for takeoff/landing and cannot hold a constant position in space, limiting their use. Multirotor configurations offer a more versatile platform that can maneuver in 3 dimensions independently but lack the endurance of fixed wing vehicles. This thesis analyses a quadrotor biplane and a variable wingspan …

Recovery Of Iron And Aluminum From Acid Mine Drainage For Beneficial Uses, Katelyn Renee Pepe

Graduate Theses, Dissertations, and Problem Reports (ETD)

Acid mine drainage (AMD) is a widespread issue across the globe, in which some of the most critical cases are created by the mining industry. Researchers have investigated ways to derive benefits from AMD, such as precipitating rare earth elements (REEs) to generate potential revenue from AMD treatment and supplement market demand. However, the bulk of precipitated sludge is composed of iron and aluminum, which also have market value but are discarded in current practice.

Using the Omega site in West Virginia (WV) as a representative AMD source, the objectives of this study are (1) to determine a replicable precipitation …