Engineering Commons^™

Micro/Nanomechanical Properties Of Top-Seeded Melt Grown Ybco Single Crystals Determined Using Depth Sensing Indentation, Ugur Kolemen, Cafer Mert Yesilkanat, Fikret Yilmaz, Fatih Dogan, Orhan Uzun

Materials Science and Engineering Faculty Research & Creative Works

Mechanical properties of the bulk YBa2Cu3O7-x (YBCO) single crystal superconductor, prepared by using the Top Seeded Melt Growth (TSMG) method, were determined. Property measurements were conducted by the nanoindentation method under various loads and the micro indentation method at different temperatures. Hardness (H) and reduced elastic modulus (Er) values were calculated by using the Oliver–Pharr method. According to hf/h max values found from load- displacement curves, there is a sink in behavior around outer rim of the indents that was confirmed by atomic force microscopy (AFM) analysis. Nanoindentation analyses conducted on upper section, middle section and subsection revealed that all …

Variable-Temperature Plasmonic High-Entropy Carbides, Simon Divilov, Sean D. Griesemer, Robert C. Koennecker, Michael J. Ammendola, Adam C. Zettel, Hagen Eckert, Jeffrey R. Shallenberger, Xiomara Campilongo, William G. Fahrenholtz, Arrigo Calzolari, Douglas E. Wolfe, Stefano Curtarolo

Materials Science and Engineering Faculty Research & Creative Works

Effective thermal management at variable and extreme temperatures face limitations for the development of novel energy and aerospace applications. Plasmonic approaches, shown to be capable of tailoring black-body emission, could be effective if materials with high-temperature and tunable plasmonic resonance were available. Here, we report a synergy between experimental and theoretical results proving that many high-entropy transition metal carbides, consisting of four or more metals at equal molar ratio, have plasmonic resonance at room, high (>1000∘C) and variable temperatures. We also found that these high-entropy carbides can be tuned and show considerable plasmonic thermal cycling stability. This paradigm-shift approach …

Exploratory Diver Geotechnical Equipment (Edge), Angel Villicana, Merrick Zellers, Erik Heuchert, Lucas Heuchert

Mechanical Engineering

The goal of this report is to showcase how our final Core Sampler design and prototype address the needs of Navy Divers. Geotechnical equipment for Navy divers has not been updated since the early to mid-1980s, resulting in imprecise and outdated sampling methods. The primary purpose of this project is to enhance, modernize, and redesign a tool to collect a minimally disturbed core sample of the seabed for geotechnical evaluation. This report presents the full development of our project from concept to verification and final outcomes. It begins with the statement of disclaimer, followed by a four-panel executive summary and …

Intrinsic Disinfection Byproducts In Free Chlorine And Chloramine Systems: Formation Of Chlorite, Chlorate, Perchlorate, And Chloronitramide Anion, Julian L. Fairey, Ashley D. Pifer, David G. Wahman

Civil Engineering Faculty Publications and Presentations

Intrinsic disinfection byproducts are formed by reactions between disinfectant species and/or their decomposition products. In this review, we focus on a subset that accumulates in free chlorine and chloramine drinking water systems. First, we review the sequential formation of chlorite, chlorate, and perchlorate in hypochlorite feedstocks. Model simulations indicate chlorate and perchlorate can accumulate under realistic dosing conditions and can be managed with less concentrated feedstocks and climate-controlled storage. Second, we review the formation pathways of dichloramine and chloronitramide anion. Chloronitramide anion accumulation may be mitigated by increasing monochloramine stability and quenching reactive nitrogen species in its formation pathway.

Deterministic Methods To Improve The Field-Of-View For Direction Finding Using Sparse Digital Arrays, Nolan J. Egging

Master's Theses

Direction finding algorithms are used with digital phased arrays to determine the incoming angle of arrival (AoA) of an incident signal. These algorithms, and direction finding as a whole, have a wide range of civilian and military applications from radar, electronic reconnaissance, mobile communication, et cetera. However, for situations where the spacing between antenna elements needs to be large, gating lobes appear in the radiation pattern of analog arrays. This work demonstrates that for digital beamforming algorithms, the field of view (FoV) of a uniform linear digital array matches the grating lobe free range of a similarly spaced analog array. …

Development And Test Of An Automatic Mass Balancing System For Cal Poly's Spacecraft Attitude Dynamics Simulator, Cameron B. Zorio

Master's Theses

The Cal Poly Spacecraft Attitude Dynamics Simulator (SADS) is an ongoing project to develop an air-bearing platform capable of recreating on-orbit rotational dynamics with near frictionless and torque-free rotations. However, any offset between the platform's center of rotation and its center of mass will introduce a torque due to gravity.

This thesis presents the design, implementation, and experimental evaluation of a low-cost, automatic mass balancing system for the SADS to address this challenge. A new modular sliding mass system was developed that overcomes issues faced in previous iterations of the SADS, providing real-time positional control of the masses and a …

Using Hydraulic And Hydrologic Modeling To Determine Scour At Toro Creek Under Climate Change Conditions, Gabriel E. Alaniz

Master's Theses

ABSTRACT

This study evaluates bridge scour at the Toro Creek crossing of Highway 1 in Morro Bay, California, under present conditions and future climate conditions with more frequent extreme rainfall events. California infrastructure is becoming increasingly vulnerable to extreme storm events and increased intense precipitation events brought by climate change. This analysis focuses on the calculation of scour for both the northbound and southbound spans. Highway 1 plays a vital role in California’s coastal transportation infrastructure by carrying more than 20,000 vehicles daily (Caltrans, 2017). In this thesis, a hydrological model (HEC-HMS) is used to simulate runoff under present-day and …

Curvilinear Image Segmentation Using Multiscale Variational U-Net, Rebekah Fortes

LSU New Orleans Theses and Dissertations

Segmentation of curvilinear structures such as water contours, cracks in cement, and vascular networks in biomedical imaging, poses unique challenges due to extreme class imbalance, irregular morphology, low contrast against complex backgrounds, and the need to preserve global connectivity while detecting fine-scale details. We propose a Multiscale Variational U-Net (MSVU-Net) architecture designed specifically to address these challenges. The model integrates multiscale convolutional filters to capture both global context and local detail, while embedding a variational model in the bottleneck layer to enhance structural representation. To mitigate class imbalance and improve fidelity, the network optimizes a hybrid loss function that combines …

G2pdeep-V2: A Web-Based Deep-Learning Framework For Phenotype Prediction And Biomarker Discovery For All Organisms Using Multi-Omics Data, Shuai Zeng, Trinath Adusumilli, Sania Zafar Awan, Manish Sridhar Immadi, Dong Xu, Trupti Joshi

Biomedical Sciences

Multi-omics data offers rich insights into complex traits across organisms, yet integrating and analyzing these datasets for phenotype prediction and marker discovery remains challenging. Researchers need accessible tools that combine deep learning, hyperparameter optimization, visualization, and downstream analysis in a unified web platform. To address this, we developed G2PDeep-v2, a web-based platform powered by deep learning for phenotype prediction and marker discovery from multi-omics data across a wide range of organisms, including humans and plants. The server provides multiple services for researchers to create deep-learning models through an interactive interface and train these models using an automated hyperparameter tuning algorithm …

Development And Validation Of A Thermal Model For An Electric Vehicle Transmission, Ghazal Rajabikhorasani

Dissertations

This research investigates the thermal behavior of a high-speed electric vehicle (EV) helical gearbox with the goal of improving the prediction accuracy of component temperatures and total power losses under a range of operating conditions. The study focuses on developing a physics-based lumped-parameter thermal network model capable of capturing the main heat generation and dissipation mechanisms within the transmission. The model integrates experimentally validated loss correlations for gears, bearings, seals, and churning, as well as convective and radiative heat transfer paths.

The thermal network model was coded in MATLAB and validated through a series of controlled experiments performed on an …

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 …

The Comparison Of Dixon–Mood And 1/Nf Methods For Fatigue Limit Estimation Of 17–4 Ph Stainless Steel (H900), Arthur Pallar Pallar

Masters Theses

This study compares two methods for estimating the fatigue limit of 17-4 PH stainless steel (H900): the Dixon–Mood staircase and Kujawski 1/Nf linear method. Tests were conducted on an MTS Acumen 3 kN system under axial tension–tension loading at R = 0.1 and 50 Hz, following the standard practice defined in ASTM E466-15. Flat specimens were fabricated by water-jet cutting and polished. Tensile tests verified mechanical properties consistent with published data for the H900 condition. Fifteen specimens tested by the staircase method yielded a mean fatigue limit of 1138 MPa. The 1/Nf analysis using four specimens produced 1159 MPa, 2 …

Evaluating Psychosocial Stressors And Mental Well-Being Of Construction Professionals From The Management Standpoint: An Exploratory Study, Md Tauhidul Karim

Masters Theses

Construction professionals face persistent workplace stressors that undermine their mental well-being outcomes. Despite progress in general job-related stressors, social and interpersonal aspects of psychosocial stressors traditionally remain underexplored in the construction management research. The present study examines how social and interpersonal factors influence construction workers’ mental well-being and how management’s awareness, responsiveness, and strategic roles evolved in the transition of the COVID-19 pandemic at the organizational level. An integrative mixed-methods approach was employed, combining a systematic literature review, a bibliometric analysis, and an exploratory case study to capture the current landscape of mental well-being and management standpoints in the US …

Extremum-Seeking Approach For Real-Time Self-Healing Of Position Sensor Offset Error In Non-Salient Pmsms, Ramitha Kalhara Dissanayake Ralalage

Masters Theses

The inherent advantages of permanent magnet synchronous machines (PMSMs), such as high efficiency, has led to their frequent use in industry, including safety-critical applications, such as transportation electrification. The accurate measurement of the rotor position is key to achieving efficient and reliable field-orientation-based torque regulation. With the high reliance on the rotor position measurement, position sensor fault diagnosis and mitigation facilitate a layer of safety. Conventional methods for compensating position sensor offset errors in electric drives typically depend on accurate knowledge of motor parameters. However, these parameters are often subject to variation due to temperature changes, system aging, and other …

Design, Optimization, And Initial Results Of An Automatic Impedance Matching Network For Nitrogen Inductively Coupled Plasma, Logan Anthony Alvesteffer

Masters Theses

The electric propulsion industry is witnessing a strategic interest toward the utilization of molecular propellants as alternatives to noble gases due to increasing cost constraints and logistical requirements. This transition is hindered by a fundamental deficiency in the understanding of molecular plasma and radio frequency physics, including the excitation, dissociation, and ionization cross-sections, which mandates a reliance on computationally inefficient, empirically modified atomic thruster designs. Furthermore, current state-of-the-art electric propulsion devices, such as gridded ion thrusters and Hall effect thrusters, utilize an electrode (cathode) for ionization and are thus susceptible to chemical poisoning and material erosion, which is prevalent while …

Local Hydrodynamics And Phase Distribution In Large-Scale Trickle Bed Reactors Using Multi-Detector Γ-Ray Densitometry, Sebastián Uribe, Ahmed Jasim, Saba A. Gheni, Nora Selem, Nouhaila Filali, Tiberiu M. Leib, Sourav Sengupta, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

This study presents a new approach of using gamma ray computed tomography (CT) in a form of arc multi-detector γ-Ray Densitometry (Arc MD-GRD) Technique where it measures the line averaged holdups of the phases which are projected on the diameter of the column to obtain their diameter profiles. This technique then was used to investigate the diameter profiles of the phases' holdups in a 12-inch diameter trickle bed reactor (TBR) using sulfur hexafluoride (SF6) as the gas phase to represent to a certain extent the industrial higher density of the used gas phase due to either the type of the …

Draft Genome Sequences Of Four Phosphate-Solubilizing Microbes Of The Family Burkholderiaceae Isolated From Tailings From The Former Pea Ridge Mine In Washington County, Mo, Usa, Prince Oppong Amoh, Abiodun E. Idowu, Elizabeth R. Grube, Melanie R. Mormile, Hunter W. Schroer

Biological Sciences Faculty Research & Creative Works

We present draft genome sequences of four Gram-negative phosphate-solubilizing microbes isolated from Pea Ridge Mine tailings in Missouri, USA. Belonging to the family Burkholderiaceae, these isolates exhibit a phosphate-mineral-dissolving phenotype in liquid and solid cultures. Genome sizes span 5.6–9.7 Mb, with GC contents of 61.6%–67.0%.

Realization Of Deterministic Quantum Circuits For Non-Deterministic Or Incompletely Specified Quantum State Machines, Manjith Kumar, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

In classical logic design, there are machine learning methods based on converting a set of input-output traces to non-deterministic automata that are then converted to deterministic automata and synthesized using logic gates. This approach has not yet been extended to quantum automata. In this paper, we present a method to convert a set of input-output traces to a non-deterministic automaton, which is then converted to an incompletely specified multi-output Boolean function. The existing logic synthesis approaches for designing quantum circuits are insufficient to handle incompletely specified functions. So, we present a novel algorithm to synthesize logic functions with don’t cares …

Investigating The Correlation And Synergy Of Artificial Intelligence Techniques, Construction Technologies, And Their Key Benefits, Fareed Salih, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Despite its reputation as one of the least digitized sectors, the construction industry increasingly adopts artificial intelligence (AI) and construction technologies. However, previous research has not adequately explored the benefits of AI techniques and construction technologies nor the correlations between them. This study aims to fill this knowledge gap. To this end, the authors used a multistep research methodology. First, a systematic literature review of studies published between 1985 and 2022 was conducted to identify AI techniques and construction technologies. Second, content and frequency analysis were performed to determine the benefits associated with AI and technology adoption. Finally, a survey …

Identifying Influential Assets In Higher Order Interdependent Infrastructure Networks Through Population Impact, Akshat Chulahwat, Emad M. Hassan, Mersedeh Tariverdi, Miguel Nunez-Del-Prado, Hussam Mahmoud

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

A significant increase in catastrophic events worldwide has had a disastrous impact on the built environment, as these disruptive events devastate critical infrastructure lifelines, resulting in a substantial reduction of services across a community. Management of critical infrastructure assets is essential, and this can be achieved by optimal resource allocation to key assets within interconnected systems. The majority of current literature focuses on capturing the behavior of infrastructure systems individually, which presents a computational problem when dealing with complex, interdependent infrastructure systems. In this study, a comprehensive framework to evaluate a type of influence metric for ranking node and edge …

Evaluating Crumb Rubber Modified (Crm) Asphalt As A Sustainable Binder Alternative For High-Friction Surface Treatments, Abdallah Aboelela, Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

High-friction surface treatments (HFSTs) are widely applied to improve pavement safety by enhancing long-term skid resistance. Although epoxy resins are commonly used due to their strength and durability, their high cost, susceptibility to delamination, incompatibility with substrates of flexible pavements, and adverse environmental concerns limit their long-term performance. This study presents crumb rubber modified (CRM) asphalt as a sustainable alternative binder for HFST applications. CRM binders offer high performance and compatibility with existing pavement surfaces, cost effectiveness and reduced environmental impacts as compared to epoxy binders. In addition, the binder development utilizes enhanced recycling technologies for interacting with used tire …

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 …

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 …

Rapid Prototyping Of Low-Cost Sensor Systems Towards A Platform For Upper Limb Posture Estimation, Russell Rathbun

Electrical Engineering and Computer Science Undergraduate Honors Theses

Physical therapy requires patients to perform repeated actions to achieve meaningful results in rehabilitation. This thesis explores production methods and various sensor systems by utilizing rapid prototyping, inertial measurement units (IMUs), and capacitive sensor arrays (CSAs). CSAs can be made from a wide ar- ray of materials and techniques including 3d printing and laser ablation–to rapidly create CSAs that can be custom fit to enable proximity, force, and touch detection. IMU and CSA systems individually are able to track upper limb movements, ges- tures, and positions. This combination of sensors enables accurate upper limb pos- ture estimation of patients. This …

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 …

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, …

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, …

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 …