Digital Commons Network^™

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 …

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 …

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 …

Temperature-Dependent Dielectric Function Of Solids From Coupled Oscillators With Radiation Reaction: Application To Atom–Surface Interactions, Tuhin Kanti Das

Doctoral Dissertations

In this dissertation, we propose a uniform functional form of the dielectric function of solids that is applicable over a wide range of frequencies. We apply our model to describe the dielectric function of two technologically important materials: silicon and calcium fluoride. The temperature dependence of their dielectric functions is also described using simple analytic forms. We found that a generalized Sellmeier-type model with complex denominators (“damped oscillators”) does not lead to a satisfactory fit of experimental data for the dielectric function. In contrast, our model, which is analytically only slightly more involved (“complex oscillator strengths”, complex numerators), allows us …

Investigations In Hydrogen Ironmaking, Joseph William Govro

Doctoral Dissertations

The purpose of this research is to contribute to the Grid Interactive Steelmaking with Hydrogen (GISH) project. This research investigates the viability of both producing and melting Direct-Reduced Iron (DRI) utilizing hydrogen. Conventional CO reduced DRI will be referred to as “C-DRI” and DRI produced using hydrogen gas will be referred to as “H-DRI”.

An H-DRI pilot plant was constructed in Golden Colorado. The pilot plant was commissioned and successfully operated four campaigns. Process improvements were made throughout the campaigns and the process was optimized. In addition to running the pilot plant in a pure hydrogen condition, the pilot plant …

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 …

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 …

Machine Learning Based Automation Of Pcb Pdn Design And Optimization, Haran Manoharan

Doctoral Dissertations

The rapid increase in power density and stringent power-integrity requirements in modern System-on-Chip (SoC) platforms have made Power Delivery Network (PDN) design an increasingly complex, multi-stage challenge. Critical decisions must be made both during pre-layout planning, such as stackup configuration, power-plane geometry, and early decoupling capacitor (decap) budgeting, and during post-layout refinements. Traditional heuristic and evolutionary optimization techniques struggle with scalability, require extensive manual iteration, leading to long runtimes and limited adaptability across varying board configurations. To address these challenges, this work proposes a unified reinforcement-learning-driven framework for automated PDN synthesis and decap optimization that spans both pre-layout and post-layout …

Advancing Coal Rib Support Design Through The Integration Of Field Studies And Numerical Simulations, Alper Kirmaci

Doctoral Dissertations

Coal rib stability remains a major safety concern in U.S. underground coal mines, with rib failure-related injuries and fatalities still occurring. A key challenge is the lack of a standardized methodology for designing rib support systems that can address varying geological conditions. As a result, many mines rely on trial-and-error or traditional practices, leading to inconsistent designs. This research aims to develop a systematic methodology for rib support design to improve coal rib stability in U.S. mining operations.

The study consists of: i) field monitoring in active room-and-pillar coal mines, ii) in-situ pull-out tests on coal ribs, iii) numerical model …

Critical Parameters Controlling Oxide Scale Formation And Hydro-Descaling Efficiency During Steelmaking, Tochukwu Princewill Ojiako

Doctoral Dissertations

In modern steelmaking, cast slabs are exposed to high-temperature oxidizing environments during secondary cooling, reheating, and hot rolling, resulting in the formation of multilayer oxide scales on the steel surface. These scales interact with mold-flux residues originating from the casting process (CC). The morphology, chemistry, and adhesion of oxide scale strongly influence its removability during high-pressure hydraulic descaling and ultimately determine the surface quality of hot-rolled products. However, the mechanistic relationship between oxide scale evolution, scale-steel interfacial structure, and hydraulic descaling performance remains poorly understood.

This dissertation investigates oxide scale formation, modification, and removal in low-carbon thin-slab steels produced by …

Accelerating Circular Economy Transition For A Sustainable Built Environment: A Systems-Based Framework, Radwa Walid Yassin Eissa

Doctoral Dissertations

"The Circular Economy (CE) has gained momentum as a transformative framework for steering the construction value chain towards greater sustainability. However, this transition requires shifts in production and consumption patterns, adoption of circular business models, and the replacement of linear practices. Despite growing interest, CE adoption in construction faces persistent challenges, including sectoral fragmentation, lack of integrated governance frameworks, and limited coordination among stakeholders. This dissertation aims to accelerate the CE transition in the built environment through a multi-scale, interdisciplinary approach spanning five modules: (1) Module 1 develops a construction value chain-structured portfolio of CE strategies and assesses their implementation; …

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, …

Optimal Slotting In Hybrid Warehousing For Industry 4.0, Teng Yang

Masters Theses

In the era of Industry 4.0, the warehouse management system (WMS) employed by many firms prescribes hybrid storage, i.e., products with high turnover, called fast movers, are kept in random storage for a short time duration before being shifted to a dedicated storage area, while products with low turnover, called slow movers, remain in random storage. From dedicated storage, the products are dispatched to the customer. The challenge for managers is selecting the slot in dedicated storage to assign to each product while demand data change because of fluctuating market conditions; this problem is referred to as slotting in the …

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 …

Calcium Based Carbon Negative Fillers And Additives: Effects On Hydration And Performance Of Low-Carbon Cement Systems, Smita Bhowmick Shithi

Masters Theses

Cement production is a major source of global CO₂ emissions creating an urgent need for carbon-negative fillers and functional additives that lower clinker use while maintaining cement performance. This thesis investigates the effects of organic mineral salts as fillers and additives on cement hydration, fresh properties, compressive strength and pore structure. In the first study, ordinary Portland cement (OPC) was partially replaced with calcium carbonate or calcium oxalate to enable a direct comparison under controlled particle size distribution (PSD). Rheology, flowability, hydration kinetics, phase evolution, mechanical performance and water absorption were evaluated. Calcium carbonate promoted early hydration through nucleation and …

Developing Discharge Estimation Algorithm Using Low-Cost Velocity Sensor And Machine Learning, Barkha Gautam

Masters Theses

Accurate river discharge estimation is essential for flood forecasting, water resources management, and hydraulic decision-making; however, continuous discharge records are unavailable at many river locations. Traditional stage-discharge rating curves are widely used but their reliability may decrease when channel conditions change or flow conditions vary rapidly. This study develops and evaluates Long Short-Term Memory (LSTM) models for discharge prediction using 15-minute time-series data from river monitoring stations in Missouri. Two model configurations, a baseline stage-only model and an enhanced stage-plus-velocity model, are developed and evaluated independently at two river sites to determine whether the inclusion of surface velocity improves discharge …

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 …

Aura-Visionpose: Creating Datasets For Vision-Based Pose Estimation, Mohanad Alameer

Masters Theses

"Spacecraft rendezvous is an integral part of many orbital missions, including active space debris removal (ADR) and in-orbit servicing, assembly, and manufacturing (ISAM). Traditionally, rendezvous missions rely mainly on manual ground-based control to perform rendezvous and docking. While this can be effective on an individual basis, it becomes less practical at scale. Autonomous vision-based methods can reduce reliance on human control, and may improve scalability, response time, and reduce the possibility of human error for both ADR and ISAM. This work lays the necessary groundwork for developing a machine learning (ML) model for autonomous rendezvous by creating a labeled image …

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 …

Castrip Process Technology: Non-Grain Oriented (Ngo) Si Steels Extension And Carbide-Free Bainitic (Cfb) For Flat Products, Naram Naidu Meesala

Masters Theses

"This research explores the development of advanced steel grades manufactured through Castrip® twin-roll thin strip casting technology, with particular attention to non-grain-oriented electrical Si-Steels (NGOES) and carbide-free bainitic (CFB) steels. The Castrip® process offers a near-net-shape route for producing thin steel strips, which greatly decreases the number of processing stages, lowers energy demand, and reduces carbon dioxide emissions when compared with traditional steel production methods.

In the NGOES part of the study, several industrial Fe–Si steel compositions were cold rolled to final thicknesses ranging from 0.35 mm to 0.15 mm. These materials were then exposed to short-duration continuous annealing at …

Structured Decomposition And Efficient Adaptation For Scientific Data Movement: From Transfer Concurrency To Genomic Data Acquisition, Rasman Mubtasim Swargo

Masters Theses

"The end-to-end performance of scientific data movement is increasingly limited not by raw network capacity but by whichever resource along the path is momentarily slowest, a bottleneck that no single static configuration can track. This thesis argues that the right response is to decompose each problem along the resource or workflow axis where bottlenecks vary, adapt only the genuinely dynamic control variables at runtime, and make that adaptation efficient through utility-guided or offline-learned control rather than expensive online search. The thesis develops this principle through four systems of widening scope. AutoMDT decomposes a transfer by operation, assigning separate concurrency levels …

Optical Fiber Eaf Refactory Lining Temperature Monitoring For Safety And Operating Efficiency, Manoj Kumar Pullagura

Masters Theses

"Electric arc furnace (EAF) sidewalls experience severe thermal, chemical, and mechanical loading, especially near burner and injector regions where refractory wear and water ingress from damaged cooling components pose safety risks. Conventional thermocouples and resistance temperature detectors provide reliable point measurements but lack the spatial resolution needed to capture steep gradients and localized anomalies. This research investigates embedded optical fiber sensors for high-resolution temperature monitoring of EAF refractory safety linings to support early water-leak detection and assessment of refractory thermal behavior. A combined Rayleigh backscattering-based optical frequency domain reflectometry (OFDR) and fiber Bragg grating (FBG) approach was evaluated through laboratory …

Dean's Update, January 2026, Neil W. Schluger

SOM Dean's Research Newsletter

No abstract provided.

Linking Women’S Empowerment And Community Contexts To Intimate Partner Violence: Evidence From Ten West African Countries, Winfred A. Avogo

Faculty Publications – Sociology and Anthropology

Abstract Purpose Intimate partner violence (IPV) is experienced by over one-third of women in sub-Saharan Africa, yet evidence on the associations between women’s empowerment, community contexts, and IPV risk remains limited and inconsistent. This study examines the association between individual empowerment and community socioeconomic conditions and different forms of IPV across West Africa, using the Survey-based Women’s Empowerment Index. Method Demographic and Health Survey data (2018–2022) from ten West African countries were pooled, yielding a sample of 38,434 ever-married or cohabiting women who completed the domestic violence module. Multilevel binary logistic regression models estimated associations between empowerment dimensions, community characteristics, …

Caterpillar's Spatial Metamorphosis: Heavy Equipment Manufacturing In The 21st Century, Utkarsh Kumar, Michael L. Dougherty

Faculty Publications – Sociology and Anthropology

Caterpillar Inc., the world's largest heavy equipment manufacturer, grew rapidly in the 20th century before a crisis of overproduction in the early 1980s threatened its survival. In response, it launched the $2.8 billion “Plant with a Future” (PWAF) program, a sweeping material and ideological overhaul that remade the firm for the post-Fordist global economy. This article advances three interventions. First, it shows how post-Fordism as a spatial and ideological project emphasized decentralization, accountability, and customer orientation, which helped legitimize and institutionalize corporate restructuring. Second, it demonstrates that flexibilization operated as a spatial strategy, implemented through four interrelated processes: bureaucratic restructuring, …

Student Perceptions Of The Learning Environment In A Hospital School Program, Hannah Buck

Brehm Scholars Research

Most research related to hospital school programs has focused on adult perspectives (e.g., teachers, administrators, parents, and clinical staff) rather than on the perspectives of hospitalized students. This study examined the education-related perspectives of hospitalized K–12 students (N = 10) who had engaged with the C.S. Mott Children’s Hospital School Program in Ann Arbor, Michigan. Participants completed one semi-structured interview and two short surveys. Sessions were audio-recorded, transcribed, in vivo coded, and thematically analyzed. Despite the challenges associated with hospitalization, participants generally reported equal or greater enjoyment of in-hospital schooling compared to non-hospital schooling. Survey responses revealed that higher …

Implementation Of The Four Pediatric Feeding Disorder Domains By The Elementary School-Based Speech-Language Pathologist: A Research Plan, Kelsi Szakovits

Brehm Scholars Research

No abstract provided.

Extradigital Glomus Tumor Mimicking Incisional Neuroma After Total Knee Arthroplasty: A Case Report, James W. Li, Michael J. Sayegh, Heng Hong, Zhongyu Li

This case report describes a patient who was presented with severe incisional pain following an uncomplicated total knee arthroplasty. There was suspicion for an incisional neuroma; however, excisional biopsy revealed an extradigital glomus tumor. The patient had immediate symptom resolution post-operatively. Clinicians should maintain a suspicion for the possibility of extra-digital glomus tumors at sites of prior extremity surgery, causing exquisite tenderness and pain.