Engineering Commons^™

Physics-Informed Machine Learning Methods For Inverse Design Of Multi-Phase Materials With Targeted Mechanical Properties, Yunpeng Wu

All Dissertations

Advances in machine learning algorithms and applications have significantly enhanced engineering inverse design capabilities. This work focuses on the machine learning-based inverse design of material microstructures with targeted linear and nonlinear mechanical properties. It involves developing and applying predictive and generative physics-informed neural networks for both 2D and 3D multiphase materials.

The first investigation aims to develop a machine learning method for the inverse design of 2D multiphase materials, particularly porous materials. We first develop machine learning methods to understand the implicit relationship between a material's microstructure and its mechanical behavior. Specifically, we use ResNet-based models to predict the elastic …

Fabrication And Characterization Of Lignin–Pva Hydrogels With Tunable Network Structures, Keturah Bethel

All Dissertations

The ability to directly tune the crosslinked network structure of hydrogels is crucial for their functional applications in various fields, such as water filtration, protein separation, and tissue engineering. By controlling the crosslink density of the hydrogel, one can directly alter the mesh size – i.e., the end-to-end distance between crosslink junctions – and, subsequently, directly alter the hydrogel performance. This work discusses the fabrication and characterization of soft composites containing the biopolymer, lignin, are discussed. Precisely, physically-crosslinked composite lignin–Poly(vinyl alcohol) (PVA) hydrogels were fabricated via the freeze-thaw (F/T) pathway, whereby solutions containing specified amounts of PVA and lignin were …

Advancing Unmanned Ground Vehicle Path Planning With Quantified Map Uncertainty, Israel Afriyie

All Theses

This thesis addresses the complex challenge of path planning for Unmanned Ground Vehicles (UGVs) in areas where traditional navigation systems are inadequate, such as unstructured or off-road military zones. Recognizing the limitations of current path planning algorithms, which primarily focus on optimizing for the shortest path and often fail to account for variability and risks, this research proposes an enhanced Hyperstar algorithm. This approach not only considers the fastest route but also integrates maximum delays and visibility risks into its computation, ensuring a balance between swift mission completion and concealment from adversaries.

Utilizing terrain maps and incorporating uncertainties in map …

Training Uav Teams With Multi-Agent Reinforcement Learning Towards Fully 3d Autonomous Wildfire Response, Bryce Hopkins

All Theses

As climate-exacerbated wildfires increasingly threaten landscapes and communities, there is an urgent and pressing need for sophisticated fire management technologies. Coordinated teams of Unmanned Aerial Vehicles (UAVs) present a promising solution for detection, assessment, and even incipient-stage suppression – especially when integrated into a multi-layered approach with other recent wildfire management technologies such as geostationary/polar-orbiting satellites and CCTV detection networks. However, there remains significant challenges in developing the necessary sensing, navigation, coordination, and communication subsystems that enable intelligent UAV teams. Further, federal regulations governing UAV deployment and autonomy pose constraints on real-world aerial testing, creating a disconnect between theoretical research …

Lab To Leadership: How Do Women College Stem Students’ Classroom Experiences Inform Their Leader Identity Development?, Meredith Mcdevitt

All Dissertations

This dissertation is an exploration of leader identity development and women in science, technology, engineering, and mathematics (STEM) college academic classrooms. While there continues to be research promoting diversity in STEM professions, women remain underrepresented in STEM disciplines, leadership positions, and for this specific study, the college academic classroom. This dissertation represents an opportunity for women in STEM college students to reflect on their experiences in STEM academic spaces and communities, while self-exploring factors that shape their leader identity development. The research utilized a basic qualitative research design to understand the participant’s authentic experiences within the academic environment. Conducting semi-structured …

Local Charge Distortion Due To Cr In Ni-Based Concentrated Alloys, Jacob Fischer

All Theses

Due to the presence of multiple elements consisting of a range of atomic radii, local lattice distortion (LLD) is commonly observed in concentrated (and high entropy) alloys. However, since these elements also have diverse electronegativities, recent works show that atoms can have a range of atomic charges. In this work, using density functional theory (DFT), we investigate electronic charge distribution in face centered cubic (FCC) Ni-based alloys and find significant charge-density distortion in HEAs. Specifically, Cr atoms have large charge density distortion that results in a wide range of bond lengths, atomic charges, and electronic density of states in Cr-containing …

Degradation Products And Microbial Communities Associated With The Conversion Of Five Long-Chain Fatty Acids Relevant For Anaerobic Co-Digestion Of Fog With Sludge, Claire Funk

All Theses

Anaerobic digestion is a technology that allows wastewater treatment plants to convert sludge to energy by recovering the biogas produced during the breakdown of proteins, carbohydrates, and lipids. Furthermore, adding fats, oils, and greases (FOG) through co-digestion with wastewater sludge can increase energy production as lipids have a higher methane yield than proteins and carbohydrates. However, adding FOG can also lead to operational problems in the digester due to the potential accumulation of certain long-chain fatty acids (LCFAs). Current research is limiting in the degradation pathways of prominent LCFAs in FOG and the microbial communities responsible for their degradation

The …

Hydrogen Isotope Exchange On Diffusion Pump Oils, Carson G. Allen

All Theses

The extent of isotopic exchange of deuterium and tritium with protium atoms in hydrocarbon pump oil was investigated as a means to quantify the chemical stability of a mineral oil, a silicone oil, and a polyphenyl ether oil as candidates for implementation in a diffusion pump. In its target application at a fusion power plant, a chemically stable and radiation hard oil offers substantial reductions in tritium inventory, electrical consumption, and operational pump expenses over alternate solutions for vacuum induction. Select oils were introduced to deuterium and tritium isotopes in a high temperature environment, analogous to an operating vacuum pump. …

Prompt Vs Local Redeposition: Model Refinement And Experimental Design For Understanding High-Z Net Erosion In Magnetic Confinement Fusion, Davis C. Easley

Doctoral Dissertations

The economic and engineering success of magnetic confinement fusion reactors significantly depends upon the optimization of plasma facing component (PFC) design. For high-Z PFCs, the critical engineering condition is minimal net erosion (i.e. gross erosion – redeposition). Here, we present a high-Z net erosion model discriminating three primary redeposition mechanisms: prompt (geometric-driven), local (sheath-driven), and far (scrape-off-layer-driven). Using these distinctions, we show modeling for high-Z net erosion in magnetic-confinement fusion over a matrix of key plasma parameters. With Sobol’ methods we assess the sensitivity of each mechanism and show that prompt-vs-local trade-off critically explains underprediction in redeposition losses of up …

Novel Polymer-Derived Ceramic Antennas For Hypersonic Applications, Peter J. Alley

Masters Theses

With recent advances in three dimensional [3D] printing of polymer-derived ceramics [PDCs], and the controllability of electrical continuity thereof, interest has risen in potential applications resultant from these techniques in the realm of radio communication, particularly in cases where extreme high temperatures are ambient. The following investigates the electrical properties of both insulating and conductive variants of these PDCs, the interaction between each, and the performance characteristics observed when combined using microstrip antenna design theory for high temperature applications.

Development Of A Smart Power Lab For Advanced Power Electronic Research, Joseph Lentz

Theses and Dissertations

In the pursuit of enhancing power systems efficiency, reliability, and sustainability, the establishmentof advanced research laboratories plays a pivotal role. This thesis dives into the development and integration of a cutting-edge power laboratory aimed at fostering innovation across three key domains: Electromagnetic Interference (EMI) analysis, Microgrid studies, and Energy Storage exploration. The first section focuses on the creation of an EMI laboratory tailored for the comprehensive evaluation of both radiated and conducted emissions. EMI poses significant challenges in modern electronic systems, necessitating meticulous analysis and mitigation strategies. By meticulously designing and equipping an EMI lab, researchers can gain insights into …

Deep-Learning Assisted Short-Wave Infrared Hyperspectral Imaging For Microplastic Classification, Melisa Nyakuchena

Theses and Dissertations

Microplastics are small plastics with a size between a few microns and about 5mm. Due to their small size, microplastics can be ingested by living organisms including humans, which has become a global concern and a heated area of research. Various methods have been proposed to detect and characterize microplastics. In this study, we demonstrate a hyperspectral transmission imaging system operating in the short-wave range of 1100 nm–1650nm. The developed system incorporates Fourier-transform spectroscopy (FTS) to acquire a hyperspectral data cube at high spectral resolution and signal-to-noise ratio. Using the developed system, we characterize six types of microplastic powders of …

Solving Large Job Shop Scheduling Problems: Using Graph Classification Via Graph Neural Networks To Pre-Seed A Genetic Algorithm For Machine Dispatching Rule Optimization, Isaac Schwab

Theses and Dissertations

The job shop scheduling problem is a difficult problem to solve, and it is also difficult to implement solutions found in research into real shops. In this research, a methodology is proposed to develop schedules for real shops. The methodology utilizes a genetic algorithm to select dispatching rules for each machine cell and accesses these schedules through a simulation optimization framework. The simulation framework allows for the study of random elements including variable job processing times and random machine breakdowns. This creates a robust schedule that is easy to understand, and therefore implement, while scaling to large, real-world job shops. …

Disproportionation Of Polysulfides Facilitated By A Bi-Functional Carbon Host In Li-S Batteries, Dantong Qiu

Theses and Dissertations

Lithium-sulfur (Li-S) batteries are regarded as one of the promising alternatives to conventional lithium-ion batteries (LIBs) due to their high theoretical energy density (2600 Wh kg-1), abundant resources on Earth, and low cost of sulfur. Nevertheless, several significant challenges persist in the practical application of Li-S batteries, including the insulating nature of sulfur, volume changes of cathodes, and, most critically, the shuttle effect of dissolved long-chain lithium polysulfide (PS) species during cycling. In this thesis, a novel carbon host for sulfur cathode, derived from natural silk and denoted as NC, was developed. This carbon host possesses excellent cycling performance because …

In Situ Direct-Write Materials Processing Methods In Electron Microscopes, John Lasseter

Doctoral Dissertations

Focused beam induced processing holds great promise for advanced nanoscale device design and prototyping but often has severe limitations in material quality, purity and compatibility. In particular focused electron beam induced deposition (FEBID) can create 3D nanostructures of extremely complex geometries, but the deposited material purity is often very low (< 10% metal). Ex situ functionalization processes, such as sputter coating, do not conformally coat the nanostructures but instead apply pure material from the top down. Here, a laser based photothermal coating method leveraging the geometry-dependent thermal transport properties is used to apply high-quality pure material conformally coat the exposed nanostructures and …

Enhancing Insights Into Traffic Flows And Activities: Evaluating And Exploiting Machine Learning Algorithms In Real-World Scenarios, Diyi Liu

Doctoral Dissertations

Understanding truck activities has become increasingly crucial in traffic research, considering the increase in electric vehicles, the potential failure of critical infrastructure, etc. There are many different data sources to monitor the traffic flow. In this study, four different data sets generated from different approaches are used to extract traffic information. An innovative approach is devised and implemented for each data set to get valuable insights. Chapter I improves a recent Linear Programming method to tackle the truck identification problem based on the results of the radar detector or its equivalents (e.g., single loop detector). Tested under different contexts, the …

Process-Property-Structure Relationships In Advanced Rare Earth Magnet Manufacturing: Towards Enhanced Performance And Developing Application, Kaustubh Vidyadhar Mungale

Doctoral Dissertations

This research aims to study advanced rare earth magnet manufacturing, focusing on the structure-process-property relationships that govern their performance and applications. Rare earth minerals are classified as critical materials because they are essential in manufacturing products across numerous cutting-edge technologies including electric vehicles, renewable energy systems, and high-performance electronics.

Bonded magnets are composites with permanent magnet powder embedded in a polymer matrix. Finely powdered (3-300 microns) rare earth based intermetallics such as neodymium iron boron (NdFeB) and samarium iron nitride (SmFeN) are blended with engineering polymers such as epoxy, polyamides (PA6/PA12) and polyphenylene sulfide (PPS), followed by molding the compound …

Cruising Towards Durability: Investigating Degradation In Polymer Electrolyte Fuel Cells (Pefcs) For Sustainable Vehicle Power, Preetam Sharma

Doctoral Dissertations

Energy production is central to the climate challenge, as a significant portion of greenhouse gases responsible for trapping heat in the Earth's atmosphere arises from burning fossil fuels to generate electricity and heat. To mitigate the adverse effects of climate change, emissions must be reduced by almost half by 2030 and achieve net-zero emissions by 2050. Polymer electrolyte fuel cells (PEFCs) offer numerous advantages compared to traditional internal combustion engines in vehicles. Fuel cell electric vehicles are known for their exceptional operating efficiency (over 60%), impressive driving range (more than 400 miles), and quick refueling times (under 5 minutes).

Automotive …

An Analysis To Improve Interim Final Project Cost Predictions, William C. Smolter

Doctoral Dissertations

When managing a project, a project manager is often faced with the decision to act if a project appears to be over budget. While this decision seems straightforward, for some projects this can be a costly decision that causes delays and missed deadlines or spending even more resources on analyzing individual expenses.

Currently, project management research has assumed that the project manager knows the correlation between the completed work and work remaining deterministically or it assumes that a general gaussian distribution holds and proceeds with cost projecting from there.

This research challenges this assumption by forcing varying correlation distribution curves …

A Convex Approach To Advanced Air Mobility Trajectory Optimization, Yufei Wu

Doctoral Dissertations

This dissertation addresses the challenge of real-time trajectory optimization for electric Vertical Take-Off and Landing (eVTOL) vehicles within the framework of Advanced Air Mobility (AAM). With urban airspaces becoming increasingly crowded, ensuring the safety, efficiency, and feasibility of eVTOL operations is crucial. This research primarily focuses on the development and application of convex optimization techniques to solve trajectory optimization problems that not only enhance operational capabilities but also ensure adherence to stringent safety and efficiency standards.

The study is structured into several critical analyses and methodological developments across multiple chapters. In the first chapter, I introduce a multi-phase trajectory optimization …

Hardware-Based Solutions For Improving Situational Awareness In Power Systems With High Renewable Integration, Yuru Wu

Doctoral Dissertations

This doctoral dissertation addresses the evolving challenges in power system frequency dynamics as the penetration of renewable energy sources increases, leading to a decrease in system inertia. The integration of these renewable sources, particularly those involving electronic inverters, introduces high-frequency harmonics and oscillations, necessitating enhanced accuracy and wideband measurement capabilities for effective monitoring and situation awareness in power systems.

The dissertation makes several significant contributions to this field. In Chapter 2, the dissertation introduces a review of the related literature, detailing the development and application of monitoring devices in modern power systems. Chapter 3 proposed a variety of hardware devices …

Power Controller For Insulated Solar Electric Cooker, Ryan Koshy, Justin Tae-Hoon Kim

Electrical Engineering

Insulated Solar Electric Cookers, or ISECookers, are devices created to aid those in impoverished regions improve safety, sustainability, and quality of life regarding their cooking practices. ISECookers present an alternative to traditional biofuel/biomass energy sources and provide a closed-loop, self-sustaining system that can be used in a variety of environments. These devices present solutions to widespread issues such as pollution, deforestation, and hazardous emissions as a result of traditional cooking in developing regions around the world. A notable obstacle of these devices is power delivery. Given the varying conditions experienced by a solar panel (inclement weather, irradiance irregularities, etc.), it …

Unrefined And Milled Ilmenite As A Cost-Effective Photocatalyst For Uv-Assisted Destruction And Mineralization Of Pfas, Eustace Y. Fernando, Zhiming Zhang

Henry M. Rowan College of Engineering Departmental Research

Per- and polyfluoroalkyl substances (PFAS) are fluorinated and refractory pollutants that are ubiquitous in industrial wastewater. Photocatalytic destruction of such pollutants with catalysts such as TiO2 and ZnO is an attractive avenue for removal of PFAS, but refined forms of such photocatalysts are expensive. This study, for the first time, utilized milled unrefined raw mineral ilmenite, coupled to UV-C irradiation to achieve mineralization of the two model PFAS compounds perfluorooctanoic acid (PFOA) and perfluoro octane sulfonic acid (PFOS). Results obtained using a bench-scale photocatalytic reactor system demonstrated rapid removal kinetics of PFAS compounds (>90% removal in less than 10 …

Hierarchy Of Exchange-Correlation Functionals In Computing Lattice Thermal Conductivities Of Rocksalt And Zinc-Blende Semiconductors, Jiacheng Wei, Zhonghao Xia, Yi Xia, Jiangang He

Mechanical and Materials Engineering Faculty Publications and Presentations

Lattice thermal conductivity (𝜅L) is a crucial characteristic of crystalline solids with significant implications for thermal management, energy conversion, and thermal barrier coating. The advancement of computational tools based on density functional theory (DFT) has enabled the effective utilization of phonon quasiparticle-based approaches to unravel the underlying physics of various crystalline systems. While the higher order of anharmonicity is commonly used for explaining extraordinary heat transfer behaviors in crystals, the impact of exchange-correlation (XC) functionals in DFT on describing anharmonicity has been largely overlooked. The XC functional is essential for determining the accuracy of DFT in describing interactions among electrons/ions …

Growth And Studies Of Novel Quantum Materials, Niloufar Yavarishad

Theses and Dissertations

By harnessing the extraordinary properties of quantum materials, researchers are not just conducting experiments but shaping the future of technology. Quantum materials enable the development of smaller, faster, and more efficient electronic components, potentially surpassing the physical limits of silicon-based devices. This dissertation will delve into quantum materials' electrical, optical, and thermal characteristics, specifically focusing on cadmium arsenide (Cd3As2) crystalline platelets. This topological semimetal, which is a three-dimensional analog of graphene, has potential in applications such as infrared light detection and thermoelectricity. The study also explores the possible uses of a heterojunction formed by combining bismuth selenide (Bi2Se3), a topological …

Enhancing Interactions Among Dipole Excitations Using Surface Plasmon Polaritons: Quantum Entanglement And Classical Interactions, Jay Berres

Theses and Dissertations

The interaction of light with matter at the nano-scale continues to be an important research area for the application of nano-optical devices in wide ranging areas such as biosensing, light harnessing, and optical communications, to name a few. An important aspect of this is the interaction among dipole excitations (which includes classical dipole emitters, and dipole approximations of atoms, molecules, and other quantum objects), mediated by the device medium where they are located. Since the dimensions of these devices, by design, are at the nano-scale, the size of the dipole-dipole interaction space is much less than the wavelength of light …

Crime Data Prediction Based On Geographical Location Using Machine Learning, Sai Bharath Yarlagadda

Electronic Theses, Projects, and Dissertations

This project employs machine learning methods like K Nearest Neighbors (KNN), Random Forest, Logistic Regression, and Decision Tree algorithms to monitor crime data based on location and pinpoint areas with risks. The project implements and tunes the four models to improve the precision of predicting crime levels. These models collaborate to offer a trustworthy evaluation of crime patterns. K Nearest Neighbors (KNN) categorizes locations by examining the proximity of data points considering coordinates and other factors to identify trends linked to increased crime data. Logistic Regression gauges the likelihood of crime incidents by studying the connection, between factors (like location …

Service Connect, Namrata Bomble

Electronic Theses, Projects, and Dissertations

ServiceConnect is an innovative web-based marketplace platform designed to revolutionize how local services are accessed and managed in the US. By connecting service providers and customers directly, ServiceConnect provides a simple, secure, user-friendly platform for a range of services such as home repairs, tutoring, pet care and more. Featuring convenient booking tools that increase efficiency while simultaneously building trust among both parties involved. ServiceConnect stands out with its comprehensive service range, user-friendly interface, secure payment processing and rigorous verification process for service providers. Leveraging advanced technologies like ReactJS on the frontend, Node.js & Express on the backend and MongoDB for …

Method Development For The Extraction And Analysis Of Per- And Polyfluoroalkyl Substances (Pfas) In Wastewater And Biosolids, Victoria Krull

All Graduate Theses and Dissertations, Fall 2023 to Present

Per and poly-fluorinated alkyl substances (PFAS) are manufactured chemicals that have water and grease repellant properties and do not readily biodegrade. PFAS are present in many consumer products and end up in waste systems and the environment. Studies have shown that PFAS can have adverse health effects on humans and animals.

There are many challenges to processing and analyzing samples containing PFAS including: adsorption of PFAS to equipment, contamination from equipment containing PFAS, and the high sensitivity needed to analyze for PFAS in the parts per trillion detection range. The United States Environmental Protection Agency (EPA) has been developing methods …

Microstructure-Based High Temperature Processing And Failure Analyses Of Engineering Alloys Under Complex Conditions, Dong Han

Doctoral Dissertations

From traditional petrochemical applications to contemporary manufacturing techniques, advanced structural materials are subjected to intricate thermomechanical and environmental conditions. In these engineering domains, high-temperature deformation plays a pivotal role, profoundly influencing the ultimate outcomes of industrial applications. Nevertheless, the underlying mechanisms of this deformation remain elusive, largely due to the absence of a microstructure-based mechanistic understanding of high-temperature processing and failure of materials.

This dissertation endeavors to comprehensively examine these mechanisms through computational methodologies, focusing on three quintessential topics: grain boundary cavitation failures (2 examples: stress relaxation cracking (SRC) and grain size dependence), high-temperature hydrogen attack (HTHA), and additive friction …