Engineering Commons^™

Sex Differences In Active Avoidance And Neural Circuit Mechanisms In Contextual Fear Generalization, Carly Vincent

Theses and Dissertations

The current studies were aimed to investigate two behavioral hallmarks of anxiety and stress-related disorders, avoidance responses and the over-generalization of fear. In the first set of studies, active avoidance and extinction learning, that parallels exposure therapy in preclinical rodent models, were used. It is known that stress can influence aversive learning and extinction training, which can result in poor extinction retention. However, it is not well understood how the stress response is facilitating extinction resistance in active avoidance learning across sexes. Therefore, the first set of studies aimed to investigate the role of biological sex and glucocorticoid receptor (GR) …

Design And Application Of Redox-Mediated Flow Electrode Electrodialysis For Ion Removal And Recovery, Rongxuan Xie

Theses and Dissertations

To meet the growing demand for freshwater driven by population growth and rising living standards, the first desalination plants were established in the late 1950s. As energy costs have risen over time, research has increasingly focused on reducing the overall cost of water treatment. Electrodialysis (ED), which facilitates the migration of anions and cations across ion exchange membranes under the influence of an electric field, has gained significant attention as a treatment method for saline water and brine due to its simplicity, low cost, and scalability. However, its traditional batch operation mode and the potential for generating flammable gases have …

Autonomous Real-Time Model Updating Within Digital Twin Frameworks For Thermal Systems, Braden Robert Priddy

Theses and Dissertations

As engineering systems increase in scale and complexity in the era of the Fourth Industrial Revolution, data-driven solutions will become essential in enabling the next generation of these systems. One of the trending tools that can aid in this transition is digital twins. As physical systems degrade throughout their life cycles, their behavior also changes. Digital twins use data assimilation to continuously update virtual models to represent the current state of their physical counterparts. A reliable digital twin can be leveraged by a system operator to perform diagnostics, optimize, and tests without ever needing the physical system. However, implementing effective …

Advancement Of The Zinc Ion Battery: Polymer Electrolyte And Electrode Development For Aqueous Zinc-Ion Batteries, Roya Rajabi

Theses and Dissertations

Rechargeable aqueous zinc-ion batteries (ZIBs) have garnered significant attention in recent years as a promising candidate for stationary large-scale energy storage due to their distinct safety features and cost-effectiveness compared to conventional lithium-ion batteries. Despite their great potential, ZIBs are currently facing critical challenges for commercialization, including poor cycle stability at low discharge rates, lower energy density (Wh/kg) and higher self-discharge rate. These issues must be addressed for them to become a viable energy storage solution. The above challenges are fundamentally rooted in the bulk properties of electrolytes and interactions with electrodes, such as; 1) formation of insulating layered double …

Augmented Reality (Ar) And Virtual Reality (Vr)-Based Data Visualization Frameworks For The Manufacturing Industry, Nitol Saha

Theses and Dissertations

Industry 4.0 is transforming the manufacturing industry by integrating digital technologies throughout the production lifecycle, leading to the development of smart factories. The integration of Augmented Reality (AR) and Virtual Reality (VR) alongside smart manufacturing is transforming traditional industry practices by establishing a robust cyber-physical infrastructure, enhanced data visualization, and improved task execution. This thesis aims to develop AR and VR-based data visualization frameworks for the manufacturing industry, focusing on detailed implementation strategies, initial results, and key findings of these frameworks. One major focus of these frameworks is the generalization of the technological assets so that these frameworks can be …

Augmented Reality Based Maintenance Operations And Training, Victor Scott Gadow

Theses and Dissertations

Augmented Reality (AR) is the process of superimposing virtual information on top of objects or other structures in the real-world environment. It is considered one of many paradigms included in the idea of smart manufacturing and can enable a mixture of the other technologies involved. A large increase in research on AR has been seen in the past decade as technologies have begun to evolve to become more robust and reliable. It has been implemented into several key areas of manufacturing such as maintenance, assembly, training, and quality control. The rise of industry 4.0 is changing how data is used …

Characterizing Mechanical Behaviors Of Railroad Ballast Based On Large-Scale Triaxial Tests, Shihao Huang

Theses and Dissertations

Ballast, typically composed of large unbound aggregates with uniform gradation, is essential for the structural integrity of railroad tracks, facilitating load transfer, drainage, and ensuring stability and resilience. The mechanical behaviors of ballast, including shear resistance, resilient modulus, and permanent deformation, are critical for effective railroad design and maintenance, directly impacting track geometry. Degradation of these mechanical properties can lead to significant track-related issues, such as excessive settlement and train derailments, resulting in substantial property damage, injuries, and fatalities. This dissertation aims to characterize mechanical behaviors of railroad ballast from perspectives of aggregate interaction, cyclic loading pulses and climatic conditions, …

Data-Driven Discovery Of Extreme Thermal Materials By High-Throughput Computation And Machine Learning, Joshua Ojih

Theses and Dissertations

The quest for materials with extraordinary properties has been a longstanding endeavor in material science and engineering, driving future technological advancement. However, the discovery of such materials is non-trivial. Recent advancements in computational methods, particularly the integration of machine learning (ML) techniques with density functional theory (DFT), have opened new avenues for accelerating the discovery of materials with exceptional and extreme properties. This dissertation focuses on developing a synergistic approach and workflow combining ML and DFT to identify materials with properties that are pushed beyond current limits, using lattice thermal conductivity (LTC) as a case study of the workflow.

We …

Electroless Deposition And Galvanic Displacement For The Control Of Supported Nanoparticle Size And Composition, Haiying Zhou

Theses and Dissertations

Catalyst performances can be greatly affected by properties such as particle size, composition, geometry, and cleanliness of the active surface. To achieve optimal catalytic performance, appropriate synthesis methods are required to synthesize the desired structures. Supported metal particle catalysts are usually prepared by impregnation and precipitation methods in industry. Although these two methods are simple, they exhibit poor control over surface morphology, leading to a wide particle size distribution and uncontrolled distribution of different metal components. In this dissertation, three topics on controlling surface morphology are discussed.

For structure sensitive reactions, reactivity and selectivity can be strongly affected by particle …

Rational Catalyst Synthesis For Sustainable Energy Applications, Alaba Upe Ojo

Theses and Dissertations

Energy accounts for two-thirds of the global climate challenges. Effective utilization of green hydrogen or finding cleaner ways to improve energy generation is necessary to combat climate crisis and allow for a more sustainable future. This work evaluates three heterogeneous catalytic processes which contribute to a sustainable future. In chapter 2, we studied the hydrogenation of toluene to methylcyclohexane; a reaction that can potentially serve as a medium for hydrogen storage and help to overcome the safety challenges of transporting gaseous hydrogen. We found that palladium catalysts on certain carbons exhibited significantly enhanced toluene hydrogenation rates compared to activated carbons …

Real-Time Robot Pose Estimation For Industry 4.0: Enhancing Motion Validation And Monitoring With A Vision-Based Framework, Jad Samaha

Theses and Dissertations

Amidst the era of Industry 4.0, robots became integral to automated production lines by performing complex tasks with high precision and adapting to changing production needs in real-time. Therefore, ensuring their precise and reliable operation is paramount for maintaining high-quality standards and operational efficiency. This invoked the need for an automated motion validation tool that guarantees accurate program task execution, by detecting deviations or anomalies that may indicate mechanical faults or software errors. Given the exponential advancements in AI, particularly in Computer Vision, a vision-based solution is ideal for ensuring the correct positioning of a robot in real-time. Operating independently …

Redefining Gas Turbine Engine Development: A Digital Twin Framework Informed By Operational Dynamics And Numerical Analysis, Sowmya Raghu

Theses and Dissertations

Gas Turbine Engines (GTEs) serve as primary propulsion systems in aviation and are key for power generation units in various industrial applications. The conventional Gas Turbine Engine Development and Monitoring Lifecycle (EDML) typically encompasses six stages: preliminary design, numerical analysis, prototyping and testing, manufacturing, systems integration, and subsequent systematic monitoring processes. This dissertation redefines the gas turbine engine design and development process by synergistically integrating design capabilities, real-time operational data, and predictive maintenance through the implementation of digital twins. The primary objective is to establish a comprehensive framework for gas turbine engine design by utilizing thermodynamic and aerodynamic modeling, supported …

Tracking Deposition And Settling Characteristics Of Airborne Metallic Particulate, William Kahale Caspino

Theses and Dissertations

Transport and deposition of metal particles is a source of environmental and public health concern. Understanding how ambient conditions and the properties of the particles interact to influence the dispersal range can provide information on and the possible extent of environmental contamination. Controlled laboratory experiments and modeling were utilized to determine when such particles would deposit. Particle samples containing heavy metals, a Palladium-dominant alloy and a Nickel/Aluminum dominant alloy LANA, were released in a static column, and the vertical displacement was tracked utilizing a Phantom v7.3 camera and a camera lens. Electron microscopy revealed that particles are not spherical and …

Thermal Management Of Power Electronic Devices Using Single Crystal Aln Heat Spreaders, Md Abdullah-Al Mamun

Theses and Dissertations

Due to high critical electric field and saturation velocity, wide bandgap (WBG) III-Nitride semiconductor materials (AlxGa1-xN) and their heterostructures have gone through extensive research in academia and industry for applications requiring high-voltage, high-current, high-frequency, and high-temperature transistor operation. AlGaN/GaN high electron mobility transistor (HEMT) has been commercialized for 650-V power converters, smartphones, PCs, USB wall power outlets, on-board and off-board EV chargers, and numerous other applications. However, AlGaN/GaN HEMTs grown on low-cost sapphire or Si substrates face significant self-heating issues due to the poor thermal conductivity of the substrate. The high thermal resistance (RTH) and heat capacity of the substrates …

A Process Planning Software For Modeling Parameter Behavior In Automated Fiber Placement, Benjamin Jeffrey Francis

Theses and Dissertations

The manufacturing of large-scale, geometrically complex composite structures is often accomplished today using the Automated Fiber Placement (AFP) process. AFP utilizes a fiber placement end effector and a gantry or robotic kinematic system to lay up groups of composite tows, iteratively building the complete structure. The reduced width of each tow allows the deployment of AFP for builds with significant curvature, unlike other automated methods such as automated tape laying. Despite its proven track record and widespread use, the current AFP process contains inefficiencies and suffers from workflow bottlenecks that significantly increase cycle time, material wastage, and overall cost. A …

Development Of Avalanche Photo Detector For Uv-C Using Gallium Oxide Material System, Md Ghulam Ghulam Zakir

Theses and Dissertations

This work describes the metal-organic chemical vapor deposition (MOCVD) optimization process for epitaxially grown gallium oxide (Ga2O3) layers, electrical field distribution, and the design for Avalanche Photo Detector (APD). MOCVD is a well-accepted process in the semiconductor industry, as it is well-known for its precise deposition of ultra-thin, high-quality semiconductor layers with extraordinary control over composition and thickness. The choice of Ga2O3 is due to r its distinctive properties of ultra-wide bandgap and low turn-on resistance. Thus, Ga₂O₃-based materials can withstand high voltage and current with the least energy loss, making them an attractive choice for …

Unveiling Similarities In The Code Of Life: A Detailed Exploration Of Dna Sequence Matching Algorithm, Mahmoud Y. Shams, Romany M. Farag, Dalia A. Aldawody, Huda E. Khalid, Ahmed K. Essa, Hazem M. El-Bakry, A. A. Salama

Neutrosophic Systems with Applications

Identifying similar DNA sequences is crucial in various biological research endeavors. This paper delves into the intricate workings of a specific algorithm designed for this purpose. We provide a systematic explanation, exploring how the algorithm handles user input, reads stored DNA sequences, utilizes the Word2Vec model for vector representation, and calculates sequence similarity using diverse metrics like Cosine Similarity and Neutrosophic Distance. Additionally, the paper explores the incorporation of neutrosophic values to account for uncertainty in the comparisons. Finally, we discuss the extraction of results, including matched sequences, similarity scores, and accuracy measures. This in-depth exploration provides a clear understanding …

An Approach To Multi-Attribute Decision-Making Based On Single-Valued Neutrosophic Hesitant Fuzzy Aczel-Alsina Aggregation Operator, Raiha Imran, Kifayat Ullah, Zeeshan Ali, Maria Akram

Neutrosophic Systems with Applications

A single-valued Neutrosophic hesitant fuzzy set (SVNHFS) is a combination of a single-valued neutrosophic set (SVNS) and hesitant fuzzy set (HFS) that has been developed to address insufficient, unreliable, and vague environments in which each element has several possible options determined by the truthiness, indeterminacy and falsity value. By considering this, in this paper, we have proposed the Aczel-Alsina aggregation operator (AAAO) for SVNHFS, which is more flexible t-norm and t-conorm than the other and due to the flexible nature of parameters to solve Multi-Attribute decision making (MADM) problems. Further, the score function, accuracy function, and certainty function of SVNHFS …

Burn Cost Modeling For Surface Grinding Optimization, Taiwo Fasae

Dissertations (1934 -)

Surface grinding plays a pivotal role in the machining industry, constituting roughly 25% of all machining operations worldwide. Its precision and efficiency are crucial, particularly in sectors requiring high-quality surface finishes, such as aerospace and semiconductor manufacturing. For thermal damage prevention, traditional approaches to parameter selection use thresholds to exclude burn-prone parameters. However, by omitting the cost of burn, the threshold-exclusion strategy yields outcomes that fail to reflect the true costs of grinding. This dissertation introduces a novel burn cost model that transcends these limitations, offering a more nuanced and cost-effective approach to managing grinding burn. The burn cost model …

Real-Time Synthesis Of A Nonuniformly Correlated, Partially Coherent Beam Using An Optical Coordinate Tansformation, Milo W. Hyde Iv

Faculty Publications

We design, build, and validate an optical system for generating light beams with complex spatial coherence properties in real time. Beams of this type self-focus and are resistant to turbulence degradation, making them potentially useful in applications such as optical communications. We begin with a general theoretical analysis of our proposed design. Our approach starts by generating a Schell-model (uniformly correlated or shift-invariant) source by spatially filtering incoherent light. We then pass this light through an optical coordinate transformer, which converts the Schell-model source into a nonuniformly correlated field. After the general analysis, we discuss system engineering, including trade-offs among …

A Systems Biology Approach To Predict Phenotypes From Genotypes For Plants And Bacteria, Niaz Bahar Chowdhury

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

Predicting phenotypes from genotypes is a central challenge in systems biology in understanding how organisms respond to environmental and genetic changes. To address this, genome-scale metabolic models (GSMs) integrated with omics data and machine learning provide a comprehensive framework to connect genotype to phenotype. This dissertation utilizes these approaches in plants and bacterial systems, revealing key metabolic adaptations. In maize, a root-specific GSM reveals metabolic reprogramming under nitrogen stress, offering strategies for improving stress tolerance. Building on this, a multi-organ maize GSM of temperature stress identifies metabolic bottlenecks, providing targets to enhance crop resilience. Similarly, in rice, a grain-specific GSM …

Effects Of Low-Cycle Fatigue Fracture Of Longitudinal Reinforcing Steel Bars On The Seismic Performance Of Reinforced Concrete Bridge Piers, Yu-Fu Ko, Jessica Gonzalez

Mineta Transportation Institute

Earthquakes, which can cause tremendous local stress and strain on infrastructure, can cause reinforced concrete (RC) bridges to collapse due to the concrete cracking and fracture of the steel reinforcement rebars. The fracture of longitudinal reinforcing steel due to low-cycle fatigue is one of the main causes of failure in RC structures under earthquake loading. The purpose of this research is to include the effects of low-cycle fatigue fracture of longitudinal reinforcing steel bars on the seismic performance of reinforced concrete bridge piers. To obtain a greater understanding of low-cycle fatigue failure of steel reinforcement of RC bridge piers subjected …

Data Provenance Via Differential Auditing, Xin Mu, Ming Pang, Feida Zhu

Research Collection School Of Computing and Information Systems

With the rising awareness of data assets, data governance, which is to understand where data comes from, how it is collected, and how it is used, has been assuming evergrowing importance. One critical component of data governance gaining increasing attention is auditing machine learning models to determine if specific data has been used for training. Existing auditing techniques, like shadow auditing methods, have shown feasibility under specific conditions such as having access to label information and knowledge of training protocols. However, these conditions are often not met in most real-world applications. In this paper, we introduce a practical framework for …

Intercellular Mitochondrial Transfer Contributes To Microenvironmental Fate Redirection Of Mammary Cancer Cells, Julie Sofie Bjerring

Biomedical Sciences Theses & Dissertations

The dynamic cellular microenvironment, made up of resident cells and various macromolecules, differs markedly across tissues in the body. The multidirectional signals that cells receive from this microenvironment, along with the signaling they send back, heavily influence their physiology and behavior. Recent important findings have further validated this notion as the mammary microenvironment has been shown to suppress tumor progression by redirecting cancer cells to adopt a normal mammary epithelial progenitor fate in vivo. However, the mechanism(s) driving changes in metabolic reprogramming and cancer fate redirection is understudied. The work presented in this dissertation focuses on exploring the impact of …

Real-Time Navigation System For Breast Cancer Surgery With Pre- And Intra-Operative Imaging Using Neural Networks, Motaz Alqaoud

Biomedical Engineering Theses & Dissertations

Breast cancer is one of the most frequently diagnosed malignancies in women worldwide, necessitating precise diagnosis and treatment. Breast-conserving surgery (BCS) is the primary treatment for nonpalpable cases, yet current approaches often lack accuracy due to the absence of real-time 3D imaging during surgery. This limitation impairs surgeons’ ability to visualize tumor locations, compromising outcomes and potentially leading to repeat surgeries with higher risks, undesirable cosmetic results, increased costs, and, in some cases, mastectomy. Thus, there is a critical need for a navigation system to facilitate accurate tumor excision in nonpalpable breast cancer through real-time patient-specific 3D tracking.

This study …

Editorial: Novel Computational Fluid Dynamics Methods For Diagnosis, Monitoring, Prediction, And Personalized Treatment For Cardiovascular Disease And Cancer Metastasis, Zahra Keshavarz Motamed, Nima Maftoon, Lakshmi Prasad Dasi, John F. Ladisa Jr.

Biomedical Engineering Faculty Research and Publications

No abstract provided.

Lumbar Spine Orientation Affects Compressive Fracture Outcome, Rachel Cutlan, Muhammaed Khokhar, Nader Shammout, Alok Shah, Lance Frazer, Narayan Yoganandan, Barry S. Shender, James Sheehy, Glenn Paskoff, Daniel Nicolella, Timothy B. Bentley, Saman Shabani, Brian D. Stemper

Biomedical Engineering Faculty Research and Publications

Purpose

Understanding how spinal orientation affects injury outcome is essential to understand lumbar injury biomechanics associated with high-rate vertical loading.

Methods

Whole-column human lumbar spines (T12–L5) were dynamically loaded using a drop tower to simulate peak axial forces associated with high-speed aircraft ejections and helicopter crashes. Spines were allowed to maintain natural lordotic curvature for loading, resulting in a range of orientations. Pre-test X-rays were used to quantify specimen orientation at the time of loading. Primary fracture types were identified (wedge, n = 6; burst, n = 4; hyperextension, n = 4) and compared for loading parameters and lumbar orientation. …

Hardware Control Unit For Trusted Program Verification System, Jake Owen Alt

Master's Theses

Trust in the underlying hardware is the foundational step towards trusting the correctness and integrity of a software application. However, verifying that today's extremely complex processors work exactly as intended has not been feasible, as evidenced by several recent hardware bugs. Trustworthy, formally verified processors currently forego intricate performance enhancements such as out-of-order execution, hampering them substantially versus their less secure counterparts.

The Containment Architecture with Verified Output (CAVO) system solves this problem by isolating the host system and requiring the result of each instruction to be validated by a small, trusted hardware module called the Sentry. Any transmissions to …

A Theoretical Framework For Resilience In Complex System Governance (Csg), Susan A. Caskey

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation addresses a critical gap in resilience research within complex systems by developing a theoretical framework for governance resilience—an underexplored area despite governance's crucial role in maintaining system resilience. Using the Complex System Governance (CSG) framework (Keating, Katina, Chesterman, et al., 2022; Keating & Katina, 2019), resilience is conceptualized as a system's ability to absorb disturbances while sustaining performance and enabling adaptive transformation. This involves three main capabilities: persistence, adaptability, and transformation in response to both internal and external pressures.

Through a constructivist grounded theory approach involving iterative coding, memoing, and theory development, this study inductively constructs a governance …

Optical Investigation Of A Low-Pressure Plasma In A Superconducting Radio-Frequency Cavity, Zachary A. Caudell

Electrical & Computer Engineering Theses & Dissertations

The state-of-the-art cryomodules for particle accelerators use superconducting radio-frequency (SRF) cavities. It is known that accumulation of hydrocarbon impurities reduces the cavity surface work function, decreasing cryomodule performance metrics such as field emission, thermal stability, and accelerating gradients. An in-situ method of plasma processing has recently been developed to clean the cavities and restore cryomodule performance [1]. This study is to understand the properties of the low-pressure plasmas generated in a C100 SRF cavity and ultimately to improve the performance of plasma surface cleaning using optical emission spectroscopy. Using a 500 mm focal length Czerny-Turner monochromator coupled with a photomultiplier …