Digital Commons Network^™

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 …

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 …

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 …

Sadqn-Based Residual Energy-Aware Beamforming For Lora-Enabled Rf Energy Harvesting For Disaster-Tolerant Underground Mining Networks, Hilary Kelechi Anabi, Samuel Frimpong, Sanjay Madria

Mining Engineering Faculty Research & Creative Works

The end-to-end efficiency of radio-frequency (RF)-powered wireless communication networks (WPCNs) in post-disaster underground mine environments can be enhanced through adaptive beamforming. The primary challenges in such scenarios include (i) identifying the most energy-constrained nodes, i.e., nodes with the lowest residual energy to prevent the loss of tracking and localization functionality; (ii) avoiding reliance on the computationally intensive channel state information (CSI) acquisition process; and (iii) ensuring long-range RF wireless power transfer (LoRa-RFWPT). To address these issues, this paper introduces an adaptive and safety-aware deep reinforcement learning (DRL) framework for energy beamforming in LoRa-enabled underground disaster networks. Specifically, we develop a …

Utilizing Digital Twins To Model And Optimize Hydraulic Excavator Operator Performance Through Arena Simulation, Mateo Fernando Montenegro Defaz, Kwame Awuah-Offei

Mining Engineering Faculty Research & Creative Works

This study aims to provide a digital twin tool for mining and construction companies to evaluate the effect of operator behaviors on the truck-loading process, focusing on swing and bucket rotation. While equipment performance estimators are available, there are few tools to assess the influence of operators. The aim is to create a discrete event simulation (DES) model in Arena® to evaluate how variations in swing and bucket angles affect hydraulic excavator production rates. We validated the DES model using real-world data from a case study to assess the differences in behavior among four operators. Results showed that Operator 1 …

Stall Detection In Hydraulic Excavator Operations Using Heuristics And Machine Learning: A Case Study, Mateo Fernando Montenegro Defaz, Kwame Awuah-Offei, Yixiang Gao

Mining Engineering Faculty Research & Creative Works

This work aims to develop a reliable algorithm for stall detection during excavator digging by analyzing key operational variables such as velocity and angular displacements from machine monitoring data. The work develops and validates a heuristic algorithm to detect stalling events and trains a support vector machine classification algorithm to distinguish between "normal" digging cycles and cycles with stalling. This work is a novel attempt at using a classification algorithm to categorize digging cycles into normal and those with stalling events based on machine monitoring data alone. The developed classification algorithm achieved a sensitivity of 100%, indicating it correctly identified …

A Literature Review And Conceptual Framework For Sustainability In Open-Pit Mine Planning, Raymond Kudzawu-D'Pherdd, Kwame Awuah-Offei, Esteban Koberg De La Cruz, Marcos Goycoolea, Andrea Brickey, Alexandra M. Newman

Mining Engineering Faculty Research & Creative Works

This paper presents a comprehensive literature review and a conceptual framework for integrating environmental sustainability into strategic mine planning, focusing on open pits. Despite growing interest, easily discernible sustainability metrics remain elusive in early mine-planning stages, and are included as a post-processing step, if at all, rather than integrated a priori into a mine plan via, e.g., optimization. Through a literature review, we identify efforts regarding how environmental dimensions, such as emissions, water use, and land rehabilitation, are addressed across mine planning phases. We propose the Environmental Stewardship and Sustainability Framework for Mine Planning, which: (i) embeds sustainability into decision …

Analysis Of Pull-Out Tests For Resin-Grouted Rib Bolts, Khaled Mohamed, Yuting Xue, Dogukan Guner, Alper Kirmaci, Taghi Sherizadeh

Mining Engineering Faculty Research & Creative Works

Resin-grouted rib bolts serve as a crucial means of stabilizing spalling of coal ribs in underground coal mines. A comprehensive investigation into their efficacy was undertaken by a collaborative effort between the National Institute for Occupational Safety and Health (NIOSH) and Missouri University of Science and Technology (MST). This study involved pull-out tests of rib bolts in multiple locations, including six coal mines and the NIOSH research mine. A total of seventy-three (73) pull-out tests were conducted for rib bolts installed at different rotation speeds and a wide range of anchorage lengths, ranging from a short encapsulation length of 0.305 …

Sustmine: A Framework For Integrating Sustainable Development Dimensions Into Strategic Mine Planning, Hussam Altalhi, Kwame Awuah-Offei, Gabriel Nicolosi, Abdullah Al Moinee, Nasib Al Habib

Mining Engineering Faculty Research & Creative Works

Strategic mine planning involves optimizing resource extraction to achieve economic, environmental, and social objectives. However, only a few frameworks offer a unified approach that simultaneously employs systematic indicator selection and weightless trade-off evaluation. This study addresses these issues by proposing a comprehensive framework for integrating sustainability into strategic mine planning, named SustMine. SustMine introduces two key advancements: (1) a rigorous, systematic, criteria-based process for selecting site-specific sustainable development indicators (SDIs), and (2) a weightless evaluation strategy that utilizes Pareto front analysis to construct composite indices. This allows decision-makers to identify non-dominated (optimally balanced) alternatives without relying on arbitrary or subjective …

4-H Day Of Service Team Guidebook, Kristen Lyons

UNH Cooperative Extension

No abstract provided.

Estuary, Kelle Loughlin

UNH Cooperative Extension

No abstract provided.

Nh State Shoreland Water Quality Protection Act (Landscaping For Water Quality Workshop - 2026), Jay Aube

UNH Cooperative Extension

No abstract provided.

Paper Or Screen: How Do Digital And Traditional Methods Shape Motivation And Reading Outcomes?, Rachel E. H. Bentley

All Electronic Theses and Dissertations

Technological advancements occur with such a high frequency that educators and administrators endeavor to offer as many knowledgeable tools as they can deliver. This sentiment, however, leaves teachers and their pupils asking if this is the right avenue to follow. This literature review investigates the question of whether digital devices and applications are beneficial to student success or cause negative effects on students' learning progress. This review specifically focuses on research that examines K-12 and undergraduate students’ reading comprehension and other ELA fundamentals, as well as students' engagement and motivation, by studying the mode of learning through which instruction was …

Integrative Approaches And Data Analysis For Single-Cell Rna Sequencing Data, Teng Long

Computer Science and Engineering Dissertations

The rapid growth of single-cell RNA sequencing and transcriptomic datasets has created major computational challenges in causal discovery, representation learning, and biologically faithful data generation. To address these challenges, this dissertation presents three complementary deep learning frameworks for the analysis and modeling of transcriptomic data. Together, these methods form an integrative computational toolkit for understanding complex biological systems from high-dimensional and heterogeneous gene expression data.

First, this dissertation introduces DAG-VAERL, a causal discovery framework that integrates variational autoencoders, graph neural networks, reinforcement learning, and attention mechanisms to infer directed acyclic graphs for gene regulatory network analysis. DAG-VAERL improves causal structure …

Data-Driven Climate Damage Functions For Capital Formation: Estimating The Climate Penalty Using Maching Learning, Pramudya Wicaksono

All Graduate Theses, Dissertations, and Other Capstone Projects

Traditional integrated assessment models assume parametric climate damage functions that may miss nonlinearities, heterogeneity, and dynamic effects on investment. This thesis develops a data-driven climate damage function for capital formation by estimating the predictive relationship between climate conditions and future gross fixed capital formation (% GDP) across 125 countries over 1982–2019. We construct a panel dataset by combining daily ERA5 climate reanalysis data (accessed via the Copernicus Climate Data Store API and aggregated to yearly country-level variables including temperature anomalies, extreme heat days, frost days, precipitation, and solar radiation) with economic indicators from the World Bank World Development Indicators and …

What Does The Quality Of Life For Congenital Heart Defect Patients Look Like Across The Lifespan?, Kaylee F. Maynor

Undergraduate Honors Theses

Throughout history, birth defects have left a mark on patients and families across the world. From an infant's first few breaths to an elderly person's last breath, congenital heart birth defects play a major role in that person's life. There are many different types of birth defects that effect the heart. Each defect is unique and has different outcomes on the body. Some congenital heart diseases have multiple defects causing more than one complication. The treatment options for many of the common congenital heart birth defects have come a long way throughout decades of research. By diving into what heart …

Judging What Jurors Know: Expert Testimony After Voir Dire, Chris Cox

Scholarly Works

No abstract provided.

Mitochondria As Primary Cause Of Neurodegeneration: Evaluating Causality Across Amyotrophic Lateral Sclerosis (Als), Alzheimer's, And Parkinson’S Diseases, Makenzie G. Johnson

Undergraduate Honors Theses

Neurodegenerative diseases like Alzheimer's Disease (AD), Parkinson’s Disease (PD) and Amyotrophic Lateral Sclerosis (ALS) have historically been explained through alternate hypotheses despite shared clinical hallmarks that lead to neuron loss. However, these varying explanations could not account for how disease onset begins among other individual issues. This thesis aims to show that mitochondrial dysfunction is a primary driver of neurodegeneration as well as a unifying mechanism shared between the three diseases. Evidence presented in this thesis will show that many issues can arise in mitochondria including issues with energy production, mitochondrial DNA (mtDNA), apoptosis activation, and calcium regulation. These issues …

Dental Implantology: A Literature Review, Kylie Taylor

Undergraduate Honors Theses

Dental implant therapy is the process of replacing teeth as a form of treatment to improve quality of life, function, and esthetics. The success of the implant depends on the surgical technique, type of prosthetic, and factors related to individual patients. The most important factor for implant success is osseointegration. Osseointegration is a process in which success is determined by the bone quality, the surface characteristics of the implant and the surgical approach. Some approaches to improve the osseointegration of the implant are low-speed drilling, guided surgery, and reduced surgical trauma at the site. The impact of systemic conditions, health …

Pull-Out Performance Of Multiple Glued-In Rods In Sustainable Inorganic-Bonded Bamboo Composite Under Perpendicular-To-Grain Loading, Jing Ru Yao, Shaohua Yu, Qingxia Yue, Hanshu Zhang, Ernian Zhao

Physics and Engineering Science

As a sustainable bio-based material derived from bamboo crops, inorganic-bonded bamboo composite (InorgBam) exhibits excellent environmental sustainability, fire resistance, and long-term durability. To enable its broader adoption in structural applications, robust and efficient connection methods are essential. Glued-in rod (GiR) connections, characterized by high strength, stiffness, and superior fire performance, are especially well-suited for modern engineered bamboo and timber connections. The pull-out behavior of multiple GiRs in InorgBam material under perpendicular-to-grain loading was experimentally investigated using double-, triple-, and quadruple-rod specimens. The influence of anchorage length and spacing on failure modes and load-carrying capacity was systematically analyzed. Results demonstrate that …

A Novel Simulation Framework To Estimate Dynamic Response Of A Solar Panel Array Under Stationary Stochastic Wind Loads, Hanshu Zhang, You Jia Li, Matthew J. Dejong

Physics and Engineering Science

This paper presents a novel simulation framework for estimating the dynamic response of a full-scale ground-mounted solar panel array under stationary wind loads that are spatially correlated across the length of the solar panel array. Specifically, the framework uses mean pressure coefficient distributions along the length of a 1:10 prototype scale of the solar panel array from smooth inflow derived using the computational fluid dynamics (CFD) simulation software The Wind Engineering with Uncertainty Quantification (WE-UQ). Note that for the CFD simulation, the input wind field across the length of the solar panel array is uniform along the horizontal direction, and …

Annual Report For The Town Of Bridgewater, New Hampshire For The Fiscal Year Ending December 31, 2025, Bridgewater Town Representatives

Bridgewater, NH Annual Reports

This is an annual report containing vital statistics for a town/city in the state of New Hampshire.

Criminal Data Function Creep, Sarah E. Lageson

Journal of Criminal Law and Criminology

Automated, data-driven decision-making can create unfair outcomes and lead to discrimination. This Article considers a relatively ubiquitous part of modern life that is increasingly automated: the criminal background check. This Article, with contributions at the intersection of law and technology, antidiscrimination and consumer protection law, and sociological theory, makes the central claim that criminal record data is characterized by function creep—the unintended use of data for another purpose—which leads to a specific set of harms. This Article makes three central contributions. First, it offers an empirical assessment of contemporary, data-driven background screening using data based on in-depth interviews and systematic …

Rebutting The Presumption: A Constitutional Theory Of Pre-Trial Asset Seizures And Procedural Due Process, Benjamin Y. Rabin

Journal of Criminal Law and Criminology

In this Comment, I trace the origins and examine the current state of the doctrine on pre-trial asset seizures, then argue for a new approach grounded in procedural due process and constitutional theory.

The existing frameworks for assessing due process in these cases fall into three categories. The first grants the government broad presumptive validity for pre-trial seizures. The second applies a utilitarian balancing test, following the Supreme Court’s reasoning in Mathews v. Eldridge and Connecticut v. Doehr. The third, illustrated by the recent decision in Culley v. Marshall, relies on comparisons to historical practice.

I argue that …

Synthetic Contact Zones: Meeting Nature And Animals In Video Games, Sarah C. Mcpherson

English Theses

Due to economic and environmental barriers, encounters with animals and nature have become increasingly inaccessible for many people, while video games have emerged as a common site for simulated environmental interaction. This thesis conceptualizes video games as synthetic contact zones, or digital spaces where representations of humans, animals, and environments interact, conflict, and shape one another. Drawing on the theories of Mary Louise Pratt, Donna Haraway, and Alenda Y. Chang, this project analyzes how video games model relationships between players, animals, and ecological systems through interactive mechanics and environmental storytelling. Explorations of Red Dead Redemption 2, Blair Witch, …

Enhancing The User Experience Of Colorado Bend State Park Through The Implementation Of Cultural Landscape Analysis, Hunter C. Lynch

Landscape Architecture Masters & Design Theses

This design thesis investigates how landscape character and sense of place can be more clearly expressed through a cultural landscape approach to design at Colorado Bend State Park, a state park in Texas, with a focus on guiding future trail and campsite development in the currently undeveloped eastern portion of the park.The park’s dramatic canyons, limestone bluffs, spring-fed systems, and upland prairies form a series of distinct, yet interconnected landscape conditions shaped by the interaction of physical structure, ecological systems, and cultural associations. While these characteristics define the site's identity and are reflected in portions of the existing park, they …

Voice And Student Engagement With Writing: Integrating Perspective, Personality, And Style, Sara S. Martin

English Dissertations

The rise of generative AI has many teachers worried about the future of writing classes and students’ desire to learn. However, instructors can motivate students to write by valuing what AI can never replace: their voices. Previous definitions of voice took the concept for granted and left it either vague or reductive, unhelpful for structured lessons. I propose a new, more teachable definition of voice as perspective, personality, and style. Perspective takes priority because it belongs solely to the individual and the unrepeatable moment of composition. Personality infuses passages with emotion, forming a bond between author and reader. Style, the …

Enhancing The Performance Of Disk-Based Key-Value Stores: From Learned Index Acceleration To I/O-Efficient Hybrid Caching, Sujit Maharjan

Computer Science and Engineering Dissertations - Archive

The exponential growth of data in modern computing environments has rendered the efficient extraction of information from massive datasets a critical systemic requirement. Key-value (KV) storage systems serve as the backbone for these operations; however, their performance is consistently bottlenecked by two primary functional requirements: identifying the data's location and managing the physical cost of accessing the storage device. Data locations are typically identified via an index, while disk I/O is minimized through caching. This dissertation presents LearnedStore, TurboIndex, and ReadBooster, which break these performance bottlenecks by introducing architectural modifications to the index and cache. LearnedStore accelerates operations by adapting …

Adaptive Synchronization In Digital Twin–Enabled Iot Systems: A Unified Framework For Energy, Fidelity, And Latency Trade-Offs, Uzma Zehra

Computer Science and Engineering Theses

Digital twin technology has emerged as a foundational paradigm for enabling real-time monitoring, analysis, and control in Internet of Things (IoT) systems by maintaining virtual representations of physical processes. Its effectiveness, however, critically depends on timely and accurate synchronization between distributed sensing devices and their corresponding digital counterparts. Frequent synchronization improves reconstruction fidelity and system responsiveness but incurs significant communication energy consumption and network latency. In contrast, infrequent synchronization conserves communication resources but can lead to stale or inaccurate digital twin states, particularly in environments with rapidly changing dynamics. These opposing effects give rise to a fundamental trade-off among energy …