Engineering Commons^™

Shape Memory Behavior In Medium To High Entropy Shape Memory Alloys: Design, Prediction, And Experimental Analysis, Hatim Raji

Theses and Dissertations

This dissertation provides a data-driven system integrating synthetic data generation and machine learning (ML) techniques to create multicomponent SMA compositions with specific transformation temperatures (TTs). Models were trained to represent the nonlinear dependencies influencing martensitic transformation behavior by using elemental, thermodynamic, and process-related aspects. The capacity of the ML models on medium entropy NiTiHfPd and high entropy NiTiHfZrCu systems accuracy was confirmed by experimental validation showing TTs closely matched with model outputs.

Designing A User-Centered Bias System To Enhance Media Literacy And Factual Accuracy, Anjali Majan

Theses and Dissertations

In an era of rapid news consumption, readers often struggle to detect bias and misinformation. This study examined whether interface design can support more critical engagement with news. We developed a progressive disclosure interface that encouraged users to reflect as they read by gradually revealing bias and factual cues. Participants were assigned to either Progressive Disclosure or Ground News. The experiment involved two phases. In the intervention phase, participants used an interface with support features. In the assessment phase, they completed tasks without the tool. We evaluated their performance using five measures: bias recognition accuracy, bias shift, factuality judgment, overlap …

Autoregressive Temporal Modeling For Advanced Tracking-By-Diffusion, Pha Nguyen, Rishi Madhok, Bhiksha Raj, Khoa Luu

Electrical Engineering and Computer Science Faculty Publications and Presentations

Object tracking is a widely studied computer vision task with video and instance analysis applications. While paradigms such as tracking-by-regression,-detection,-attention have advanced the field, generative modeling offers new potential. Although some studies explore the generative process in instance-based understanding tasks, they rely on prediction refinement in the coordinate space rather than the visual domain. Instead, this paper presents Tracking-by-Diffusion, a novel paradigm for object tracking in video, leveraging visual generative models via the perspective of autoregressive models. This paradigm demonstrates broad applicability across point, box, and mask modalities while uniquely enabling textual guidance. We present DIFTracker, a framework that utilizes …

A Study On The Propagation And Exploitation Of Structured Light In Underwater Turbulence, Jaxon P. Wiley

All Dissertations

The development and optimization of optical systems will play a pivotal role in the continued exploration and exploitation of the world’s underwater environments. These systems offer advantages in many sectors, and includes applications in areas such as high-speed communication, advanced sensing and imaging, and environmental characterization and monitoring. Underwater environments offer a plethora of challenges, however, and mitigating these obstacles remains an arduous task. In this work, the inherent advantages of structured light are leveraged to optimize optical system performance through non-ideal underwater conditions. Additionally, fundamental relationships between the generation of specified structured modes and their interactions with complex environments …

Multiple View Neural Regression Of A Facial Shape Model, Xiang Li

All Dissertations

Creating re-topologized 3D facial meshes is a critical step in high-quality facial animation pipelines, yet it remains a labor-intensive and time-consuming task. Traditional approaches typically rely on multiview stereo reconstruction and specialized photometric environments to acquire accurate geometric and reflectance data under controlled conditions. This dissertation presents work toward more efficient capture of production-ready meshes including (1) developmental aspects of VarIS, a custom-designed light sphere capable of capturing high-resolution stereo geometry and reflectance maps—including diffuse, specular, and normal components under programmable illumination; (2) a study of the effects of camera parameters on automatic 2D and 3D landmarking methods, (3) methods …

Advancing Life Cycle Assessment For Environmental Sustainability Of Carbon Fiber-Reinforced Polymer Composites (Cfrps)), Hao Chen

All Dissertations

Carbon fiber-reinforced polymer composites (CFRPs) have emerged as promising materials, particularly for lightweight applications, with the potential to reduce environmental impacts across multiple sectors, including automotive, aerospace, and renewable energy. However, fully realizing their sustainability potential requires a more comprehensive and context-specific understanding of their environmental performance throughout the entire life cycle—from raw material production to end-of-life management.

This dissertation advances life cycle assessment (LCA) practices for CFRPs by addressing key challenges across multiple phases of the CFRP life cycle. First, I conducted a critical review and meta-analysis of carbon fiber manufacturing, revealing substantial variability in reported data on energy …

Effects Of Lossy Compression Data On Machine Learning Models, Max H. Faykus Iii

All Dissertations

Machine learning is a fundamental tool that is incorporated in every field across academia and other industries. Due to the large amount of data needed for training machine learning models, lossy compression plays a crucial role in storing data. Machine learning involves the use of algorithms and models to learn patterns in data. This allows the AI to make decisions without specific programming. On the other hand, compression utilizes encoding and decoding techniques to reduce the size of files. Compression is either lossy or lossless, lossy causes a loss of data while lossless preserves the data. This dissertation will explore …

Studies On The Effects Of Operator Fatigue On Performance, Trust, And Workload Demand In Human-In-The-Loop Ai-Enabled Drone Systems, Snowil Lopes

All Dissertations

Civil infrastructure must be regularly inspected to ensure its safety and reliability. Traditionally, risk engineers performed these inspections manually and in person. However, with the introduction of drones equipped with artificial intelligence (AI), inspections of civil infrastructure can now be conducted remotely. These AI-enabled drones capture and analyze images, helping engineers monitor large and complex structures from a distance. However, working with integrated systems consisting of multiple drones, especially those with varying levels of reliability, can be challenging. Operators must divide their attention, determine how much to trust each drone, and manage mental workload, which can affect their performance. Another …

Enhancing Credit Path Planning With Llm-Based Multi-Agent Systems, Sahar Yarmohammadtoosky

Dissertations

This work explores applying Multi-Agent (MA) Large Language Models (LLMs) to enhance credit card management, an underexplored area for their multi-step reasoning capabilities. Focusing on Equifax’s Optimal Path™ model [1]—a personalized solution for credit score optimization—the study addresses two key challenges: first, designing a natural language interface for financial credit models to improve accessibility and aid customer decision-making, and second, enhancing the reliability and real-world applicability of complex financial models prone to generating invalid or unfeasible recommendations caused by a lack of practical interpretability and susceptibility to edge cases. To tackle these, we propose and evaluate various MA designs, including …

Sensitivity Analysis Of Flexible Pavement For South Carolina Conditions, Shilpa Girish

All Dissertations

The objective of the study was to evaluate the sensitivity of various input variables on the flexible pavement design thickness of high-speed, high-traffic routes in South Carolina using the Mechanistic-Empirical Pavement Design Guide (MEPDG) by means of the AASHTOWare Pavement ME Design software using global calibration coefficients with a focus on bottom-up fatigue cracking. The variables considered in this investigation included two-way average annual daily truck traffic (AADTT), asphalt mix type, climate station, subgrade type and resilient modulus, and aggregate base thickness. The study includes comparative analysis using older methods like the AASHTO 1993 method and the South Carolina DOT …

Drift Dynamics Of Early Life-Stage Invasive Carps, Saurav Karki

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Asian carp species pose significant ecological threats to North American freshwater systems due to their invasive nature and prolific reproduction. Their semi buoyant eggs develop while drifting downstream with the river current. Understanding early life-stage transport is therefore critical for predicting recruitment potential and guiding management efforts. Existing fluvial egg drift models, including those relying on 1-D hydraulics and fully 3-D CFD-based models, are either inadequate for complex braided rivers or too computationally demanding for large-scale application. The Platte River in Nebraska, characterized by wide, shallow, multi-threaded channels, is dominated by two-dimensional flow conditions, making a depth-averaged 2-D modeling approach …

Impact Of Humidity From Shrink (Wrap) Tunnels On Refrigeration Systems: Comparing Economic And Environmental Impact Of Natural Gas And Electric, Segun Samuel Oladipo

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

This thesis examines the economic and environmental effects of electric and steam shrink-wrapping tunnels used in beef packaging processes, paying particular attention to the indirect refrigeration loads caused by the heat and humidity that each system releases. Traditional sustainability evaluations frequently ignore these indirect impacts, which are especially important in meat processing facilities where 45–55% of electricity use is attributed to refrigeration. Life cycle assessment (LCA), field measurements, and thermodynamic modeling are all used in this work to offer a thorough analysis of both tunnel types.

The case study facility in Nebraska operates both steam and electric shrink tunnels to …

The Significance Of Snow In Hydrometeorological Extremes, Sinan Rasiya Koya

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

Snow is the largest natural reservoir on Earth. It accumulates water during the cold and dry months and releases it during warm and dry months. Societies, especially in the extratropical zone, heavily depend on snow as their freshwater resources, resulting in the massive economic value of snow. The recent changes in snowpacks and associated processes are concerning. We are susceptible to disruptions in snow processes, which can have disastrous implications. Yet the importance of snow is often not realized by a wider population. There are limited studies quantifying snow-related extremes, partly stemming from the limitations of existing methodologies.

This dissertation …

Development And Evaluation Of Supported Ionic Liquid Membrane And Porphyrin Frameworks For Carbon Capture Separation, Sarang Ismail

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

The global urgency to mitigate anthropogenic CO₂ emissions has intensified the pursuit of energy-efficient separation technologies. Supported Ionic Liquid Membranes (SILMs) have emerged as promising candidates for CO₂ capture due to their tunable solubility-selectivity and low energy requirements. However, challenges such as mechanical instability, limited scalability, and trade-offs in transport performance have impeded their widespread adoption.

This thesis explores a systematic approach to designing and optimizing SILMs for enhanced CO₂ separation by tailoring polymer–ionic liquid interactions, processing conditions, and material architectures. A comprehensive set of studies were conducted using poly(vinylidene fluoride) (PVDF) with varying molecular weights, different grades of PEBAX®, …

Robust Online Inertia Estimation In Power Systems Using Ambient Data In The Presence Of Inverter-Based Resources, Narges Ghiasi

All Dissertations

The increasing penetration of Inverter-Based Resources (IBRs) in power systems has significantly altered system dynamics, reducing the system's effective rotational inertia and challenging frequency stability. Accurate online inertia estimation is essential for maintaining system reliability under these evolving conditions. This paper introduces a robust methodology for online inertia estimation using ambient data collected during normal system operation. The proposed method employs a state-space model to represent system dynamics and introduces synthetic step changes to simulate disturbances. By analyzing the frequency response and applying advanced signal processing techniques, the methodology estimates system inertia without requiring real large-scale disturbances. The approach is …

Replacement Optimization For Offshore Wind Turbine Farms, Morteza Soltani

All Dissertations

This dissertation is concerned with devising optimal replacement policies for offshore wind turbines with a focus on minimizing the costs associated with major component replacements and production losses due to downtime. Like their onshore counterparts, offshore wind turbines are subject to progressive degradation due to normal operations, as well as the influence of dynamic environmental conditions that influence their rate of degradation. Due to their proximity, wind farm turbines share common environmental conditions, as well as specialized maintenance resources. Their common exposure to the environment and need to share resources introduce both stochastic and economic dependence between the wind turbines. …

Advancing Smart And Adaptive Living Spaces Through Design And Development Of Reconfigurable Multifunctional Robot Rooms, Nithesh Kumar

All Dissertations

This work explores and introduces prototype hardware for a new category of robots: ‘Robot Rooms’, in an effort to refine the concept of traditional smart spaces and human-robot interaction. Unlike traditional robots that tend to be compact and exist within a space, this new category of robots is designed to be expansive: they do not exist within a space but rather shape space around them. We present several design concepts for potential robotic elements of a Robot Room. We then develop and demonstrate, at full scale, a new and novel concept: a ‘slice’ of a Robot Room. This slice changes …

Resilient Control Framework For Ev Motor Drive System Subject To Cyber-Physical Security, Ali Arsalan

All Dissertations

The electric drive system (EDS) in electric vehicles (EVs) is one of the key safety-critical components. As IoT-enabled communication infrastructure for modern cyber-physical automotive systems continues to evolve, the importance of securing EDS against cyber threats along with physical faults, has become increasingly prominent. Among physical faults, power switches are particularly vulnerable and exhibit the highest susceptibility to open-circuit faults (OCFs). A compromised EDS, whether due to cyber threats or physical issues, can lead to excessive mechanical vibrations, increased thermal stress, fluctuations in electromagnetic torque, and elevated total harmonic distortion. These factors can substantially undermine traction control stability and jeopardize …

Designing Self-Healable Aromatic Copolymers And Olefinic Composites, Samruddhi Yashwant Gaikwad

All Dissertations

Self-healing polymers capable of recovering from mechanical damage are promising materials for advanced applications, especially those involving mechanical and/or physical fatigue. In these studies, we have developed techniques to achieve autonomous self-healing in commodity Styrene/n-butyl acrylate copolymers. The mechanism of self-healing in the designed polymers involves inter-and/or intrachain non-covalent interactions between π-cloud and polar linkages of acrylic nBA in random/preferentially alternating copolymers. A combination of spectroscopic tools, thermo-mechanical analysis, and molecular dynamics (MD) simulations has been used to elucidate the mechanism of self-healing. These studies further show the incorporation of dipolar C-F groups to understand the effect of having fluorinated …

Investigation Of Solid-State Reactive Sintering And Rapid Laser Reactive Sintering For Al-Doped Li7la3zr2o12 Solid-State Electrolyte, Aaron Santomauro

All Dissertations

As a society, we’ve exhausted an extreme amount of fossil fuels and put an overwhelming strain on Earth’s natural resources. From this, it is critical to think about the successful future of our planet and ourselves by developing energy devices such as all-solid-state lithium-ion batteries (ASSLIBs). These devices offer a greener and more efficient alternative to power our daily lives, such as electric vehicles (EVs), portable electronics, medical devices, grid-scale energy storage, and aerospace/aviation. ASSLIBs are an excellent alternative to liquid-state batteries, which pose dangerous safety concerns (e.g., flammability, electrolyte leakage, etc.). These ASSLIBs are known to have generally high …

Advancing Lithium-Ion Batteries Through Exploration Of Novel Physico-Chemical Phenomena, Peshal Karki

All Dissertations

Lithium-ion batteries (LIBs) power a wide range of modern devices, from smartphones to electric vehicles. This dissertation integrates materials characterization and electrochemical testing to develop novel Si-based electrode materials, investigate separator effects, and improve electrochemical impedance spectroscopy (EIS) modeling. First, I synthesized Si@CC composites using bio-based carbon sources and discovered a novel in situ disorder reduction in the amorphous carbon cloud during cycling, attributed to Si volume fluctuations and mesoporous carbon structure, which enhanced capacity retention. A binder-free electrode (Si@CC@BP) using bucky paper further improved gravimetric and areal capacities while reducing weight and manufacturing complexity.

Next, I investigated how separator …

Structural Design Using Conditional-Gan Fused With Property Text Information: A Case For Masonry Structures, Arash Teymori Gharah Tapeh

All Dissertations

Structural design, by nature, is a complex process that requires a considerable amount of time, expertise, and knowledge. In such a process, the structural designer must navigate various codal provisions to crystallize a proper and adequate design. As the role of automation continues to shape the domain of structural engineering over the past few decades, a new front leverages artificial intelligence (AI). Currently, AI acts as a "copilot," collaborating to advance workflow speed and accelerate the design process. Among all the different collaborations between humans and AI, GANs (Generative Adversarial Networks) are seen to complement human creativity by automating specific …

Human Comfort Modeling, Measurement, And Improvement In Human–Robot Collaboration, Yuchen Yan

All Dissertations

A dissertation is proposed to explore human comfort in human-robot collaboration (HRC) through modeling, prediction, and enhancement methodologies. Human comfort is a crucial yet underexplored factor in HRC, directly influencing task efficiency, trust, and overall collaboration effectiveness. Understanding the influential factors, developing computational models, and refining methods to improve human comfort in HRC are essential steps toward advancing the field of collaborative robotics. To address these challenges, multiple studies have been conducted. A series of experimental studies were performed to investigate how robot motion-based parameters affect human comfort in HRC. These studies examined both analytical comfort modeling approaches and physiological …

An Investigation Into The Impact Of Inverter Based Resources On Critical Clearing Time, Trupal Patel

All Dissertations

Renewable energy sources, mainly inverter-based resources (IBRs) such as solar and wind plants are being connected in large numbers to the bulk power grid in the United States and around the world. Additionally, generation using fossil fuels are being phased out, which results in the loss of rotor inertia, a key contributor to the transient stability of power systems. Therefore, the large-signal behavior of IBRs and its impact on transient stability must be studied.

This work studies this impact through the metric of critical clearing time (CCT). Impact of grid topology, generation mix and control modes of IBRs on CCT …

Bilevel Network Interdiction Models For Human Trafficking Disruption, Daniel Bruno Lopes Da Silva

All Dissertations

In this dissertation, we study a series of bilevel network interdiction problems motivated by applications in human trafficking disruption. First, we consider a bilevel network interdiction problem where the follower aims to maximize the amount of flow from the source node to the sink node and the leader aims to minimize the number of arcs from a critical set that have positive flow on them in the solution obtained by the follower. This problem models the situation where an anti-trafficking agent wants to minimize the number of people affected by the trafficking operations whereas the trafficker wants to maximize trafficking …

Modeling Disaster Resilience Through A Human-Centered Lens: Exposure, Vulnerability And Adaptation, Tong Liu

All Dissertations

The core of reframing and operationalizing disaster resilience with a human-centered lens is to incorporate concepts from socio-ecological resilience into engineering resilience to better understand the humans’ capability for disaster adaptation. Existing studies have drawn practical implications by identifying actionable thresholds for infrastructure systems under disasters, which can be easily applied by policymakers, emergency managers and municipal agencies. However, how individuals interact with, respond to, or adapt under these infrastructure thresholds remain understudied. This hinders the operationalization of disaster resilience at the human scale.

First, I examined exposure by analyzing how configuration and distribution of urban infrastructure systems, such as …

Synthesis And Characterization Of Magnetic Nanoparticles To Study Effective Magnetic Anisotropy For Biomedical And Catalytic Applications, Alexander Malaj

All Dissertations

This dissertation focuses on understanding how to tune the magnetic properties of nanoparticles through controlling the effective magnetic anisotropy (Keff), which is a key variable in determining a nanoparticle’s Néel relaxation time, which will dictate its magnetic behavior in various applications. In this work, magnetocrystalline anisotropy is tuned by synthesizing tri-metallic substituted ferrite (Fe3-x-yMnxCoyO4) nanoparticles with specific metallic compositions that were informed by computer simulations using density functional theory (DFT) to target magnetocrystalline anisotropy values. A drip synthesis was used to control the size and composition of the tri-metallic ferrites, which were revealed to be monodisperse and compositionally mixed by …

Constructing A State: Canals And The Transformation Of The Economy, Politics, And Finance In Nineteenth-Century New York, Youwei Xing

All Dissertations

This dissertation consists of three essays in economic history, unified by a focus on one of America's earliest transportation infrastructures, the canal system, in nineteenth-century New York. Each chapter explores a different aspect of the state's transformation: its economy, politics, and finance, each of which helped construct New York as the Empire State.

The first chapter studies the economic impact of canals on economic modernization from three aspects: sectoral transition, urbanization, and banking development. Contrary to much of the modern literature finds transportation infrastructure leads to decentralization, I find the opposite-evidence of centralization. Specially: (1) canal towns experienced a transition …

Fleet Algorithm Design For Pooled Rideshare: Integrating Human Factors, Simulation, And Optimization, Joseph Paul

All Dissertations

This dissertation explores the study the integration of human factors modeling and rideshare fleet control algorithms. Pooled rideshare is a unique transportation mode offering that allows riders increased flexibility and accessibility over public transportation, and decreased cost relative to personal vehicles or traditional rideshare. Additionally, relative to personal vehicles, pooled rideshare offers reduced costs and options for those with difficulty obtaining transportation. Prior research in the space typically focused on modeling human behavior, or optimizing system performance, but a lack of integration of the concepts leads to unrealistic or underutilized outcomes. To tackle this problem, novel rideshare assignment, and repositioning …

International Comparison Of Weather And Emission Predictive Building Control, Christian Hepf, Ben Gottkehaskamp, Clayton Miller, Thomas Auer

Research Collection College of Integrative Studies

Building operational energy alone accounts for 28% of global carbon emissions. A sustainable building operation promises enormous savings, especially under the increasing concern of climate change and the rising trends of the digitalization and electrification of buildings. Intelligent control strategies play a crucial role in building systems and electrical energy grids to reach the EU goal of carbon neutrality in 2050 and to manage the rising availability of regenerative energy. This study aims to prove that one can create energy and emission savings with simple weather and emission predictive control (WEPC). Furthermore, this should prove that the simplicity of this …