Digital Commons Network^™

Feature Extraction From Railroad Bearing Onboard Vibration Sensors Using Machine Learning Models, Diego Cantu

Theses and Dissertations

The University Transportation Center for Railway Safety (UTCRS) has developed an algorithm capable of identifying defective railroad bearings, determining damaged component(s) within, and quantifying severity of the defects. The defect-detection algorithm requires the operating speed as an input, which is not readily available in field operation of onboard sensors. Therefore, onboard sensors deployed in rail revenue service must rely on Global Positioning Systems (GPS) to obtain speed, which can be power-intensive and susceptible to signal interference. This study covers the development of a vibration-based model that extracts operating speed from wireless sensor data to enable fully autonomous onboard diagnostics. Signal …

Life Cycle Assessment Of A Prefabricated Modular Timber Building, Bryan Mai

Construction Management

Traditional concrete construction carries a high carbon footprint, motivating interest in lower-impact alternatives such as prefabricated modular timber systems. This project conducts a process-based life cycle assessment (LCA) using OpenLCA to evaluate the environmental impacts of a modular timber building. Material quantities from major processes were modeled as flow inputs and converted into standardized OpenLCA units. Impact categories—including acidification potential, human toxicity, and energy/resource use—were analyzed to determine which materials and processes contribute most to overall environmental burden. Results show that transportation and plumbing materials drive the largest acidification impacts, while interior finishes dominate human toxicity. This LCA establishes a …

Concrete Masonry Unit Construction: Creating Educational Modules On Sustainability, Eric Dam

Construction Management

Concrete Masonry Units are one of the most widely used building materials due to their durability, fire resistance, low maintenance, and specifications. With the growing trend for sustainable construction, it is necessary to teach students how CMUs can contribute to improving environmental performance and dive deeper into multiple resource efficiency. This project developed an instructional module that introduces CMU materials, reviews performance and durability attributes of these materials, and how they are linked to well-known rating systems. The final module includes a presentation, three assignments, and one quiz that will reinforce student learning and refresh industry professionals' knowledge. The following …

Developing A Metabolic Engineering Chassis From A Metabolically Versatile Organism, Rhodopseudomonas Palustris Cga009, Mark William Kathol

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Metabolic engineering has made it possible to develop biological processes that were once considered economically unfeasible or uncompetitive. This field has enabled both a robust niche market, whereby products, such as pharmaceutical substances like monoclonal antibodies, are produced exclusively through biological means, as well as an emerging commodity production market. Nonetheless, significant challenges remain in harnessing the unique metabolic capabilities of genetically non-tractable organisms. This dissertation focuses on Rhodopseudomonas palustris CGA009 as a potential chassis for metabolic engineering. To address the issue of genetic intractability, a synthetic biology toolkit was developed to facilitate the expression of heterologous proteins in R …

Detecting Prescribed Fire, Haying And Grazing Events Via Remote Sensing To Create Grassland Disturbance Landcovers For The Ring-Necked Pheasant (Phasianus Colchicus), Megan Amy Baldissara

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation developed disturbance detection models to fulfill the need for remote sensing landcover products describing grassland structure. The use of landcover products derived from remote sensing is increasing over time in pheasant (Phasianus colchicus) research. Such landcover, however, does not provide relevant pheasant structural habitat information (Chapter 1). Pheasants require tall, high-density grassland for nesting, tall grassland with medium density for brood rearing, and tall grassland for wintering. Time since disturbance can serve as a proxy for structure, as it shapes vegetation by removing biomass and resetting succession. Disturbance is easier to detect than structure with current …

Exploring Transformative Learning Experiences In Engineering Doctoral And Post-Doctoral Education: Developing Non-Technical Competencies For Early-Career Academic Roles, Ibukunoluwa Eunice Salami

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation explores the transformative learning experiences that early-career engineering faculty recounted from their doctoral and postdoctoral training and how these experiences shaped the development of non-technical competencies essential for academic success. Grounded in Mezirow’s Transformative Learning Theory (TLT) and the Competency-Based Professional Development Framework (CBPDF), the study examines how reflection and shifts in frames of reference supported competency growth and faculty readiness. A qualitative holistic single-case study design was employed. Data sources included semi-structured interviews with early-career engineering faculty and program learning objectives drawn from graduate handbooks. Data analysis was both deductive and inductive guided by Mezirow’s ten phases …

In-Field Tractor Operational Load Profile Generation In Support Of Advanced Tractor Testing In Mixedmode Power, Andrew Donesky

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation addresses the need to better characterize real-world tractor power requirements across drawbar, power take-off (PTO), and hydraulic modes to support more representative tractor testing. Conventional testing protocols, such as OECD Code 2, emphasize steady-state performance under controlled high-load conditions, which do not reflect the mixed and dynamic demands of modern field operations. To address this gap, a Tractor Instrumentation System (TIS) was developed, validated, and deployed to collect high-resolution, mixed-mode power data during planting, anhydrous ammonia application, and grain cart operations. The TIS integrates physical sensors, including custom load pins, hydraulic pressure/flow sensors, and a redesigned PTO torque …

Investigating Programming Behaviors To Understand Student Engagement And Experience In Introductory Programming Courses, Marcus Eugene Gubanyi

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Introductory programming courses are foundational to developing students’ problem-solving abilities and shaping their persistence in computing pathways. Engagement with programming tasks plays a central role in student learning and experience. Many research measures, including self-reports and code submissions, offer only a limited view of student engagement with programming tasks. This dissertation leverages programming process data, consisting of keystrokes and compilation events, to capture the programming process as it unfolds and to investigate observable programming behaviors. Guided by educational theories, three studies examine how students’ programming behaviors vary across instructional and assessment contexts, how they relate to motivational profiles, and how …

Large-Scale Experimental Study On The Impact Of Air Cleaning & Ventilation On Indoor Air Quality And Student Illness-Related Absenteeism, Daud Nosham

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This large-scale randomized experimental field study investigated the effect of portable air purifiers (PAPs) on classroom’s air quality and student’s illness related absenteeism. PAPs were installed in 317 classrooms from various school districts located in Eastern Nebraska. The classrooms were randomly assigned into four conditions: three treatment conditions (T1, T2 & T3) and one control condition (device without any filter). T1 was equipped with HEPA filters, T2 added Activated Carbon (AC) layer to HEPA, and T3 further integrated Germicidal Ultraviolet (GUV) alongside HEPA and AC filters. The measured variables were carbon dioxide (CO2), fine particles (PN2.5) and coarse particles (PNcoarse), …

Real-Time, Co-Regulated Design For Cyber-Physical, Multi-Rotor Uas Swarms, Grant Simon Phillips

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Uncrewed Aerial Systems (UAS) have been integrated into a wide range of research and industrial applications, with growing interest in extending mission duration and spatial coverage through coordinated multi-UAS systems, or swarms. While swarming offers the potential for extended mission endurance and robustness through advanced path-planning, control, and estimation algorithms, significant challenges arise when implementing these methods on decentralized platforms composed of size, weight, and power-constrained (SWaP) vehicles. Limitations in onboard computational capacity and congested communication channels can break critical design-time assumptions, which at best, will degrade application quality of service, and at worst, destabilize the fleet through excessive delays …

Ai-Enabled Robotic Nitrogen Management, Ankita Kalra

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Nitrogen management in corn agriculture faces economic and environmental challenges, motivating development of precision, site-specific solutions. This dissertation presents AIR-N (AI-Enabled Robotic Nitrogen Management), a novel system that integrates cloud-based artificial intelligence with an autonomous field robot (Flex-Ro) to optimize nitrogen fertilizer application in real time. The research is driven by the need to improve nitrogen use efficiency while reducing leaching and emissions.

Comprehensive architecture (Cloud-E) was designed using Amazon Web Services to ingest multi-modal agronomic data (soil sensors, crop reflectance, weather) and host machine learning models. A Random Forest-based model was trained on historical field data to predict spatially …

An Integrated Modeling Framework To Evaluate Circularity Of The Corn–Water–Ethanol–Beef Nexus, Heydi Han

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation examines the transition from conventional linear agricultural and food bioenergy systems toward more circular, resilient, and resource-efficient configurations. Prior research indicates that spatial and temporal variability in soil, weather, animal biological responses, and management decisions strongly influences productivity, nutrient-use efficiency, and profitability. Studies have also shown that a diversified circular system can buffer these sources of variability, improving stability and adaptive capacity. Building on these insights, the central focus of this work is to develop an integrated modeling framework to evaluate circularity within the Corn-Water-Ethanol-Beef (CWEB) nexus and explore how climate variability and management choices shape system-wide performance. …

Making Deep Neural Networks Trustworthy: Intelligibility And Safety Through Symbolic Methods, Eleanor Catherine Quint

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The rapid adoption of deep learning has come at the cost of properties long valued in artificial intelligence: intelligibility and safety. This dissertation develops methods that restore these properties by coupling neural networks with symbolic structure.

First, for supervised classification, I propose a differentiable decision tree integrated with a supervised variational autoencoder. The resulting model maintains competitive accuracy and generative performance while exposing clear macro-features in its latent space, improving interpretability.

Second, for reinforcement learning, I extend constrained Markov decision processes by specifying constraints in formal languages. This formal language constrained MDP enables the use of automata for state augmentation, …

Favorability Mapping For Hydrothermal Power Resource Assessments Of The Great Basin, Usa, Stanley P. Mordensky, Erick R. Burns, John Lipor, Jacob Deangelo

Electrical and Computer Engineering Faculty Publications and Presentations

Highlights

• • The new approach to predict hydrothermal resource favorability for the U.S. Great Basin is a synthesis of modern data-driven machine learning improvements from the last several years and predicts 85 % of power-producing systems with operating power plants in the most favorable 10 % of the total area with over half of the power-producing systems (10 of the 19 exposed power-producing systems and 5 of the 9 hidden power-producing systems) in the 99th percentile.
• • The new hydrothermal favorability map predicts both hidden and exposed power-producing hydrothermal systems equally well.
• • The new hydrothermal favorability map preferentially predicts …

A Novel Microfluidic Approach To Quantify Pore-Scale Mineral Dissolution In Porous Media, Rafid Musabbir Rahman, Elliott Niemur, Gianluca Blois, Farzan Kazemifar, Myeongsub Kim, Yaofa Li

Faculty Research, Scholarly, and Creative Activity

Mineral dissolution in porous media coupled with single- and/or multi-phase flows is pervasive in natural and engineering systems. Dissolution modifies the physical, hydrological, and geochemical properties of the solid matrix, resulting in a complex coupling between local dissolution rate and pore-scale flow. The work reports a microfluidic approach that includes 2D reactive porous media and advanced pore flow diagnostics for the study of pore-scale dissolution in porous media with unprecedented details. The 2D microfluidic porous media, called micromodels, were fabricated in calcite by combining photolithography and wet etching, which not only offers precise control over the structural and chemical properties, …

Genetic And Environmental Determinants Of Streaming And Aggregation In Myxococcus Xanthus, Trosporsha T. Khan, Patrick Murphy, Jiangguo Zhang, Oleg A. Igoshin, Roy D. Welch

Faculty Research, Scholarly, and Creative Activity

Under starvation conditions, a spot of a few million Myxococcus xanthus cells on agar will migrate inward to form aggregates that mature into dome-shaped fruiting bodies. This migration is thought to occur within structures called ‘streams,’ which are considered crucial for initiating aggregation. The prevailing traffic jam model hypothesizes that intersections of streams cause cell crowding and ‘jamming,’ thereby initiating the process of aggregate formation. However, this hypothesis has not been rigorously tested, in part due to the lack of a standardized, quantifiable definition of streams. To address this gap, we captured time-lapse movies and conducted fluorescent cell tracking experiments …

Building Kit For K-8 Education: An Introduction To Construction Fundamentals, Marc Joynt

Construction Management

Introducing construction concepts to young students requires tools that are both engaging and easy to use, which led to the development of a laser-cut building kit designed for K–8 classrooms. The process began with hand-drawn sketches to establish a simple, age-appropriate structure. The design was then modeled in AutoCAD, where each individual component was drafted for fabrication. After completing the digital model, the files were transferred into Rhino and organized by layer to ensure accurate communication with the laser cutters used to produce the final basswood pieces. Throughout the project, challenges such as material limitations, tolerance adjustments, and simplifying complex …

Signaling Through National Security Lawmaking, Weijia Rao

Faculty Scholarship

An often-overlooked element of the ongoing TikTok saga is China’s export control law, which prohibits the sale of TikTok’s core content recommendation algorithm without prior approval from the Chinese government. This law is just one example of the extensive national security lawmaking China has undertaken in recent years. Closely paralleling similar institutions in the U.S., China has established a comprehensive national security legal framework that authorizes the government to restrict exports, sanction foreign entities, screen foreign investments, and block transactions involving cyber infrastructure.

Why turn towards legality when China has the ability to employ these actions without a formal legal …

Secondhand Social Capital And Idea Quality In Open Innovation Communities, Elisa Mattarelli, Aaron Schecter, Pamela Hinds, Noshir Contractor

Faculty Research, Scholarly, and Creative Activity

Open innovation communities provide valuable opportunities for creators from diverse backgrounds to collaboratively generate and refine new ideas that companies can implement in new products or services. However, many submitted ideas in these communities are underdeveloped or misaligned with companies' expectations, raising questions about what drives high-quality ideas and, more specifically, innovation potential. We focus on the role of secondhand social capital, i.e., the indirect network benefits an idea accrues through feedback from providers who are themselves actively engaged with other influential ideas in the community. While prior research has explored ego-centric or first-hand networks, we extend this work by …

Design And Soft-Switching Analysis Of Resonant Converters In Unfolding-Based Ac-Dc Topologies For Wide Operating Range Electric Vehicle Charging Applications, Shubhangi Gurudiwan

All Graduate Theses and Dissertations, Fall 2023 to Present

As the global community becomes increasingly aware of the need to reduce greenhouse gas emissions and reliance on fossil fuels, transitioning to electric mobility emerges as a critical step towards a more sustainable and energy-efficient future. One of the major barriers to the mass adoption of battery electric vehicles is the lack of convenient, fast, and accessible charging stations. Long charging times and limited charger availability contribute to range anxiety. To address this challenge, improvements in public charging infrastructure and the development of reliable, high-efficiency, high-power converters are required.

Typically, a grid-tied ac-dc converter with a two-stage architecture, consisting of …

Built For Participation: A Set Of Measures For Evaluating Community Living For People Of All Abilities As Supported By The Built Environment, Christopher A. Wilson Ii

All Graduate Theses and Dissertations, Fall 2023 to Present

As the world enters a new era of urban living, it is important to develop cities that allow residents of all ages and abilities to fully participate in society. Integration of people with disabilities into daily community living involves looking beyond site- or product-specific features to community- and city-wide systems. Some tools have been developed to begin evaluating cities’ levels of inclusive social participation and to provide recommendations for city planning professionals. However, the tools that have been developed often are too complex for practical use or rely on data that varies in obtainability. Therefore, the purpose of this series …

Reconstruction And Texturing Of 3d Surfaces From Fused Low-Cost Aerial Lidar And Optical Imagery, Samuel Kiguthi

All Graduate Theses and Dissertations, Fall 2023 to Present

Drones equipped with laser scanners (LiDAR) and cameras capture detailed 3D scenes. Combining the laser points with photos builds realistic, photo-textured 3D maps used in surveying, agriculture, and infrastructure planning. Conventional methods to create these maps often misrepresent inward shapes such as doorways, overhangs, and outcrops. These shapes are misrepresented because drones mainly view top surfaces and do not collect significant data on vertical or hidden areas.

This study introduces a surface-reconstruction method that groups LiDAR points into clusters, reconstructs smooth surfaces for each cluster, and uses information from recorded camera poses to stitch clusters together. Tests on real drone …

Data-Driven Streamflow Forecasting In The Upper Colorado River Basin Using Spatio-Temporal Graph Networks, Akhila Akkala

All Graduate Theses and Dissertations, Fall 2023 to Present

Forecasting river flow is essential for managing water supplies, reducing flood risk, and supporting healthy ecosystems. In the Upper Colorado River Basin, much of the yearly water comes from melting snow. However, many traditional models struggle to capture how snowpack and river flow interact, especially across such a large and complex region.

This study uses a modern machine learning approach called a Spatio-Temporal Graph Neural Network (STGNN) to improve streamflow prediction. The model uses Snow Water Equivalent (SWE)—a measure of how much water is stored in the snowpack—along with river flow data. By treating each river gauge as part of …

Optimization In The Synthesis Of Dual Ionic-Liquid-Functionalized Cellulosic Materials, Megan L. Franke

Honors College Theses

There is a growing urgency to develop sustainable alternatives to petroleum-based materials as concerns about environmental impact and resource depletion intensify. Among renewable biopolymers, cellulose stands out as one of the most abundant and versatile organic compounds on Earth. As the structural backbone of plant cell walls, it provides rigidity and mechanical strength, while its abundance, biodegradability, and tunable chemistry make it an attractive candidate for sustainable materials. Beyond its traditional uses in textiles, paper, and food additives, cellulose has been increasingly investigated in polymer chemistry for advanced

applications. The present study aims to optimize synthetic routes to dual ionic …

From Mechanisms To Management: Implications Of Biogeochemical Controllers And Land Management For Soil Carbon Cycling And Storage, Savannah R. Adkins

All Graduate Theses and Dissertations, Fall 2023 to Present

Climate change and its cascading effects are driven by increases in atmospheric carbon dioxide (CO₂). Many climate solutions exists to remove this excess carbon (C) from the atmosphere, and soils, in particular, represent one of the few win-win solutions. Soils play a vital role in the global C cycle because they store more C than plants and the atmosphere combined, however, they also release more CO₂ annually than fossil fuel combustion (a major contributor to accelerating climate change). Therefore, preventing CO₂ loss from soil could help slow the progression of climate change, and increasing overall soil …

Cognitive Dynamics In Undergraduate Engineering Education: Effects Of Need For Cognitive Closure And Achievement Goal Orientation On Cognitive Engagement, Zain Ul Abideen

All Graduate Theses and Dissertations, Fall 2023 to Present

Cognitive and motivational factors play an important role in students’ engagement during problem-solving, which can lead to academic and professional success. Among these factors, Need for cognitive closure (NFCC) and achievement goal orientation (AGO) have been studied extensively individually, but their interaction and impact on engineering students’ problem-solving is still not explored. NFCC refers to the person’s desire for quick answers, and AGO is the student’s approach to learning and success. This research investigated the impact of NFCC on gender and engineering major, and the relation between NFCC (five facets) and AGO (Mastery, Performance) at their different levels. Additionally, this …

Predicting Major Solar Flares Using Convolutional Neural Networks And Multivariate Magnetic Field Time-Series Data, Arash Azizian Foumani

All Graduate Theses and Dissertations, Fall 2023 to Present

Major solar flares are sudden, intense bursts of X-ray energy from the Sun, capable of severely impacting critical technological infrastructure like satellites, communication networks, and power grids on Earth. Accurate prediction of these high-intensity events is crucial but presents a significant challenge. This is largely due to their infrequent occurrence and the complex, dynamic nature of the Sun's underlying magnetic activity which drives these events. This research focuses on improving the prediction of major solar flares by utilizing detailed historical data that tracks the evolution of magnetic properties within solar active regions over time. This time-based data, however, contains inherent …

Array Of Mini-Graphene-Silicon Solar Cells Intermittently Recharges Storage Capacitors Powering A Temperature Sensor, Ashaduzzaman, Syed M. Rahman, Md R. Kabir, James M. Mangum, Hung Do, Gordon Carichner, David Blaauw, Paul M. Thibado

Physics Faculty Publications and Presentations

Developing autonomous sensor systems that draw power from the ambient environment is a critical step for creating the Internet of Things. In this study, the authors built dozens of graphene-based solar cells, wire bonded them into standard packages, and characterized the current-voltage characteristics of each under illumination. Next, solar cells were connected in series to increase the output voltage. Three different sets of solar cells were used to charge three storage capacitors to the voltage levels required by our temperature sensor. The storage capacitors require only a few minutes to charge, yet power the sensor system for more than 24 …

Soil Organic Carbon Depth Profiles And Centennial And Millennial Decay Rates In Tidal Marsh, Mangrove And Seagrass Blue Carbon Ecosystems, Nerea Piñeiro-Juncal, Miguel Ángel Mateo, Carmen Leiva-Dueñas, Eduard Serrano, Karina Inostroza, Montserrat Soler, Eugenia T. Apostolaki, Paul Lavery, Carlos M. Duarte, Anna Lafratta, Oscar Serrano

Research outputs 2022 to 2026

The management of coastal blue carbon ecosystems can contribute to mitigate anthropogenic greenhouse gas emissions. However, limited information on soil organic carbon (OC) decay rates in tidal marsh, mangrove, and seagrass soils hinders their inclusion in climate strategies and carbon-crediting schemes. Here, we analyzed downcore OC trends in 3761 soil cores from blue carbon ecosystems worldwide. A decrease in OC content with soil depth was measured in 63% of the cores, whereas stable and increasing trends were observed in 22% and 15% of the cores, respectively. Based on 85 profiles where OC decay could be modelled, the OC decay rate …

Design Of A Novel Robust Adaptive Fractional-Order Model Predictive Controller For Boost Converter Using Grey Wolf Optimization Algorithm, Chao Peng, Seyyed Morteza [email protected] Ghamari, Hasan Mollaee, Omid Rezaei

Research outputs 2022 to 2026

Boost converters play a crucial role in power electronics but present control challenges due to their non-minimum phase behavior and nonlinear dynamics at high switching frequencies. To address these issues, this work proposes a Fractional-order adaptive Model Predictive Control (FO-MPC) framework incorporating Exponential Regressive Least Squares (ERLS) for system identification. Traditional MPC frameworks often rely on accurate mathematical models, which are difficult to obtain in real-world scenarios. This adaptive modelling approach based on ERLS identification method eliminates the need for precise system models, improving robustness and adaptability under parameter variations. Additionally, a FO derivative term enhances damping, stability, and noise …