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Impact Of Bubble-Induced Turbulence On Two-Phase Flow Dynamics At High Void Fraction In A Large Diameter Channel, Sungje Hong, Joshua P. Schlegel, Subash L. Sharma

Nuclear Engineering and Radiation Science Faculty Research & Creative Works

This study represents the first investigation into the influence of bubble-induced turbulence (BIT) on interfacial area transport mechanisms in gas–liquid two-phase flows under conditions of high void fraction and high velocity in a large diameter channel. Given the unique characteristics of bubble flow in larger channels, the turbulent effects induced by bubbles differ from those observed in smaller channels. However, limited research exists regarding the impact of BIT beyond bubbly flows in large-diameter channels. To address this gap, two approaches for implementing the BIT model are explored: a direct method and an indirect method. This paper assesses both the general …

Robust Broadband Characterization Of Flexible Absorbers, Sheet Material, And Liquids Using A Coaxial Structure, Joseph Christopher Stecher

Masters Theses

Modern high-frequency measurement systems require reliable calibration and sample positioning to ensure measurement fidelity. This thesis presents three studies addressing practical limitations in broadband material parameter extraction and instrumentation.

The first study introduces a modified Nicolson–Ross–Weir (NRW) technique for flexible, compression-sensitive materials from 100 MHz to 18 GHz. Rigid 3D-printed spacers ensure precise sample positioning, and a T-matrix–based de-embedding procedure removes spacer effects. Validation using microstrip measurements and full-wave simulation confirms accurate permittivity extraction across compression levels.

The second study extends NRW to sheet materials enabling accurate material characterization. Independent validation using toroidal inductors with leakage correction and parallel-plate capacitors …

Analyzing Sleep Architecture And Brain State Transitions Via Hidden Markov Models On Fmri Data, Brileigh Jay Cates

Masters Theses

Sleep is associated with systematic changes in brain activity and functional connectivity observable in functional magnetic resonance imagining (fMRI) signals. Because subjects often fall asleep during resting-state experiments, the absence of vigilance monitoring can confound the interpretation of resting-state dynamics. Although electroencephalography (EEG) is the gold standard for sleep staging, simultaneous EEG-fMRI acquisition is not always feasible.

This study investigates whether sleep stages can be inferred directly from fMRI using a probabilistic latent-state framework. Hidden Markov Models (HMMs) are applied to blood-oxygen-level-dependent (BOLD) time series to identify latent brain states and their temporal transitions. Inferred states are aligned with EEG-derived …

Architecting A Complex Adaptive System Model For Selecting Policies To Reduce Kidney Discard, Lirim Ashiku

Doctoral Dissertations

"The kidney allocation system is a complex, evolving system involving multiple heterogeneous agents. Each agent exhibits emergent behavior that may not fully align with the complex system goals. Therefore, there is a need for a transdisciplinary systems approach to visualize the interdependency among agents and understand the dominant patterns that shape the kidney allocation system.

First, this research presented an incremental hierarchical system engineering approach in identifying the agents’ needs and behaviors toward the complex systems’ goal of maximizing deceased donor kidney utilization and reducing kidney discard. The hierarchical systems approach linked with model-based system engineering aided in eliciting agents’ …

Theoretical Study Of Long-Range Molecular Interactions, Adrian Luis Batista-Planas

Doctoral Dissertations

Describing intermolecular forces is fundamental to modeling and predicting the behavior of molecular systems. In particular, long-range molecular interactions—with electrostatic, induction, and dispersion as main components—play a critical role, especially for low-temperature and low-density regimes. Long-range interactions are often described through perturbation theory, representing the electronic charge distribution via multipolar series of the moments and polarizability tensors corresponding to each molecule. However, while the theory is well-established, obtaining the resulting analytical expressions (and their practical implementation) constitutes a highly complex and system-dependent task. To address this challenge, we developed Long-Range-Fit (LRF), an interactive and user-friendly software package designed to automate …

Security And Energy-Efficiency In Federated Learning, Priyesh Ranjan

Doctoral Dissertations

Federated Learning (FL), which facilitates collaborative model training and protects users' privacy, has drawn great interest from the research community. With FL, the participants train their models on local data and submit the corresponding updates for aggregation to a server. While concealing the participants' identities, FL may attract adversaries aiming to hamper the underlying model. These adversaries aim to submit malicious weight updates that corrupt the performance of the server model. Further, these models when communicated to the participating clients extend the behavior which is undesirable. Additionally, FL suffers from increased energy consumption at the edge device level due to …

Adaptive Machine Learning Framework For Microstructural Optimization And Mechanical Performance Prediction In Steels, Henry Adekola Haffner

Doctoral Dissertations

Evolution of microstructures, such as polygonal ferrite, acicular ferrite, bainite, and martensite, plays a pivotal role in determining the final microstructural and mechanical properties of steel products. Given the established inter-relationship between processing parameters, microstructure, properties, and performance, precise control of phase transformation is essential to achieve pre-determined properties. To understand transformation routes in different steel grades, time-temperature-transformation (TTT) and continuous-cooling-transformation (CCT) diagrams are necessary and can be described using the Johnson-Mehl-Avrami-Kolmogorov equation and Scheil’s additivity rule. This study presents a comprehensive computational framework for predicting and optimizing microstructure and mechanical properties in advanced high-strength steels (AHSS) using adaptive machine …

Exploring New Poly-Anion Based Materials For Lithium – Ion Battery Cathodes, Sutapa Bhattacharya

Doctoral Dissertations

The escalating global demand for sustainable energy storage solutions has driven intensive research into novel electrode materials. Polyanion-based cathode materials have emerged as promising candidates due to their structural stability, safety, and voltage tunability enabled by the inductive effect of polyanionic groups. This research explores the synthesis, crystal structure, and electrochemical performance of new polyanion-based cathode materials featuring vanadium, molybdenum, and iron within phosphate and selenite frameworks.

Novel selenite-based materials, such as LiFe(SeO₃)₂ and Li₀.₂₅V₂O₃(SeO₃)₂, were synthesized and characterized, revealing stable electrochemical cycling associated with Fe2+/Fe3+ and V⁴⁺/V⁵⁺ transitions. Additionally, a systematic investigation was conducted on molybdenum phosphate compounds, including …

Essays On Accelerated Failure Time Models For Recurrent Event Data, Emmanuel Masavo Djegou

Doctoral Dissertations

Recurrent event data arise in many fields such as medicine, reliability, insurance, and economics, where the same event may occur repeatedly for a subject. Accelerated Failure Time (AFT) models provide an intuitive framework for relating covariates to event times and offer a useful alternative to proportional hazards models, allowing direct prediction of event timing under right censoring. However, existing AFT extensions for recurrent events, such as accelerated gap time (AGT) models, often fail to account for interventions between events and may not capture complex temporal patterns.

In this work, we first propose a class of semiparametric AGT models incorporating an …

Zirconium Carbide Based Materials For Extreme Aerospace Environments, Nathaniel Hyman Blatt

Doctoral Dissertations

This research focuses on the processing and properties of zirconium carbide-based materials to promote their use in extreme environment aerospace applications, including nuclear thermal propulsion and hyper sonics. Several carbide systems including ZrC, ZrC-Mo cermets, (Zr, Nb)C, and a high entropy carbide were developed. The ZrC-Mo cermet was studied extensively to understand the effect of starting carbide grain size on the final microstructure, composition, elastic moduli, hardness, fracture toughness, room and elevated temperature flexural strength, thermal diffusivity, electrical resistivity, thermal expansion coefficient, and thermal conductivity. It was shown that heat transport in the cermets was dominated by the ZrC phase …

Incremental Cluster Validity Indices And Their Role In Interpreting Lifelong Learning Systems, Niklas Max Melton

Doctoral Dissertations

Clustering and supervised learning are often treated as distinct paradigms, yet both rely on structure in feature space. This dissertation investigates the relationship between cluster validity indices (CVIs) and supervised learning in real-time and lifelong learning settings where data arrive incrementally and cannot be revisited. Across four studies, it develops methods for online cluster validation, uses supervised learning to improve their interpretability, and applies these ideas to evaluating performance degradation in continual learning.

The first study extends incremental cluster validity indices (iCVIs), enabling widely used validation metrics to operate in streaming environments. Experiments on synthetic and real-world datasets show systematic …

Probability Of Detection For Corrosion-Induced Mass Loss And Yield Strain In Metal Structures Using Fe-C Coated Long Period Fiber Gratings Sensors And Electroresistive Strain Gauges, Ying Zhuo

Doctoral Dissertations

"Graphene-based, Fe-C coated long-period fiber grating (LPFG) sensors individually reveal a causal relation between LPFG wavelength change and Fe-C mass loss. Their correlation parameters vary significantly between the sensors mainly because hydrophobic multilayer graphene and graphene oxide make sensor fabrication inconsistent. This study explores MXene-based, Fe-C coated LPFG sensors due to MXene’s inherent hydrophilic property in the presence of surface functional groups such as hydroxyl and oxygen and the probability of detection (POD) for mass loss from Fe-C coated LPFG sensors when deployed at a fixed location. A novel fabrication process incorporating Piranha solution pretreatment is proposed to ensure uniform …

Bond Graph And Extended Generalized Average Method With Applications In Cyber-Physical Systems And Power Electronics, Arnold Anthony Fernandes

Doctoral Dissertations

"This research examines two applications of control theory. The first application considers the bond graph (BG) modeling technique, which is used to develop the MATLAB structural analysis toolbox (MATSAT), an open-source toolbox for sensor placement and qualitative system analysis that considers the observability and fault-detection capabilities of multi-domain cyberphysical systems. The toolbox provides information on redundant sensors, guiding the system designer in cost and security trade-offs. The toolbox uses traditional BG causality assignment procedures. Additionally, MATSAT provides optimal causality assignment methods that perform significantly better at assigning causality to BGs with increased junctions, sources, and simple meshes, without encountering causality …

Quantifying, Forecasting, And Mitigating Construction Labor And Material Challenges In A Dynamic Global Economy Using Econometrics And Deep Learning, Ahmed Gamal Elsayed Mohamed Shiha

Doctoral Dissertations

"The construction industry contributes to the global economy, yet its cost management practices remain constrained by labor shortages and material price volatility. These challenges are intensified by economic disruptions, geopolitical tensions, and trade policy shifts. Despite a growing body of literature, five knowledge gaps remain unaddressed: (1) the absence of dynamic, and localized measures of construction labor shortages; (2) limited empirical investigation of macroeconomic leading indicators of labor shortages; (3) underutilization of deep learning (DL) algorithms in forecasting local construction labor earnings; (4) the limited treatment of structural breaks in existing construction material price forecasting models; and (5) the lack …

An Energy-Stable Mixed Cg-Dg Scheme For A Full Shliomis Phase Field Model Of Two-Phase Ferrofluid Flows, Mahdi Gharehbaygloo

Doctoral Dissertations

"Ferrofluids are magnetic nanoparticle suspensions whose motion couples surface tension, flow field, magnetostatics, and magnetization dynamics. This dissertation develops, analyzes, and validates an energy-stable finite element method for a two-phase ferrofluid model that couples the Cahn-Hilliard equations with the full Shliomis model of single-phase ferrofluids, retaining its damping torque term, magnetic torque term, and magnetic stress term.

The spatial discretization is a mixed continuous Galerkin (CG) and discontinuous Galerkin (DG) formulation. It uses continuous ��2 elements for the phase field, chemical potential, velocity, and magnetostatic potential, discontinuous ��2 elements for the magnetization, and discontinuous ��1 elements for the pressure. The …

Innovative Methods In Intact Rock Deformation Detection, Ali Abdullah M Alzahrani

Doctoral Dissertations

"An accurate assessment of intact rock deformation is imperative in engineering activities carried out either in or above rock masses. However, instruments used for post-peak deformation are easily debonded and cannot record the whole process of post-peak deformation required in the failure modeling of rocks. This dissertation focuses on the investigation of the performance of two non-contact measuring systems (Laser Displacement Sensor (LDS) and Inductive Proximity Sensor (IPS)) compared to the contact type instrument (conventional Strain Gauge System (SGS)) in monitoring intact rock deformations. Subsequently, an IPS was installed in a high-pressure triaxial testing system before investigating its performance in …

Harnessing Coherent-Wave Control For Sensing Applications In Scattering Media, Pablo Xavier Jara Palacios

Doctoral Dissertations

"Diffuse electromagnetic waves are widely used for non-invasive sensing and imaging in complex scattering media such as biological tissues. A fundamental limitation of such techniques is the scarcity of detected photons: as the source-detector separation increases to access deeper regions of the medium, the signal strength decays rapidly, leading to poor signal-to-noise ratio and limited sensitivity. This dissertation addresses this challenge through a combination of theory and computation.

We show that coherent control of the incident optical wavefront can compensate for the scarcity of detected photons that limits conventional diffuse optical imaging, typically performed in the near-infrared spectral region. By …

Empirical-Based Model Of Spatio-Temporal Errors, Godwin Naaba Ndaa

Masters Theses

This research develops an empirical model to characterize spatial-temporal InSAR errors and improve the accuracy of deformation time-series analysis. Using standardized Sentinel-1 HyP3 products and MintPy, the study quantifies how correlated noise affects velocity precision and validates the results against continuous GNSS velocities.

Residual velocities are near-Gaussian, with σ ~0.92–2.04 cm/yr and ~1 cm/yr on average. Variograms show power-law spatial structure with a non-zero nugget implicating troposphere and decorrelation while errors drop exponentially with more acquisitions; spatial uncertainty is strongly affected by unwrapping errors, coherence, and tropospheric noise, not simply troposphere.

A comparative assessment of on-demand cloud processing with other …

Assessment Of Simulation Software Used For Cubesat Gnc Verification And Validation By University Research Teams, Alexander Taiyo Newett

Masters Theses

As the growth in university satellite teams continues, along with the greater trend in the small satellite market, the need for a guidance, navigation, and control verification and validation pipeline suitable for these young and inexperienced teams becomes evident. Much of the mathematical theory and software implementation of GNC concepts are large hurdles for teams largely composed of undergraduate students.

Many software packages exist that can help these teams achieve GNC verification and validation. If the learning curves of these software packages can be overcome, new satellite teams have the opportunity to better build and test GNC algorithms that are …

Assessment And Comparison Of Selected Carbon Ablation Models In Hypersonic Free-Flight And Arc-Jet Conditions, Andrew Steven Heider

Masters Theses

Accurate prediction of ablative thermal protection system (TPS) performance is critical for hypersonic vehicle design. However, numerical prediction of ablation remains challenging because results are influenced by complex physics and the choice of surface chemistry model and assumptions made in material response calculations. The objective of this work is to evaluate several carbon ablation models and their implementation within modern computational fluid dynamics (CFD) codes. Numerical simulations were performed using NASA’s LAURA flow solver and the commercial CFD code ANSYS Fluent, which coupled Navier-Stokes with surface chemistry models describing carbon oxidation, nitridation, and sublimation reactions. Several reaction sets were considered, …

Autonomous Navigation Development And On-Ground Validation For Satellite Rendezvous And Proximity Operations, Logan Banker

Masters Theses

Spacecraft rendezvous and docking are critical mission phases for various applications of spaceflight, including active debris removal (ADR) and in-orbit servicing, assembly, and manufacturing (ISAM). While previous missions utilized humans to perform rendezvous and docking, this style of mission greatly increases safety risks and cannot be implemented on a large scale. Autonomous servicing satellites provide a path towards scalable rendezvous and proximity operations (RPO) because these autonomous agents do not require human intervention. This work presents a lightweight convolutional neural network (CNN) for the navigation system of an agent which analyzes monocular images and predicts the target's position and orientation …

Investigating The Dynamic Rating Method: Effects Of Flood Wave Geometry On Discharge Estimation, Daniel James Read

Masters Theses

Rating curves are a vital tool to convert from observed stage to discharge in streamflow monitoring. Most gaging sites utilize a simple rating curve, which assumes a monotonic relationship between stage and discharge. In most cases, this assumption is valid; however, dynamic effects of flood waves often cause significant error in discharge estimation for mildly sloped streams. The dynamic rating method utilizes a numerical solution of the St. Venant Equations applied to time series stage data to compute discharge. Within this method, there is a flood wave parameter called the flood wave factor. The researchers designed a formal computational model …

Validating A Low-Cost Radio Frequency Characterization Framework For Development-Grade Software-Defined Radios In Short-Duration Cubesat Missions, Thomas Wayne Francois

Masters Theses

Software-defined radios (SDRs) and CubeSat platforms have reduced the cost and complexity of space-based communication systems, enabling broader participation in satellite missions. While low-cost radio hardware is increasingly accessible, the ability to characterize and validate its performance remains constrained by the high cost and limited access to traditional RF test equipment. This disparity creates a challenge for small satellite development teams, which must characterize communication-system technical performance with limited access to laboratory-grade instrumentation.

This thesis presents a low-cost RF characterization framework for assessing key radio-frequency performance metrics using readily available hardware and measurement techniques. The approach integrates frequency translation, SDR-based …

Examination Of Laser Microwelding As A Technique For The Repair Of Steel Castings, Allan John Woldow

Masters Theses

"Metal castings have long been plagued with minor defects caused by various process and design conditions. Commonly, minor defects are not seen until after machining operations have been completed, and by the time they are identified, they cannot be salvaged in a manner that is structurally sound and does not have other detrimental effects on the product. Detrimental effects may include warping from high heat input in traditional welding, warping from reheat treatment, oxidation of machined surfaces, microstructural anomalies, and reduced mechanical properties. Micro laser welding has the potential to provide a solution to these issues by providing a low …

Specialty Glass Fibers For Optical Applications, Theodore Carver Lewis

Masters Theses

"Fibers were draw from melts of a commercial Na-aluminosilicate for ion-exchange treatments. A process was developed to draw 100-meters of fiber with a diameter of 100±10m. The fibers were sectioned for ion exchange treatments. SEM analysis showed an ion penetration depth of 45um after 4 hours of ion exchange in a 400°C KNO3 salt bath. The pristine and ion-exchanged fibers were characterized by a two-point bend test in room temperature air with controlled relative humidity (RH) and faceplate velocities between 100 and 4000 μm/s to characterize fatigue effects. Pristine fibers tested in air (40% RH) at 4000 μm/s had failure …

Transformer-Based Language Models For Bitcoin Market Prediction And Interpretation, Erich Gozebina

Masters Theses

"In the context of a Master's thesis in applied mathematics, this work investigates compact transformer-based language models as an instrument for Bitcoin-related predictions and decision support. The work connects three topics: the structure of the Bitcoin system and its data, the mathematical and algorithmic foundations of deep autoregressive transformers, and the design of practical training pipelines for financial applications. On this foundation, a reproducible ETL pipeline for Bitcoin data is developed and two forecasting experiments are conducted with the compact language model nanochat. The first experiment approaches the prediction of next-day price movements through autoregressive next-token generation based on structured …

Characterizing A Delay-Programmable Two-Color Femtosecond Light Source For Coherent Control Of Atomic Multi-Photon Ionization Processes, Mason Tanner Toombs

Masters Theses

"In this work a delay-programmable two-color femtosecond laser based on a chirped-seed noncollinear optical parametric amplifier was characterized. This design utilizes a titanium-sapphire crystal oscillator to generate broadband pulses of light spanning approximately 600-1200 nm, with a pulse duration of ~5 fs, repetition rate of 80 MHz, and pulse energy of ~2.5 nJ. An infrared portion of the light, spanning approximately 1020-1060 nm, is split off from the pulse and used to generate a pump beam. By dispersing the remaining seed beam and controlling the relative timing delay between the seed and the pump, tunable frequencies within the seed can …

The Occurence Of Expansive Clay Soils In Illinois And Their Effects On Shallow Lightly Loaded Foundations, Greg James Gollaher

Masters Theses

"The damage caused to shallow foundations and slabs on grade by the shrink-swell activity of clay soils is well documented across the United States. There are local and national resources available that delineate areas that are problematic and areas that are not. These resources paint Illinois as an undemanding foundation environment. However, our experience differs from this. Our experience tells us that damage related to the shrink-swell activity of clay soils is widespread, and commonly severe causing not only cosmetic damage to structures and hard improvements but also affecting the serviceability and longevity of structures. My goal is to accurately …

General Approach To Determining The Embodied Energy Of Refractory Products, Jacob A. Kerr

Masters Theses

"Refractories are an important group of engineered materials that are critical for sustaining life in the modern age. These products are key components in many industrial processes, such as the production of steel, cement, glass, aluminum, copper, lead, and many others. It is estimated that 50 million tons of refractory products are produced and used around the world every year. Of this, an estimated 28 million tons of spent refractory is generated after use, much of which ends up in landfills all over the globe. By utilizing embodied energy methodologies, a complete sum of energy inputs can be mapped throughout …

Simulated Lunar Gravity Testing Of A Magnetic And Electrostatic System For Beneficiating Lunar Regolith, Blake A. Coffman, Gabriel Porter, Lindsay Manteufel, Mitchell Cottrell, Jeffrey D. Smith, David J. Bayless, William Shonberg, Frank D. Han, Fateme Rezaei, Kirby Runyon

Materials Science and Engineering Faculty Research & Creative Works

We present the design and testing of a lunar regolith beneficiation device that utilizes magnetic and electrostatic separation methods to concentrate desired minerals by removing unwanted material, such as the mineral anorthite, from bulk lunar regolith. The beneficiated materials would have value for downstream in-situ resource utilization (ISRU) processes such as metal extraction, oxygen extraction, and metal oxide additive manufacturing processes. The apparatus uses a dual-strength magnet system with N52 and N42 neodymium magnets to separate particles by magnetic susceptibility. The electrostatic separation system, which acts like a sieve, sorts the regolith simulant by particle size using a single-phase 50% …