Engineering Commons^™

Universal Systems Simulation Via Constraint Hypergraphs With Applications To Digital Twins, John Morris

All Dissertations

The characterization of systems encompasses a variety of modeling frameworks designed to capture specific behaviors and components of various system domains. Whatever the framework, the core elements of a system representation are the information of the system and a description of how that information is related. The relations in deterministic systems are functions, which, when composed to form executable processes, can be used to simulate system data. A declarative modeling framework is one that encodes mechanisms for preparing these simulations within the model structure, allowing an external agent to form the execution processes required for a given context. To date, …

Thermal Management Of Power Electronic Converters In Electric Motor Drives Using Active Thermal Control And Active Cooling, S M Imrat Rahman

All Dissertations

The application of power electronic converters (PEC) in electric vehicles (EVs) has significantly increased due to their enhanced controllability and flexibility. Additionally, Permanent Magnet Synchronous Machines (PMSMs) are favored in EVs for their higher torque, efficiency, performance, and heat dissipation capabilities compared to asynchronous machines. The reliable operation of power converters in PMSM drives is crucial for EV operation, and this is driving interest in developing innovative and sustainable technologies that ensure the safe and reliable functioning of PECs. One of the main challenges in achieving reliable PECs is designing effective thermal management systems to control junction temperature and reduce …

Advancements In Sinkhole Remediation: Field Data-Driven Sinkhole Grout Volume Prediction Model Via Machine Learning-Based Regression Analysis, Bubryur Kim, Yuvaraj Natarajan, K. R. Sri Preethaa, V. Danushkumar, Ryan Shamet, Jiannan Chen, Rui Xie, Timothy Copeland, Boo Hyun Nam, Jinwoo An

Civil Engineering Faculty Publications

Sinkhole formation poses a significant geohazard in karst regions, where unpredictable subsurface erosion often necessitates costly grouting for stabilization. Accurate estimation of grout volume remains a persistent challenge due to spatial variability, site-specific conditions, and the limitations of traditional empirical methods. This study introduces a novel machine learning-based regression model for grout volume prediction that integrates cone penetration test (CPT)-derived Sinkhole Resistance Ratio (SRR) values, spatial correlations between CPT and grouting points (GPs), and field-recorded grout volumes from six sinkhole sites in Florida. Three data transformation methods, the Proximal Allocation Method (PAM), the Equitable Distribution Method (EDM), and the Threshold-based …

The Equity Implications Of Pecuniary Externalities On An Electric Grid, Charles Sims, Gasser G. Ali, J Scott Holladay, Tim Roberson, Chien-Fei Chen, Islam H. El-Haddad

Civil Engineering Faculty Publications

The adoption of rooftop photovoltaic (PV) systems can create upward pressure on retail electricity rates as utilities are forced to spread their fixed costs of generation and transmission across a smaller customer base. Since high-income households are more likely to purchase PV systems, low-income households may be disproportionately impacted by these rate increases. Using a novel combination of agent-based computational economic modeling and a choice experiment of rooftop solar adoption, we show how this pecuniary externality between low- and high-income customers increases low-income electricity bills by 10% in an area with some of the highest poverty rates in the United …

A Low-Power Mixed-Signal Potentiostat System-On-Chip With Integrated Dual-Slope Adc, Seth Mcrobert

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

This thesis presents the design and characterization of a low-power mixed-signal potentiostat that was integrated with a 65 nm core in a SoC for low-power electrochemical sensing applications. The system integrates a low-noise transimpedance-based potentiostat front end with a 12-bit dual-slope analog-to-digital converter (ADC) for accurate current-to-digital conversion. The potentiostat core—comprising the control amplifier, current-mirror network, and transimpedance amplifier—consumes 38.2 µA from a 2.5 V supply (95.5 µW) and achieves an input-referred noise floor of 113 µVRMS over a 330 Hz bandwidth, while having an input current range from 1 nA to 20 µA and a noise-limited sensitivity of 56.4 …

Enhancing Ad/Adrd Management Through Ihelpcare: A Compliant And Culturally Sensitive Ai-Driven Digital Healthcare Platform, Trisha Bhowmick

Master's Theses

The digital healthcare field is expanding fast, and now it requires platforms that use advanced technology and maintain robust data security and compliance practices. In the present paper, we present the main structure, key methods, and compliance strategies of the digital healthcare system iHelpCare, which, while fully meeting the HIPAA/GDPR requirements, provides health services more accessible, efficient, and inclusive. The proposed platform is powered by AI for personalized care solutions, with the main emphasis on preventive health management and providing tools for people with disabilities.

iHelpCare achieves real-time patient monitoring while securing medical data management and easy communication between patients, …

Llm-Powered Question Answering For Object States In Virtual Reality, Shiyi Ding

Master's Theses

Recent advances in large language models (LLMs) and multimodal large language models (MLLMs) enable natural language–based querying in virtual reality (VR). However, VR environments are highly localized, personalized, and dynamic, making it challenging for general-purpose models to answer environment-specific queries or reason about subtle object state changes. To address these challenges, this thesis develops two systems for 3D question answering in VR.

First, we present RAG-VR, the first retrieval-augmented 3D question-answering system designed for VR. RAG-VR augments an LLM with external knowledge retrieved from a localized knowledge database and includes a pipeline for extracting environmental and user-related information. To improve …

Nanotechnology Strategies For Endometrium Health: Are We On The Right Track?, Victoria Herrera, Dana Tarab-Ravski, Subhash Chauhan, Nikesh Narang, Mohammad Mirazul Islam, Dan Peer, Rajendra Prasad, Murali Yallapu

School of Medicine Publications

The endometrium is a vital mucosal tissue which undergoes cyclical regeneration, differentiation, and remodeling upon hormonal, cellular, and molecular signaling networks. Dysregulation of these processes can trigger a range of pathological conditions including chronic inflammatory disorders, hyperplastic lesions, malignancies, and infertility, necessitating the need for effective therapeutic interventions. Furthermore, we are still dependent on conventional treatment modalities which are often constrained by inefficient drug biodistribution, systemic toxicity, and emergence of therapeutic resistance. Recently, nanomedicines have gained tremendous attention in human healthcare, because they not only diagnose the disease but also deliver therapeutic agents to the targeted site without affecting healthy …

Polydopamine-Coated Magnetic Nanoparticles Data, William G. Pitt

ScholarsArchive Data

This data archive contains raw data and processed data related to research and development of magnetic nanoparticles that adhere to bacteria. This data is the foundation of data in the MS thesis of Bowen Houser, and publications and presentations related to that research effort. Polydopamine-coated magnetic nanoparticles are found to be very adhesive to gram-positive bacteria, and less adhesive to gram-negative bacteria. These data files contain information for S. aureus, S. epidermidis, S. mutans, E. coli, P. aeruginosa, and N. perflava. Some data include the kinetics of capture.

Data Release Of 5-Fluorouracil From Polylactic Acid Microparticles Containing Magnetic Nanoparticles, William G. Pitt

ScholarsArchive Data

This data archive contains raw data and processed data related to research and development of the release of the chemotherapy drug 5-fluororacil from microparticles of poly(lactic acid) which also contain superparamagnetic magnetite nanoparticles. This data is the foundation of data in the MS thesis of Tyler Green, and publications and presentations related to that research effort.

Scalable Carbon-Based Electrodes For Hole-Transport Layer-Free Perovskite Solar Cells., Sharmin Akter

Electronic Theses and Dissertations

Perovskite solar cells (PSCs) have rapidly reached certified single-junction efficiencies near 26%, but deployment is still limited by operational instability, scale-up challenges, and the cost and complexity of typical device stacks. This dissertation explores a simpler, scalable approach: HTL-free PSCs using low-cost, chemically robust carbon (e.g., carbon black) counter electrodes compatible with low-temperature, solution processing. This work demonstrates how carbon-ink formulation, scalable deposition (blade vs. slot-die), and work-function-tuning additives control film quality, interfacial energetics, and device performance. Carbon inks were developed for both coating methods by systematically varying carbon-to-binder ratio, polymer chemistry, and solvent system. Among the binders screened, ethyl …

Emerging Solid Electrolytes For Solid-State Sodium Batteries: Synthesis And Interface Study., Xiaolin Guo

Electronic Theses and Dissertations

Over the past decade, solid-state batteries have attracted significant attention as the next-generation energy storage technology due to their higher energy density and enhanced safety. Given the abundant sodium (Na) resources relative to lithium (Li), the development of sodium-based batteries has become increasingly compelling. Within a solid-state battery, the solid electrolytes (SEs) serve the dual function of (i) electronically insulating and physically separating the electrodes, and (ii) transporting ions between the anode and cathode. To meet these essential requirements, ideal SEs must process high ionic conductivity with negligible electronic conductivity, robust structural and chemical stability, a wide electrochemical window, and …

From 2d To 3d: Multi-Agent Reinforcement Learning For Spectrum-Constrained Urban Air Mobility., Qingyang Li

Electronic Theses and Dissertations

Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) are accelerating a transformation of air transportation but face acute spectrum congestion in dense urban environments. Reliable Control and Non-Payload Communications (CNPC) must be maintained at all times to ensure safe operations, even as fleets of aerial vehicles (AVs) transport passengers and cargo between distributed vertiports. We first develop a 2D formulation that jointly optimizes discrete headings, velocities, and spectrum allocation to minimize total mission time while satisfying quality of service (QoS) and collision-avoidance constraints, and we demonstrate significant gains over non-learning and learning baselines. Building on this 2D framework, we …

Design And Development Of A Multi-Port Solid State Circuit Breaker Based On Half Bridge Sic Mosfets, Yannal Nawafleh

Graduate Theses and Dissertations

This thesis investigates multi-port solid-state circuit breaker (M-SSCB) architectures that reduce steady-state conduction losses while preserving microsecond-class DC fault interruption and per-port selectivity. The proposed M-SSCB consolidates protection for several node interfaces into a single assembly with shared sensing, control, and a common energy-absorption branch. In normal operation, two electrically symmetric parallel semiconductor paths are established so each port’s current divides approximately in half; because conduction loss scales with current squared, the M-SSCB achieves ≈75% reduction in on-state loss relative to a conventional anti-series SiC path without increasing device count. During fault handling, the coordinated controller detects the local over-current, …

Advanced Membrane Methods For Treatment Of Toxic Contaminants And Education Of Early-Career Researchers, Thomas Mckean Iii

Graduate Theses and Dissertations

Membrane technologies are attractive as they are linearly scalable and often require lower operating costs compared to other technologies. One area where they are particularly effective is the treatment of water contaminated with toxic substances. The simplicity of this removal mechanism provides reliable performance capable of meeting stringent removal requirements. However, membrane fouling is a major challenge that often limits their commercial viability. This research sought to investigate novel approaches to pretreatment and membrane modification to overcome fouling and high operating pressures. In addition, membrane separation processes can often be developed into simple yet educational experiments that are ideal for …

Feed Network Design For Passive Beamforming In Hemispherical Phased Arrays, Daniel Flores

Theses and Dissertations

This thesis presents the design, fabrication, and evaluation of a four-element microstrip patch antenna array with a passive 1 to 4 corporate feed network operating at 5 GHz. A single inset-fed patch was developed on Rogers DiClad 880 to ensure accurate tuning and mechanical flexibility, achieving a measured resonance of 5.009 GHz with excellent return loss. The corporate feed network, synthesized using T-junction dividers and quarter-wave transformers, demonstrated strong impedance matching, balanced amplitude distribution, and broadside realized gain near 10 dBi when integrated with the array.

Beam steering was examined through simulation-based phase control, revealing effective scanning up to approximately …

Piezoelectric Energy Harvesting From Roadways: Challenges, Advances, And Future Directions, Heba Mohamed Gaber, Mohamed Abdel-Raheem

Civil Engineering Faculty Publications

As the global demand for renewable energy intensifies, piezoelectric energy harvesting from roadways has emerged as a promising avenue for sustainable power generation. This systematic literature review analyzes 61 peer-reviewed studies to assess the feasibility, performance, and potential of integrating piezoelectric systems into roadway infrastructure. While technology faces challenges, such as high installation costs, limited energy output, and a scarcity of thorough economic evaluations, findings suggest it holds considerable promise as a supplementary renewable energy source. The review analyzes the operational characteristics and efficiencies of various piezoelectric transducers, identifies key factors influencing system performance, and evaluates recent technological advances. It …

Optimization Of Size And Siting Of Distributed Generation In Unbalanced Distribution Systems: A Literature Review, Pema Dorji, Stefan Lachowicz, Octavian Bass

Research outputs 2022 to 2026

Renewable energy sources (RES) are essential for meeting the rising global electricity demand while reducing greenhouse gas emissions from conventional generation. As traditional systems approach capacity saturation, the integration of RES into power grids becomes increasingly vital. However, the intermittent and variable nature of RES introduces significant technical, economic, and operational challenges. This review focuses on the optimal planning and integration of distributed generation in unbalanced distribution systems, which more accurately reflect real-world power network conditions. Emphasis is placed on siting and sizing strategies aimed at enhancing voltage stability, minimizing power losses, and reducing system costs and emissions. The review …

Interface Engineering And Safety In Solid-State Batteries: Advancing From Human-Centered Insights To Ai-Driven Innovations, Elnaz Karimi, Stefan Iglauer, Muhammad Rizwan Azhar

Research outputs 2022 to 2026

Solid-state batteries (SSBs) represent a transformative advancement in energy storage, offering superior safety, higher energy density and extended cycle life compared to conventional lithium-ion batteries (LIBs). However, challenges related to interface engineering—particularly in ensuring stable electrochemical performance and preventing lithium dendrite formation—have hindered their widespread adoption and can compromise safety. Effective interface engineering is critical for mitigating interfacial resistance, enhancing mechanical stability and preventing thermal runaway, all of which are vital for improving battery reliability. The integration of artificial intelligence (AI) and machine learning (ML) in this context accelerates battery optimization by enabling predictive modelling of interfacial behaviour, material discovery …

Next-Generation Underwater Localization: Artificial Intelligence-Based And Energy-Aware Approaches, Mainul Islam Chowdhury, Quoc Viet Phung, Iftekhar Ahmed, Walid K. Hasan, Daryoush Habibi

Research outputs 2022 to 2026

Designing accurate, reliable, and energy-efficient localization techniques for underwater acoustic networks is highly challenging due to factors such as large propagation delays, the absence of Global Positioning System (GPS), node mobility, and limited acoustic link capacity. In any underwater sensor network (UWSN) monitoring application, data collected by underwater nodes becomes more meaningful when accompanied by location information. However, traditional localization methods often rely on geometric models and statistical filters that are highly sensitive to sensor noise and communication constraints. Energy consumption is another primary concern in UWSNs, not only because replacing and recharging underwater batteries are challenging, but also due …

Mozgus, Damian Cerda, Madison Lopez

Computer Science and Software Engineering

The indie game market is flooded with genre experiments, yet few successfully combine fast-paced action with meaningful strategic decision-making. Our project aims to fill this gap by creating a game that fuses top-down action combat with resource-management tycoon mechanics. We found that in many games, the management phases lack mechanical stakes. Our goal was to intertwine these systems so that choices made in one phase meaningfully impact the other.

Integrating Machine Learning With An Fps Aim Trainer For Optimal Sensitivity Finding, Sharan Krishna

Computer Science and Software Engineering

First-person shooter (FPS) games often demand high levels of skill in aiming, which leads players to look for external tools to improve their performance. This is where the concepts of aim training and aim trainers come in, becoming an easily accessible outside source for players to strengthen their performance with custom scenarios outside a set game. While many aim trainers exist, they offer limited insight into player performance metrics or adaptability to varying aiming styles. Furthermore, most existing aim trainers lack a standardized way of correlating aim skill with real-world performance or personalized feedback. This aim trainer addresses these limitations …

Optimal & Robust Control Of A Bidirectional Dc-Dc Converter In Ev Systems, Yasser Ayeva

Electrical Engineering and Computer Science Faculty Publications and Presentations

This paper analyzes the performance of PI, LQR, and H∞ controllers for the regulation of a bidirectional buck boost converter in electric vehicle systems. To get the system state space equations, a continuous conduction average model is linearized. For analysis a PI controller will be used as baseline, the LQR controller will be used to improve transient response, and the H∞ controller will be used for the system robustness and disturbance rejection. The simulation results show that the advanced controllers surpass the PI controller in terms of overshoot, settling time, and voltage ripple, with the H∞ controller offering the best …

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 …

Reinforcement Learning Based Security Schemes For Distributed Ai Systems, Ashan Chamath Gunawardena

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

Distributed machine learning (DML) is a component of modern intelligent systems, enabling collaborative training across devices such as mobile clients, vehicles, and edge networks. However, the decentralized nature of these systems introduces vulnerabilities, particularly data poisoning attacks that compromise model integrity and degrade performance. Traditional defenses, such as statistical filtering, robust aggregation, and privacy-preserving techniques, often struggle to adapt to overwhelming adversaries or operate under strict privacy and real-time constraints. This dissertation proposes the use of reinforcement learning (RL) and deep reinforcement learning (DRL) based misbehavior detection schemes that dynamically identify poisoning attempts in distributed AI systems, including federated learning, …

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, …

Ethical Decision-Making Processes In Authentic Environmental Engineering Contexts Through Systems Thinking And Team Collaboration Lenses: An Embedded Single Case Study, Toluwalase Eniola Brower

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

Ethical and professional responsibility is a critical learning outcome emphasized in ABET accreditation. However, ethics instruction in engineering education often lacks integration of system-level considerations such as economic, environmental, and societal contexts, that are essential for developing engineering solutions that ensure the safety and welfare of diverse stakeholders. This embedded single-case study investigated the integration of authentic ethics instruction within a junior-level environmental engineering course at a Midwestern U.S. university during spring 2025 and explores how civil engineering student teams within the course engage in ethical decision-making process during authentic problem-solving.

The instructional intervention consisted of four problem-based ethics modules, …

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 …

Rapid State-Of-Health Estimation Of Batteries Using Machine Learning With Limited Eearly-Discharge Voltage Data, Mohammad Bakhtiari

Durham School of Architectural Engineering and Construction: Dissertations, Theses, and Student Research

The utilization of lithium-ion batteries has been rapidly expanding across diverse sectors, including electric transportation, stationary energy storage systems, and the built environment. Ensuring a high level of reliability in these applications is essential, as the performance and safety of such systems depend strongly on the accurate assessment of the battery’s State of Health (SOH). Conventional SOH estimation techniques—often based on complex electrochemical models or extensive laboratory testing—tend to require a large number of measurements, advanced instrumentation, and high computational cost. These factors make them impractical for large-scale deployment or real-time monitoring. This study introduces a simplified machine-learning-based approach for …

Series Resonant Converters With Medium Voltage Sic Mosfets For Electric Aircraft Applications, Xinyuan Du

Graduate Theses and Dissertations

To develop high-performance high- power-density MV power converters, the emerging silicon carbide (SiC) devices are more attractive than their silicon (Si) counterparts, since the fast switch frequency brought by the SiC can effectively reduce the volume and weight of the filter components and thus increase the converter power density. From the converter topology perspective, with the MV dc distribution, the single stage isolated dc/dc converter are suitable for next-generation electric aircraft system due to soft switching and high power density. In this work, comprehensive static and dynamic characterizations were conducted for the latest 6.5 kV silicon carbide (SiC) MOSFETs from …