Engineering Commons^™

Multiphysics Modeling Of Microwave-Assisted Calcination Of Soec Perovskite Precursors, Hongwei Liu

Graduate Theses, Dissertations, and Problem Reports (ETD)

The calcination of precursor powders is a critical step in the synthesis of solid oxide electrolysis cells (SOECs), where phase purity and microstructural control directly influence electrochemical performance. Conventional calcination methods are energy-intensive and time-consuming, often requiring prolonged high-temperature processing. In this thesis, microwave-assisted calcination is investigated as an alternative approach to enable rapid, energy-efficient processing of SOEC per- ovskite precursor powders. Microwave heating offers distinct advantages, including volumetric and selective heating, reduced processing times, and improved energy utilization compared to con- ventional thermal methods. A multiphysics modeling framework is developed, which integrates electromagnetic wave propagation, governed by Maxwell’s equations, …

Evaluation Of Engineering Controls In Mitigation Of Fecal And Chloride Contamination To An Urban Stream, Gabriel J. Zenny

Graduate Theses, Dissertations, and Problem Reports (ETD)

Fecal coliform contamination is a major contributor to surface water pollution in the United States’ (U.S.) waterways, whether from combined sewer overflows (CSOs) (point source pollution), runoff from precipitation and snowmelt (nonpoint source pollution), or exfiltration from aging and failing infrastructure. In addition to fecal bacteria, chloride contamination is also a major, prevalent surface water contaminant impacting U.S. waterways. Chloride contamination is predominantly released into U.S. waterways as nonpoint source pollution, endemic to northern areas that use industrial brine and salt as a form of mitigation for ice accumulation on roadways. The purpose of this research was to investigate impairment …

Plant-Wide Process Modeling, Techno-Economic Optimization, And Bayesian Uncertainty Quantification For Manufacturing Value-Added Products From Lignocellulosic Biomass, Poulomi Das

Graduate Theses, Dissertations, and Problem Reports (ETD)

For decades, many chemicals have been produced from fossil resources, contributing to resource depletion, pollution from extraction and refining, and hazardous byproducts. Growing environmental concerns and declining fossil reserves have intensified the search for sustainable sources of fuels, energy, and chemicals. Lignocellulosic biomass, the only abundant renewable carbon source, is therefore being explored as a feedstock for second-generation biofuels and high-value chemicals.

Currently, global wood-panel industry heavily depends on petroleum-derived commercial adhesives like phenol-formaldehyde, urea-formaldehyde, etc. These formaldehyde-based chemicals cause hazards to both human health and environment through emission of toxic volatile organic compounds. Typically, lignin is considered as one …

Semantic-Weighted Lidar–Camera Slam For Robust Mapping In Vegetation-Rich Environments, David Aigbovboise Akhihiero

Graduate Theses, Dissertations, and Problem Reports (ETD)

Many LiDAR odometry and SLAM methods are lightweight and effective, but they assume that all LiDAR point returns are equally reliable. In practice, this assumption is often violated in vegetation rich or semi transparent environments, where in a single beam footprint, LiDAR beams may intersect multiple scattering surfaces like leaves, branches or glass. These ambiguities in returns produces probabilistic or biased range measurements that violate the assumptions of most geometric registration frameworks and can lead to drift and inconsistency.

To address this challenge, this dissertation proposes a semantic-weighted LiDAR-camera SLAM framework that integrates class dependent weights into a front-end LiDAR …

Multi-Timescale Monitoring And Modeling For Resilient Smart Grids: Pmu Anomaly Detection And Battery Digital Twins, Muhammad Imran Hossain

Graduate Theses, Dissertations, and Problem Reports (ETD)

Modern power systems face failures at very different timescales. Cyber-physical disturbances may emerge within seconds, while battery degradation develops over hundreds of operating cycles. Both monitoring problems share the same underlying difficulty: power systems produce measurement data in abundance, but reliably labeled examples of abnormal or degraded operation are scarce. Rare grid events are difficult to label, and battery degradation data are heterogeneous across cells, cycling protocols, and chemistries. This thesis addresses these challenges through two complementary domain-informed learning frameworks that constrain representation learning using information specific to each physical problem.

First, at the system level, T-BiGAN, a Transformer-augmented bidirectional …

Cell-To-Pack Modeling Of Lithium-Ion Batteries: From Bayesian Parameterization To Pack-Level Optimization, Derek Slack

Graduate Theses, Dissertations, and Problem Reports (ETD)

One of the major hurdles for electric or hybrid aviation is the comparative energy density between lithium-ion batteries and jet fuel. To help obtain maximal power-to-weight ratio in electric or hybrid powertrains the battery pack design should be optimized to be as light as possible while meeting thermal safety and power requirements. The proposed solution is an optimization routine beginning with a cell-level parameter estimation of lithium-ion battery cells, where data driven Bayesian Gaussian Processes replace empirically or analytically derived parameters in a first principles electrochemical model in PyBaMM, as functions of the transient state of the cell. The resulting …

Physics-Informed Machine Learning Methods To Predict Heavy-Duty Diesel Engine Performance And Emissions, Sandeep Guguloth

Graduate Theses, Dissertations, and Problem Reports (ETD)

The development of internal combustion engines for increased efficiency and reduced emissions demands improved design tools that are cost-effective, fast, and easy to integrate into existing engineering workflows. Low-dimensional physically based engine models serve this role by reducing the need for iterative experimental prototyping but historically rely on empirical correlations that sacrifice fidelity compared to CFD. Machine learning (ML) approaches, conversely, achieve high predictive accuracy but lack interpretability and generalize poorly beyond their training data. Physics-informed machine learning (PIML) bridges this gap by constraining the solution space to physically feasible predictions, offering a more reliable way to model in-cylinder phenomena. …

Dataless Neural Networks For Boolean Satisfiability And Network Optimization, Andrew Evan Gautier

Graduate Theses, Dissertations, and Problem Reports (ETD)

Combinatorial optimization problems (COPs) require searching over a finite solution space subject to constraints, with the goal of satisfying an objective function. They arise in operations research, scheduling, resource allocation, circuit design, and many other fields. Many problems in combinatorial optimization (including satisfiability and network design) are NP-hard. Traditionally, researchers have built approximate solvers that return near- optimal solutions efficiently by developing increasingly sophisticated heuristics and meta- heuristics. Deep learning has provided new opportunities for improving combinatorial solvers by leveraging neural guidance to prune the search space. Traditional neural networks have distinct drawbacks in this context: separate training and …

Data Augmentation And The Reliability Of Conformal Prediction For Uncertainty Quantification In Medical Imaging, Rizwan Ahamed

Graduate Theses, Dissertations, and Problem Reports (ETD)

The safe clinical deployment of deep learning models for high-stakes medical imaging tasks requires more than high average accuracy; it requires demonstrable, per-case reliability. Uncertainty quantification (UQ) provides the missing signal that tells a clinician when a model prediction can be trusted and when a case should be escalated for expert review. Among UQ approaches, conformal prediction (CP) is especially attractive because it produces prediction sets that are guaranteed, under the assumption of exchangeability, to contain the true label with a user chosen probability, and it does so without assumptions about the model or the data distribution. This report first …

Student Support In Civil And Environmental Engineering, Heather Marie Rice

Graduate Theses, Dissertations, and Problem Reports (ETD)

Many student support services target first-year engineering students to help improve their transition from high school to college and to reach first-year retention goals. These opportunities are communicated to students through a variety of ways. The objectives of this work are to evaluate student perspectives of student services support factors in a civil and environmental engineering program and investigate how student support services and opportunities are communicated to students in a civil and environmental engineering program. The media identified for student support service outreach were the fundamentals of engineering program newsletters, academic advising newsletters, Statler eNews newsletters, and the bulletin …

Dielectrophoretic Biomarkers For Cancer Detection And Cell Analysis: Integrating Microfluidics And Ai, Raphael Olumide Oladokun

Graduate Theses, Dissertations, and Problem Reports (ETD)

Pancreatic ductal adenocarcinoma (PDAC) carries a five-year survival rate of 13%, driven largely by late-stage diagnosis and the absence of sensitive noninvasive screening tools. Current diagnostic methods lack the sensitivity to detect disease-associated systemic changes at early and precancerous stages, representing a critical clinical gap. This dissertation addresses the central hypothesis that PDAC and its pathological subtypes induce measurable, disease-associated electrophysiological changes in circulating PBMCs that can serve as correlative liquid-biopsy biomarkers. To test this hypothesis, this work asks: can dielectrophoresis (DEP), impedance and zeta potential analysis with AI-assisted classification distinguish benign pancreatic conditions (non-malignant control), precancerous lesions (primarily IPMNs), …

Multi-Sensor Fusion For Manual Wheelchair State Estimation, Kathylee Pinnock Branford

Graduate Theses, Dissertations, and Problem Reports (ETD)

Kathylee Pinnock Branford Manual wheelchairs are essential to mobility and independence, yet accurately characterizing wheelchair motion in real-world environments remains challenging. Inertial measurement units (IMUs) provide a practical means of estimating wheelchair kinematics, but existing trajectory-reconstruction studies have largely been limited to short, controlled trials. This report developed and evaluated a four-IMU framework comprising one sensor on each rear wheel and two sensors on the wheelchair frame. Three orientation algorithms (VQF, Mahony AHRS, and Madgwick AHRS), two accelerometer ranges (±2 g and ± 4 g), and calibrated and uncalibrated sensor data were evaluated during indoor motion-capture trials and a outdoor …

Process Optimization And Quality Control In Manufacturing Of Frp Composites By Vartm, Mohamed Emadeldin Omar Abdelhadi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Railroad tank cars, being one of the most used means of transportation of hazardous material across the country, have not been structurally upgraded for a long time. Thus, the Pipeline and Hazardous Materials Safety Administration (PHMSA), a United States Department of Transportation (USDOT) agency, released a rule for safer transportation of highly hazardous and flammable liquids by railroad to enhance the design specifications of both the new and existing tank cars in May 2015. A multifunctional composite jacket is proposed as a new material to structurally enhance the railroad tank cars to withstand any accidents that could happen en route. …

Assessing Mobility And Upper Extremity Function Beyond Laboratory Settings In Manual Wheelchair Users With Spinal Cord Injury Using Inertial Measurement Units, Kathylee Pinnock Branford

Graduate Theses, Dissertations, and Problem Reports (ETD)

Manual wheelchair users with spinal cord injury (SCI) face chronic, repetitive shoulder demands that far exceed those of able-bodied daily life, placing them at high risk for rotator cuff pathology and long-term upper extremity dysfunction. Despite this burden, existing research has relied predominantly on brief laboratory assessments that capture only a narrow part of real-world mechanical demands, leaving critical gaps in the identification of true injury risk factors. This dissertation developed and applied inertial measurement unit (IMU)-based methods and novel algorithms to characterize arm use, mobility, and environmental context during a full week of free living behavior in 25 manual …

Experimental Evaluation Of 100 Ft X 10 Ft Frp Truss Pedestrian Bridge, Ashish Dhital

Graduate Theses, Dissertations, and Problem Reports (ETD)

ABSTRACT

Experimental Evaluation of 100 ft x 10 ft FRP Truss Pedestrian Bridge

Ashish Dhital

FRP truss bridges are now increasingly used in pedestrian bridge applications due to their high strength-to-weight ratio, corrosion resistance, better impact performance compared with conventional materials, and ease of assembly. These advantages make FRP systems attractive for accelerated construction, remote-site installation, and environments where steel or reinforced concrete bridges may experience corrosion-related deterioration. Due to insufficient data on both strength and serviceability (i.e deflection, frequency) performances. Full-scale testing of FRP pedestrian bridges of longer spans (50’-100’) is needed to better understand the dynamic behavior, long-term …

Development Of Periodic Plasmonic Nano-Structures For Enhanced Labeled Bio-Sensing Systems, Kyle Zackary Smith

Graduate Theses, Dissertations, and Problem Reports (ETD)

The biomedical industry has seen sustained growth over the past half century, with a continually increasing demand for flexible, easy-to-use, and cost-effective tools. One large area of commercial interest has been point-of-use or point-of-care diagnostics, using optical based Lab-On-Chip (LOC) style systems. Label and label-free fluorescence detection systems are common benchtop modalities that have seen recent integration into these portable, cost-effective LOC applications. However, despite their maturity, there are still opportunities to improve device characteristics, specifically in reference to throughput, limit-of-detection (LOD), and hybrid integration (along with associated costs).

Optical research avenues at WVU have focused on improving these systems …

Deep-Learning-Based Generation Of Synthetic Contactless Fingerphotos, Christopher Harry Burton

Graduate Theses, Dissertations, and Problem Reports (ETD)

The collection of biometric data is a labor-intensive, high-resource process that presents significant logistical, privacy, and cost barriers for researchers and developers. To address these challenges, the biometrics community has increasingly turned to generative models capable of producing synthetic datasets that reflect the statistical properties of real data. While substantial progress has been made in synthetic fingerprint generation for contact-based modalities, the contactless fingerphoto domain has remained largely underserved. This work presents a deep learning-based approach to synthetic contactless fingerphoto generation using a Stable Diffusion model guided by multimodal conditions (text and image). The dataset used for training was collected …

Supply Chain Optimization For Fertilizer Production From Wastewater, Ethan Clement Robey

Graduate Theses, Dissertations, and Problem Reports (ETD)

In West Virginia, approximately 27,000 tons of wastewater solids are generated annually, with nearly 75% being landfilled or alternatively disposed of in a non-beneficial manner. Over the past two decades, the amount of these solids being taken for beneficial uses, such as agricultural application, has declined by 25%, while landfilling has increased by more than 30%. This highlights issues related to eutrophication and disposal costs. This study aims to develop a supply chain optimization framework that addresses the conversion of wastewater solids into fertilizers to match local farm requirements, while determining processing facility locations that minimize transportation costs. To determine …

Feasibility Study Of Concurrent Removal Of Organics And Ammonium Using An Iron Dosed Upflow Anaerobic Sludge-Blanket Bioreactor, Morgan Elizabeth Amos

Graduate Theses, Dissertations, and Problem Reports (ETD)

Aerobic microbial reactions have commonly been utilized in treatment processes to oxidize and remove organics and nitrogen through aeration, using processes such as nitrification that converts ammonium (NH₄⁺) into nitrite (NO₂^-) and nitrate (NO₃^-). Anoxic microbial reactions like denitrification often require organic compounds as an external source to chemically reduce the oxidized nitrogen (NO₃^- and NO₂^-) to nitrogen gas (N₂) for nitrogen removal from the liquid phase. These mainstream processes have a high chemical cost and energy footprint which results in an increased release …

A Study In The Advanced Manufacturing Of Full Solids Oxide Fuel Cells (Sofcs) Via Aerosol Deposition (Ad) Methods With Macro- And Microstructural Defect Characterization, Davis A. Warmuth

Graduate Theses, Dissertations, and Problem Reports (ETD)

The goal of this work is to 3D print a full SOFC layer-by-layer using aerosol deposition (AD) at a resolution of 5 μm. To achieve this goal, several studies were undertaken to develop and optimize an AD system to use ceramic inks. A 130 kHz AD system was developed with 4 material pumps to allow for depositions of individual compositions of the in-situ mixture of multiple solutions to allow for the fabrication of functional gradients in three dimensions. This system was then programmed to deposit air electrode layers containing different material ratios and porous microstructures, comparing their electrochemical performance to …

Process Modeling, Operability Analysis, And Techno-Economic Optimization Of Soecs For Sustainable H2 Production, Krishna Murthy Busam

Graduate Theses, Dissertations, and Problem Reports (ETD)

The global imperative to decarbonize energy systems has intensified research into sustainable hydrogen production pathways, as hydrogen emerges as a critical energy carrier for sectors difficult to electrify directly. Among water electrolysis technologies, solid oxide electrolyzer cells operating at elevated temperatures offer the highest theoretical efficiency by utilizing thermal energy to reduce electrical energy requirements, yet comprehensive frameworks integrating electrochemical modeling with process operability analysis and techno-economic optimization remain scarce in the literature. This dissertation develops a process systems framework for proton-conducting solid oxide electrolyzer cells that bridges the gap between fundamental electrochemical phenomena and industrial-scale process economics. At the …

A Multiobjective Framework For Joint Coverage And Motion Planning In Uav Inspection Tasks, Luis Fernando Escobar Carvajal

Graduate Theses, Dissertations, and Problem Reports (ETD)

Unmanned Aerial Vehicles (UAVs) have become essential for data acquisition in complex 3D environments. However, traditional Coverage Path Planning (CPP) methodologies often rely on a sequential pipeline that isolates viewpoint generation from flight path routing. This decoupling fails to account for the interdependence between viewpoint distribution and minimum flight paths, effectively restricting the search space and preventing the identification of a global optimum. This dissertation proposes a unified multi-objective framework for joint coverage and motion planning. The primary contribution of this work is the transition from isolated, sequential steps to a simultaneous optimization of the number and position of viewpoints …

Comprehensive Evaluation Of Co₂ Eor Numerical Modeling In The Clinton Sandstone Of The Appalachian Tri-State Region Using Compositional Reservoir Simulation (Cmg Gem), Bushra Aref Alqattan

Graduate Theses, Dissertations, and Problem Reports (ETD)

ABSTRACT

The Clinton Sandstone of the Appalachian Basin represents a mature hydrocarbon-producing formation with potential for carbon dioxide (CO₂) enhanced oil recovery (EOR). This study develops a compositional reservoir simulation model using the CMG software suite (WinProp, Builder, and GEM) to evaluate the performance of CO₂ injection in improving oil recovery within the Clinton formation.

A three-dimensional reservoir model was constructed using representative geological and petrophysical properties consistent with those of the Clinton Sandstone. Fluid behavior was modeled using a compositional equation-of-state (EOS) approach to accurately capture phase behavior, miscibility development, and CO₂–oil interactions under reservoir conditions. Injection scenarios were …

Machine Learning-Based Prediction Of Heavy-Duty Diesel Engine Emissions And Comparative Analysis Against Statistical Models, Abdullah Ahmad Khan

Graduate Theses, Dissertations, and Problem Reports (ETD)

The increasing stringency of emissions regulations for heavy-duty (HD) diesel engines necessitates the development of accurate, efficient, and general predictive models for engine-out emissions under steady-state operating conditions. Traditional statistical approaches, while computationally efficient, often fail to capture the inherent nonlinear relationships between the engine operating parameters and emissions formation. In contrast, machine learning (ML) techniques offer a promising alternative by learning the complex patterns directly from experimental data. The present thesis summarizes a comprehensive study on the prediction of steady-state, HD diesel engine emissions using ML models, along with a comparative analysis against conventional statistical modeling approaches.

A high-quality …

A Digital Calibration Source For 21 Cm Cosmology Telescopes, Kalyani Balkrishna Bhopi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Precise calibration of radio telescope beams and gains is a central requirement for 21 cm intensity mapping experiments, which aim to measure large scale cosmological structure through the redshifted emission line of neutral hydrogen. Bright astrophysical foregrounds dominate the sky at these frequencies, and separating them from the cosmological signal demands precise control over instrumental systematics, particularly the telescope beam and its frequency-dependent response. Existing aerial calibration sources are incoherent broadband emitters, detectable only as total power. They provide no direct phase information and suffer from poor sensitivity in low signal-to-noise regimes.

We present the Precision Emitter for 21cm Array …

Simulation Optimization Of Intermodal Freight Transportation Under Disruptions, Israt Humayra

Graduate Theses, Dissertations, and Problem Reports (ETD)

Rapid growth in freight transportation in modern supply chains has led to increased operational costs, congestion, and severe environmental impacts, especially greenhouse gas emissions. Combining different modes, such as highway, railway, and waterway, intermodal transportation could thus offer considerable benefit to improve efficiency, sustainability, and resilience. However, most existing planning approaches rely on simplified assumptions, fixed schedules, and average cost estimates, making them less relevant to dealing with real-world uncertainties and disruptions. This study develops a simulation-optimization framework for intermodal freight transportation under disruption. We develop a mixed-integer programming model to represent an intermodal logistics planning framework on a multi-layered …

Hyperglycemia Detection From Single-Lead Ecg Using A Hybrid Cnn & Transformer Model, Adam Ayomikun Ogunjembola

Graduate Theses, Dissertations, and Problem Reports (ETD)

Diabetes Mellitus is known as high blood glucose. This high blood glucose level happens when the body has a problem with producing or using insulin. Insulin is a very important hormone that the pancreas makes to control how much glucose gets into the bloodstream and cells. Diabetes Mellitus has an effect on the body if it is not treated, such as damaging the blood vessels and nerves which can lead to stroke, kidney failure, heart attack and permanent loss of vision. Since people with diabetes need to measure their glucose levels in order to determine how much insulin or medicine …

Bi-Level Optimization Of Peer-To-Peer Trading In A Decentralized Energy Market, Marshal Miezah

Graduate Theses, Dissertations, and Problem Reports (ETD)

Distributed power generation based on rooftop photovoltaic (PV) systems integrated with battery storage emerges as a promising pathway for reducing greenhouse gas emissions and im- proving flexibility in modern power systems. This study develops a bi-level optimization model to examine how prosumers maximize profit through peer-to-peer (P2P) energy trading with consumers and the grid, and how consumers minimize cost by leveraging P2P trading. The bi-level problem is reformulated as a single-level mixed-integer programming (MIP) model using Karush- Kuhn-Tucker (KKT) conditions to improve tractability and preserve market-clearing behavior. For the model validation and case study development, prosumer and consumer data are …

Elucidating Structure–Reactivity Relationships In Ni-Catalyzed Co2 Methanation, Majed Alam Abir

Graduate Theses, Dissertations, and Problem Reports (ETD)

The catalytic hydrogenation of carbon dioxide (CO₂) to methane represents a promising strategy for carbon utilization and renewable energy storage within power-to-gas systems. When coupled with hydrogen derived from renewable electricity, CO₂ methanation enables the conversion of intermittent energy sources into storable and transportable chemical fuels compatible with existing natural gas infrastructure. Nickel-based catalysts have emerged as leading candidates for this reaction due to their high activity towards CO₂ methanation, abundance, and cost. However, the performance and long-term stability of Ni catalysts are strongly influenced by catalyst support properties, Ni nanoparticle size, and promoter effect, and …

Swarm Of One: Self-Organization In Multicellular Robots, Trevor Riley Smith

Graduate Theses, Dissertations, and Problem Reports (ETD)

Designing robots traditionally relies on centralized, top-down methods that constrain adaptability and resiliency, producing systems optimized for specific tasks. However, such systems often fail in complex environments, such as extraterrestrial, disaster, or natural settings, where designers cannot foresee every scenario a robot may encounter. Achieving autonomy in these contexts requires robots that are resilient and capable of adapting to the unknown. Multicellular organisms exhibit this adaptability through self-organization, where complex structures and behaviors emerge from local interactions among their cells. Such organisms can be viewed simultaneously as a single entity and a swarm of cooperating cells, i.e., a Swarm-of-One.

This …