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Design And Production Of A Carbon Fiber Longboard, John R. Beebe, Jacob Williams, Julia Stradinger, Vince Fitchtel, Jordan Cochran

Honors Theses

This thesis contains an overview of the design, prototyping, and manufacturing of a carbon fiber long board. The purpose of this capstone was to create a viable product for the real-world market and then determine how to manufacture it at scale with sustainable financial practices. In order to accomplish this task, engineering, accounting, and manufacturing challenges had to be overcome throughout all stages. The production process involved the carbon fiber layup, baking, water jet cutting, and assembly of the carbon fiber longboard. In order to optimize this process, continuous improvement and lean manufacturing problem solving techniques were applied. After a …

Sustainable – Low-Cost - Upgrade Of Activated Sludge Process For Nitrogen And Phosphorus (N&P) Removal From Wastewater, Abanoub N. Basta

Theses and Dissertations

Many municipal wastewater treatment plants (WWTPs) in developing countries were designed primarily for organic matter and suspended solids removal and therefore face increasing difficulty in meeting modern nitrogen (N) and phosphorus (P) discharge requirements. Conventional biological nutrient removal upgrades commonly require additional reactor volume, recirculation systems, aeration energy, and capital investment. Accordingly, sustainable retrofit strategies that improve nutrient removal within existing treatment footprints are increasingly needed, particularly in water-scarce and land-constrained regions.

This study investigated the integration of water hyacinth (Eichhornia crassipes) into the aeration stage of an activated sludge process as a hybrid nature-based enhancement for nitrogen and phosphorus …

Green Waste Biochar And Plant Growth-Promoting Bacteria Enhance Tomato Growth Under Combined Nutrient Deficiency And Salinity Stress, Soumaya Tounsi-Hammami, Munawwar Ali Khan, Mahra Alqemzi, Salama Ali Almehairi, Aneesa Rasheed Anwar

All Works

This study characterized a green-waste-derived biochar from date palms and ghaf trees and investigated its potential as a soil amendment with halotolerant Bacillus spp. to improve tomato seedling quality under dual stress of salinity and nutrient deficiency. Biochar was produced through pyrolysis at 450 °C and then characterized for yield, pH, electrical conductivity, proximate analysis, surface morphology, energy-dispersive X-ray spectroscopy, and heavy-metal content. Its effectiveness was tested both alone and in combination with a Bacillus sp. mix, using a completely randomized design with varying NPK fertilizer levels and saline irrigation. Tomato seedlings were evaluated 45 days after planting for various …

Extending Geometric Acoustic Ray Tracing To Multi-Room Environments: A Case Study On Gunshot Sound Transmission Between Adjacent Rooms, Tyler Ton

Theses and Dissertations

Accurate localization of gunshots in multi-room building environments remains a challenging problem in acoustic forensics and public safety applications. Existing approaches model sound propagation within a single room, neglecting the transmission of acoustic energy through walls and other building materials. This thesis presents a study on modeling multi-room gunshot acoustic transmission, combining geometric ray tracing with structural acoustic transmission-loss modeling to generate impulse responses for two horizontally adjacent rooms separated by a shared wall, providing a foundation for future inter-room gunshot localization work. The proposed system uses GSound-SIR, a geometric acoustics engine, to simulate sound propagation in both of the …

Nanofluid-Assisted Enhanced Sealing Containment Of Caprocks For Efficient Geological Co2 Storage, Muhammad Ali, Nurudeen Yekeen, Mujahid Ali, Nilanjan Pal, Mohammed Al Kobaisi, Alireza Keshavarz, Hussein Hoteit

Research outputs 2022 to 2026

Millions of tons of CO2 are stored annually in geological formations in order to reduce greenhouse gas emissions, relying on caprock as a seal to prevent CO2 leakage. The wettability of caprock is crucial for its effectiveness, and can be altered by organic acids present in the storage media. The present study investigates the impact of stearic acid on the CO2 wettability of shale, along with the potential of alumina nanofluids to reverse this effect. Using contact angle measurements, X-ray diffraction, and other analytical methods, the study reveals that stearic acid increases the CO2 wettability of shale, making it more …

A Review Of Gallium And Germanium Recovery From Industrial Solid Residues, Ernest V. Oteng, Marthias Silwamba, Lana Alagha, Alex Luyima

Mining Engineering Faculty Research & Creative Works

The global demand for critical elements such as gallium (Ga) and germanium (Ge), and the shift toward circular mining has accelerated the development of new extraction and recovery processing these metals from industrial solid residues. This transition is driven by a substantial surge in demand for advanced technologies and the depletion of primary ore. Consequently, industrial solid residues, particularly zinc processing residues, smelter slags, flue dusts, and coal fly ash, are emerging as viable alternative sources. These residues incorporate Ga and Ge through isomorphic substitution in phases such as ferrites, silicates, and glassy aluminosilicates, and are enriched by industrial processes, …

Mind The Hazard: Modeling And Interpreting Comfort With Personalized Sensing, Yufei Zhang, Matteo Favero, Patrick Chwalek, Sailin Zhong, Denis Lalanne, A. Joseph Paradiso, Clayton Miller, Andrew Sonta

Research Collection College of Integrative Studies

Recent advances in personalized sensing and comfort feedback have spurred the development of data-driven comfort models tailored to individual needs. However, because current models treat sequential comfort feedback independently, they are subject to unstable predictions and limited interpretability, hindering their deployment in building management. This study introduces a dynamic modeling framework that utilizes a Neural Ordinary Differential Equations-based Continuous-time Markov Chain to model the transitions in comfort states over time. Our modeling approach, developed through a field study utilizing smart glasses and mobile app feedback, tracks occupants' comfort transitions across daily activities and contexts. The results demonstrate that this model …

Estimation Of Unmeasurable External Disturbances Of A Dynamic Object Based On A Robust Adaptive Kalman Filter, Bunyod Mamurjon Ugli Buronov

Technical science and innovation

This article considers the problem of directly estimating unmeasurable external disturbances acting on a dynamic object under the condition that the state vector of the object is available for measurement. In the considered case, the problem is reduced to the estimation of an unknown input of a dynamic system. It is shown that when the system state is measurable, both a direct inversion scheme based on the object’s dynamic equation and filtering methods that eliminate the need for coarse numerical differentiation can be applied. For slowly varying disturbances, a random walk model with a small process noise covariance is proposed, …

Where Do We Go Now: An Examination Of The Role Of 3d Modeling In Cancer Research, Ella Claire Gregory, Hannah Noelle Cochran

ABE 4523/6523 Biomedical Materials

The development of three-dimensional tumor models has become an important area of cancer research. By incorporating biomaterials that can mimic the physical, chemical, and biological characteristics of the tumor environment. 3D models can provide a more physiologically relevant environment for studying tumor growth, cell interaction, metastasis, and drug response.

Integrated Evaluation Of Rooftop Solar Power Generation System Performance In Tropical Climate Using Geometric, Electrical, And Environmental Parameters, Ayu N. Sari, Ilham R. Fadhlurrahman, Surya Pinanggi, Ermanu A. Hakim, Haneef Nouval Alannibras Humaidi

Journal of Mechanical Engineering Science and Technology (JMEST)

The increasing demand for electrical energy in the commercial sector has encouraged the utilization of rooftop Photovoltaic (PV) systems as a sustainable energy solution in tropical climate regions. However, rooftop PV performance is influenced by the interaction of geometric, electrical, and environmental parameters, which may affect system efficiency. This study analyzes the performance of a rooftop PV system under tropical climate conditions using PVsyst simulation and actual monitoring data collected over 30 days. The research was conducted on an on-grid rooftop PV system with a capacity of approximately 135 kWp, consisting of 217 photovoltaic modules and three inverters with a …

Evaluation Of The Metrological Characteristics Of An Ultrasonic Flowmeter For Water Resources, Makhsud Idrisovich Makhmudov, Uktam Farkhodovich Mamirov, Siroj Sobirovich Nurov

Technical science and innovation

This paper presents the results of evaluating the metrological characteristics of a developed ultrasonic flowmeter intended for measuring water flow in open channels. The study analyzes the main sources of measurement errors and classifies them into methodological, instrumental, additional, systematic, and random components. Experimental investigations were carried out to estimate the random and systematic errors under steady-state flow conditions. Using the least-squares method, the systematic error was separated into additive and multiplicative components, providing a basis for calibration and correction of the measurement results. The reliability of the developed measuring instrument was evaluated using the failure rate method based on …

Mathematical Modelling Of Nitrification And Denitrification Processes Based On Neuro-Fuzzy Bioreactor Models, Mirkhalil Agzamovich Ismailov, Boburbek Zokirjon Ugli Mannobjonov

Technical science and innovation

This paper presents the development and investigation of hybrid neural network and fuzzy models for the mathematical modelling of nitrification and denitrification processes in a biological wastewater treatment bioreactor. A comprehensive approach is proposed, integrating a mechanistic model of the ASM1/ASM2d type with neural networks (LSTM and Gaussian Process Regression), as well as a fuzzy control system based on an extended set of expert rules. A digital twin of the bioreactor was developed to allow for the prediction of the dynamic behavior of key parameters such as NH₄⁺, NO₃⁻, dissolved oxygen, etc. within a prediction range of 1 to 12 …

Artificial Neural Network-Based Modelling And Prediction Of Key Performance Indicators In Road Construction Projects, Hussein Mativila, John M. Kafuku, Beatus A. T. Kundi

Tanzania Journal of Engineering and Technology (TJET)

Road construction projects in developing countries including Tanzania experience several challenges including cost overruns, schedule delays and poor quality. The causes of these challenges include complex interdependencies project’s uncertainty factors. This makes traditional methods for predicting Key Performance Indicators (KPIs) less effective. This study has developed a robust Artificial Neural Network (ANN) model for accurate modelling and predicting KPIs for road construction projects in Tanzania. The analysis was based on data obtained from 281 projects implemented by TANROADS in 11 regions from 2015 to 2025. Fourteen uncertainty factors were measured on a five-point Likert scale and screened using Principal Component …

Willingness To Pilot Under Varying Weather And Tower System Conditions: Mediating Effects Of Risk, Nathan Royal Schultz

Doctoral Dissertations and Master's Theses

The implementation of Remote Tower Systems (RTS) within the National Airspace System (NAS) offers potential improvements in operational efficiency, cost-effectiveness, and scalability; however, its success depends on pilots' willingness to operate in such environments. This study examined the effects of tower system type (RTS vs. Traditional Tower Systems [TTS]) and weather conditions (visual meteorological conditions [VMC], marginal visual meteorological conditions [MVMC], and instrument meteorological conditions [IMC]) on pilots’ willingness to pilot (WTP), while also evaluating the mediating role of perceived risk (PR). Grounded in Paul Slovic’s Risk Perception Theory (RPT), this research employed a quantitative experimental design using a factorial …

Thermo-Entropic Analysis Of Unsteady Mhd Nanofluid Couette Flow: A Classical Spectral Approach With An Exploratory Quantum Linear-Solver Application, Serai Israel Mosala, Oluwole Daniel Makinde, Azwinndini Muronga

Mathematical Modelling and Numerical Simulation with Applications

This study presents a thermo-entropic analysis of unsteady MHD nanofluid Couette flow, combining a classical bivariate spectral quasilinearisation (BI-SQLM) and Crank--Nicolson solution with an exploratory application of quantum linear solvers. An incompressible, electrically conducting nanofluid flows between parallel plates under partial slip and convective heat exchange; the discretised linear systems are additionally solved via the Harrow--Hassidim--Lloyd (HHL) algorithm and the Variational Quantum Linear Solver (VQLS). Results are presented for Pure Water, Cu-Water, and Al₂O₃-Water across seven parameter variations. The Hartmann number dominates velocity suppression and entropy amplification, while velocity slip reduces upper-wall entropy generation more than …

The Algorithmic Narcissus: Ai Validation And The Atrophy Of The 'Athletic' Social Self, Ilham Phalosa Reswara, Anggi Mayangsari

Jurnal Psikologi Sosial

Artificial intelligence systems designed around continuous affirmation and minimal friction are becoming increasingly prominent as social and relational partners in everyday life. This article examines how sustained interaction with such frictionless AI systems may reshape the developmental conditions under which social selfhood forms and is maintained. Drawing on Cooley's (1902) looking glass self, Kohut's (1971) concept of optimal frustration, and the developmental literature on social competence, the article argues that frictionless AI may distort the social mirror through which identity forms, remove the manageable frustration that appears necessary for psychological growth, weaken empathic capacity, and erode the social stakes that …

Effect Of Acid Pretreatment On The Adsorption Of Phenol Red By Cellulose Isolated From Sandbox (Hura Crepitans L.): Kinetics, Isotherms And Thermodynamics, Muibat O. Alabi-Abass, Najeem A. Adesola Babarinde, Adeola A. Ibikunle, Nurudeen O. Sanyaolu

Tanzania Journal of Science

The removal of synthetic dyes from wastewater remains an urgent environmental concern due to their persistence and toxicity. This study evaluates cellulose from Hura crepitans (HC) and its acid-modified form (AHC) for the adsorption of phenol red (PR) dye from aqueous solutions. The adsorbents were characterized using FTIR to identify functional groups responsible for dye binding, XRD to determine the crystalline structure, SEM to examine surface morphology, and BET/BJH analyses to measure surface area and pore distribution. Acid modification enhanced surface roughness, porosity, and the abundance of active functional sites, leading to improved adsorption efficiency. Optimal conditions were pH 9.0 …

Efficient Acidic H2O2 Electrosynthesis Over Co Atoms Anchored On Nitrogen-Doped Hierarchical Porous Carbon, Xiao Huang, Zi-Hao Zhan, Hao-Xu Niu, Guan-Yu Luo, Jin-Tao Huang, Bo-Xuan Jin, De-Li Wang

Journal of Electrochemistry

The two-electron oxygen reduction reaction (2e⁻ ORR) presents a promising route for the on-site production of hydrogen peroxide (H₂O₂), offering a green alternative to energy-consuming anthraquinone process. However, the high selectivity toward the competing 4e⁻ ORR over the desired 2e⁻ pathway leads to low Faradaic efficiency for H₂O₂, posing a critical challenge in catalyst design. In this work, a nitrogen-doped hollow hierarchical porous carbon with anchored Co atoms (CoN/HPC) was constructed for high-performance H₂O₂ production. The as-prepared Co-N/HPC catalyst showed excellent 2e⁻ ORR performance, achieving …

Engineering Small-Sized Cations With Strong Solvation For High-Voltage Supercapacitors, Tong Huo, Pan Liu, Hao Chen, Peng Zhang, Zhen-Lei Chen, Guo-Fu Sun, Zhi-Qiang Shi, Jing Wang

Journal of Electrochemistry

Supercapacitors (SCs) have attracted much attention in the field of energy storage due to their high power density and long cycle life. However, their relatively low energy density limits their application in a wider range of fields. Methods to increase energy density include enhancing specific capacitance and extending operating voltage window. Herein, we report a novel electrolyte salt, tetramethylammonium bis(fluorosulfonyl)imide (TMA-FSI), the resulting electrolyte formed with propylene carbonate (PC), designated as TMF, exhibited a wide electrochemical stability window (ESW) of 5.09 V. On the one hand, we found that the small size of TMA⁺ enables it to enter the …

Dense Platinum Nanoparticles Confined In Mn-N-C Nanocages For Robust Heavy-Duty Pemfcs, Lei Zhao, Zhen-Min Cao, Jia-Yu Zuo, Ming-Liang Yang, Hong-Yan Qiao, Jun-Song Chen, Rui Wu

Journal of Electrochemistry

High-loading Pt cathodes are essential for heavy-duty proton exchange membrane fuel cells but suffer from a critical tradeoff between ionomer sulfonate poisoning and nanoparticle instability. Herein, we report a spatial confinement strategy to encapsulate dense Pt nanoparticles (~51.8 wt%) within Mn/N-co-doped mesoporous carbon nanocages (denoted as Pt-MnNC). This architecture excludes bulky ionomers to create an ionomer-shielded environment against sulfonate poisoning, while Mn-N_x-mediated strong metal-support interactions anchor the Pt nanoparticles to prevent agglomeration and further boost durability. In the 5 × 5 cm² membrane electrode assembly tests, the Pt-MnNC catalyst delivers an exceptional power density of 1.26 W·cm …

Geotechnical Enhancement Of Noncohesive Coal Mine Overburden Using Microbially Induced Calcite Precipitation And Fly Ash Stabilization For Sustainable Pavement Applications, Atul Gautam, Laxmikant Yadu

Journal of Sustainable Mining

The majority of the waste generated from opencast mining, termed as overburden (OB), is dumped adjacent to the mine boundary and poses long-term stability issues. Various studies have been carried out to assess the risk of dump slope failure, and treatment strategies have been accordingly recommended to strengthen this OB dump. However, scant works are reported to sustainably utilize this OB for construction works. This study aims to quantify the performance of stabilized noncohesive coal mine OB collected from Gondegaon opencast mine (OCM) in India. Stabilization was achieved using two techniques, namely microbially induced calcite precipitation (MICP) through Sporosarcina pasteurii …

Reducing Drag Of Vehicles With Half-Stepped Cylinder Surfaces Part I: Numerical Optimization, Ryan Moffit, Hamid Rahai, Komal Gada

Mineta Transportation Institute

Aerodynamic drag is a major source of energy loss for vehicles, increasing fuel consumption, reducing the driving range of electric vehicles, and contributing to greenhouse gas emissions. For a vehicle, the major components of its drag are pressure and viscous drag. Engineers have developed a variety of strategies to reduce drag, including streamlined vehicle designs, surface modifications, and devices that alter airflow around the vehicle. This research focuses on reducing the viscous drag. Specifically, this study investigates whether microscopic surface features called half-stepped cylinder arrays can reduce skin friction by altering the turbulent boundary layer and promoting smoother airflow near …

Hands-On Ransomware: An Experiential Wannacry Case Study For Undergraduate Cybersecurity Education, Eli Creek Richmond, Thomas R. Devine

Military Cyber Affairs

Ransomware represents one of the most disruptive threats in the cyber landscape, yet hands-on malware analysis remains rare in undergraduate cybersecurity curricula. This paper presents the design, implementation, and evaluation of an experiential learning module centered on the WannaCry ransomware case study, deployed in a senior-level course at West Virginia University. Students performed static and dynamic analysis using industry-standard tools. Pre- and post-module assessments demonstrated measurable gains in self-reported competency across seven technical dimensions. The module's competencies align directly with DoD Cyber Workforce Framework Work Role 212, Cyber Defense Forensics Analyst, supporting education-to-workforce pipeline development.

Are Large Language Models Safe? A Vulnerability Analysis Of Generated Source Code, James Richards-Perhatch, Mitchell Milander, James M. Halvorsen, Assefaw Gebremedhin

Military Cyber Affairs

The increasing complexity of software and demands for rapid deployment have pushed the software industry to rely more on large language models (LLMs) in developing source code. However, as this technology is still relatively recent, questions can arise about the safety of the generated code. This paper presents an analysis of seven LLMs with respect to the presence of vulnerabilities within source code. Our findings show that LLMs are more likely to produce vulnerable web applications than vulnerable C programs, and that vulnerabilities are more likely to occur when program size and complexity increases.

Exploring The Role Of Single Pilot Operations In Night Cargo Aviation: A Phenomenological Study, Kollin Ellis

Doctoral Dissertations and Projects

The purpose of this qualitative descriptive phenomenology was to examine the lived experiences of pilots who have operated alone at night in an aviation cargo environment. The design was guided by an epistemological philosophical assumption. Extreme advancements in the technology of artificial intelligence and their applications in the aviation industry have raised the question of the value of a single operator serving in commercial cockpits. Some experts argue that a two-person crew is unnecessarily redundant. A significant gap in the current literature of experiential data existed to prompt this study. Through the contextual lens of the Dual Process Theory and …

Comparison Of Gravity Separation And Flotation For Pyrite Recovery From Tailings, Gülay Bulut, Gönül Göksu Gökçe, Dilruba Karamanlı, Oğuzhan Mert Gürkan, Ergin Sarp Zenzirci, Binnur Kırım, Alim Gül

Journal of Sustainable Mining

Tailings generated during the production of lead, zinc, and copper concentrates contain significant amounts of sulfide minerals, particularly pyrite. Pyrite, which remains in tailings after the recovery of other metals, is one of the main contributors to acid mine drainage (AMD). Therefore, recovering pyrite from tailings is environmentally and economically an important issue. In this study, pyrite recovery from tailings was investigated using flotation and gravity separation methods. Mineralogical characterization and liberation analyses were conducted by Mineral Liberation Analysis (MLA), indicating that pyrite is the major sulfide mineral with over 76% liberation degree even in the coarsest fractions. Flotation tests …

Challenges, Trends, And The Role Of Lstm In Ai-Based Predictive Maintenance Of Electrolyzers For Solar Hydrogen Systems: A Review, Yani Koerniawan Kuatno, Muhamad Zahim Sujod

Turkish Journal of Electrical Engineering and Computer Sciences

The transition toward low-carbon energy systems has increased interest in hydrogen as a clean energy carrier, with solar-driven water electrolysis emerging as a promising technology due to its high efficiency and compatibility with renewable energy sources. However, dynamic operating conditions and intermittent renewable input accelerate electrolyzer degradation, reducing reliability and system lifespan. Predictive maintenance (PdM), supported by artificial intelligence (AI), offers a data-driven approach to anticipate failures and improve operational durability. This review systematically investigates AI-based PdM approaches for electrolyzers, with an emphasis on long short-term memory (LSTM) networks and Internet of things (IoT) integration. Following PRISMA 2020 guidelines, 35 …

Dynamic Focal Loss Adjustment For Railway Defect Detection, Mehmet Koç, Ridvan Özdemi̇r, Ömer Gerek

Turkish Journal of Electrical Engineering and Computer Sciences

Railway infrastructure is critical to the safe and efficient operation of transportation systems, and the early detection of defects is essential for preventing catastrophic failures. Automated defect detection methods are therefore crucial for maintaining continuous safety while reducing maintenance costs. Although Focal Loss is widely used in object detection under class-imbalanced conditions, its fixed α parameter may limit its effectiveness in detecting rare defects. In this study, we propose an adaptive α-tuned Focal Loss approach that dynamically adjusts class weights based on average precision (AP) values. By iteratively optimizing α without relying on gradient-based optimization, the proposed method improves the …

Relative Rate Observer-Based Online Tuning Mechanism For Single-Input Interval Type-2 Fuzzy Pid Controllers, Oqba Aldreiei, Cenk Ulu, Mert Can Kurucu, Müjde Güzelkaya

Turkish Journal of Electrical Engineering and Computer Sciences

The characteristics of the footprint of uncertainty (FOU) in interval type-2 membership functions (IT2-MFs) are crucial to the performance and robustness of interval type-2 fuzzy controllers (IT2-FCs). However, existing IT2-FC design approaches mostly use fixed FOU structures. This study proposes an online membership function (MF) adjustment mechanism for a single-input interval type-2 fuzzy PID controller (SIT2-FPID)  that adjusts the FOU of the antecedent MFs and weights of the consequent MFs, respectively, to achieve high performance and robustness. The proposed online adjustment mechanism consists of a relative rate observer (RRO), a two-input rule-base adjustment system, and a first-order smoothing filter. The …

Cuip-X25: A Real-World Network Intrusion Dataset For Next-Generation Ai-Driven Security, Arshad Iqbal, Sohail Asghar

Turkish Journal of Electrical Engineering and Computer Sciences

The efficacy of artificial intelligence (AI) in intrusion detection systems (IDS) is critically dependent on high-fidelity training data. However, as detailed in the manuscript's literature review, existing benchmark datasets are predominantly synthetic, outdated, or imbalanced and fail to capture the complexity of the contemporary threat landscape. To bridge this gap, this study introduces CUIP-X25, a novel real-world cyber-attack dataset captured over a four-month period using a dionaea honeypot deployed on a public network. Unlike synthetic alternatives, this dataset provides an authentic representation of modern adversarial tactics, techniques, and procedures, encompassing 3.16 million real events across ten distinct attack categories, including …