Physical Sciences and Mathematics Commons^™

Towards Reduced-Order Model Accelerated Optimization For Aerodynamic Design, Andrew L. Kaminsky

Doctoral Dissertations

The adoption of mathematically formal simulation-based optimization approaches within aerodynamic design depends upon a delicate balance of affordability and accessibility. Techniques are needed to accelerate the simulation-based optimization process, but they must remain approachable enough for the implementation time to not eliminate the cost savings or act as a barrier to adoption.

This dissertation introduces a reduced-order model technique for accelerating fixed-point iterative solvers (e.g. such as those employed to solve primal equations, sensitivity equations, design equations, and their combination). The reduced-order model-based acceleration technique collects snapshots of early iteration (pre-convergent) solutions and residuals and then uses them to project …

Enabling Daily Tracking Of Individual’S Cognitive State With Eyewear, Soha Rostaminia

Doctoral Dissertations

Research studies show that sleep deprivation causes severe fatigue, impairs attention and decision making, and affects our emotional interpretation of events, which makes it a big threat to public safety, and mental and physical well-being. Hence, it would be most desired if we could continuously measure one’s drowsiness and fatigue level, their emotion while making decisions, and assess their sleep quality in order to provide personalized feedback or actionable behavioral suggestions to modulate sleep pattern and alertness levels with the aim of enhancing performance, well-being, and quality of life. While there have been decades of studies on wearable devices, we …

Unobtrusive Assessment Of Upper-Limb Motor Impairment Using Wearable Inertial Sensors, Brandon R. Oubre

Doctoral Dissertations

Many neurological diseases cause motor impairments that limit autonomy and reduce health-related quality of life. Upper-limb motor impairments, in particular, significantly hamper the performance of essential activities of daily living, such as eating, bathing, and changing clothing. Assessment of impairment is necessary for tracking disease progression, measuring the efficacy of interventions, and informing clinical decision making. Impairment is currently assessed by trained clinicians using semi-quantitative rating scales that are limited by their reliance on subjective, visual assessments. Furthermore, existing scales are often burdensome to administer and do not capture patients' motor performance in home and community settings, resulting in a …

Synthesis And Assembly Of Polymer Materials At Interfaces, Xiaoshuang Wei

Doctoral Dissertations

The overarching goal of the thesis is to understand growth and assembly of polymer materials at interfaces. Chapter 2 and Chapter 3 study simultaneous polymer growth and assembly at fluid interfaces, where in-situ photopolymerization and vapor phase deposition were utilized to grow polymers, respectively. Chapter 4 leverages capillary condensation to pattern polymer growth at solid substrates. Chapter 1 provides background information on polymer materials at interfaces, and vapor phase deposition method (initiated chemical vapor deposition, iCVD) to grow polymers. This chapter also reviews polymer thin film wetting, and colloidal assemblies at interfaces. In Chapter 2, we demonstrate the preparation …

Frontiers In The Self-Assembly Of Charged Macromolecules, Khatcher O. Margossian

Doctoral Dissertations

The self-assembly of charged macromolecules forms the basis of all life on earth. From the synthesis and replication of nucleic acids, to the association of DNA to chromatin, to the targeting of RNA to various cellular compartments, to the astonishingly consistent folding of proteins, all life depends on the physics of the organization and dynamics of charged polymers. In this dissertation, I address several of the newest challenges in the assembly of these types of materials. First, I describe the exciting new physics of the complexation between polyzwitterions and polyelectrolytes. These materials open new questions and possibilities within the context …

Hyperspectral Unmixing: A Theoretical Aspect And Applications To Crism Data Processing, Yuki Itoh

Doctoral Dissertations

Hyperspectral imaging has been deployed in earth and planetary remote sensing, and has contributed the development of new methods for monitoring the earth environment and new discoveries in planetary science. It has given scientists and engineers a new way to observe the surface of earth and planetary bodies by measuring the spectroscopic spectrum at a pixel scale. Hyperspectal images require complex processing before practical use. One of the important goals of hyperspectral imaging is to obtain the images of reflectance spectrum. A raw image obtained by hyperspectral remote sensing usually undergoes conversion to a physical quantity representing the intensity of …

Enabling Nanoimprint Lithography Techniques Across Multiple Manufacturing Processes, Vincent Einck

Doctoral Dissertations

Advanced nanooptics in the areas of flat lenses, diffractive elements, and tunable emissivity require a route to high throughput manufacturing. Nanooptics are often demanding of high refractive index materials, nanometer precision and ease of fabrication. Nanoimprint lithography (NIL) is a low-cost, high throughput manufacturing technique beginning to be realized in commercial industry.^1,2 The NIL process is an ideal manufacturing candidate due to its ability to have a fast process time, efficient use of materials, repeatability and high precision while also having wide diversity of potential structures and material choices. Appling NIL techniques to other facets of manufacturing enable the …

Functional Bottlebrush Polymer Additives For Thin Films And Coatings, Travis S. Laws

Doctoral Dissertations

Bottlebrush polymers are a class of highly branched polymers consisting of polymeric side chains that are densely grafted to a linear backbone. Their highly branched architecture results in surface enrichment across a broad range of materials. The goal of my research has been centered around the design of functional bottlebrush polymers and their use as surface active additives in blend films and coatings.

In the first chapter, we examine the segregation behavior of polystyrene bottlebrushes that are blended with linear polystyrene. We systematically vary the lengths of the bottlebrush backbone (Nb), side-chain (Nsc), and the linear matrix (Nm) in order …

How Dynamic Bond Results In The Unique Viscoelastic Behavior Of The Associating Polymers, Sirui Ge

Doctoral Dissertations

Associating polymer is a special kind of polymer possessing transient reversible bonds in addition to the conventional covalent bonds. The reversible bonds provide unique dynamics and fascinating viscoelastic properties, resulting in attractive applications for these polymers, such as self-healing and shape memory materials. Despite many years of studies, the understanding of dynamics of polymers with reversible bonds, especially on molecular level, is still in the rudimentary stage, preventing the rational design of the potential novel functional materials based on associating polymers. In this dissertation, we provide a detailed and quantitative understanding of the dynamics and viscoelastic properties of associating polymers. …

Polynorbornenes For Advanced Applications And Processes, Xinyi Wang

Doctoral Dissertations

Polynorbornenes have dramatically different properties and various applications depending on their chemical structures. The modular nature of norbornene-based systems provides a facile route toward synthesizing diverse polymeric materials, thus making them ideal materials for systematic structure-property investigations. Herein, their application as gas separation membranes and the correlation between their gas-transport properties and polymer structures will be investigated. Though many valuable correlations between gas-permeability and polynorbornene structure have been studied previously, many of these efforts have focused heavily on designing materials with various chemical structures to achieve high permeabilities. In contrast, the influence of molecular structure on: a) polynorbornene chain packing …

Direct Calculation Of Configurational Entropy: Pair Correlation Functions And Disorder, Clifton C. Sluss

Doctoral Dissertations

Techniques such as classical molecular dynamics [MD] simulation provide ready access to the thermodynamic data of model material systems. However, the calculation of the Helmholtz and Gibbs free energies remains a difficult task due to the tedious nature of extracting accurate values of the excess entropy from MD simulation data. Thermodynamic integration, a common technique for the calculation of entropy requires numerous simulations across a range of temperatures. Alternative approaches to the direct calculation of entropy based on functionals of pair correlation functions [PCF] have been developed over the years. This work builds upon the functional approach tradition by extending …

Remote Sensing Of High Latitude Rivers: Approaches, Insights, And Future Ramifications, Merritt E. Harlan

Doctoral Dissertations

High latitude rivers across the pan-Arctic domain are changing due to changes in climate and positive Arctic feedback loops. Understanding and contextualizing these changes is challenging due to a lack of data and methods for estimating and modeling river discharge, and mapping rivers. Remote sensing, and the availability of satellite imagery can provide ways to overcome these challenges. Through combining various forms of fieldwork, modeling, deep learning, and remote sensing, we contribute methodologies and knowledge to three key challenges associated with better understanding high latitude rivers. In the first chapter, we combine field data that can be rapidly deployed with …

Models And Machine Learning Techniques For Improving The Planning And Operation Of Electricity Systems In Developing Regions, Santiago Correa Cardona

Doctoral Dissertations

The enormous innovation in computational intelligence has disrupted the traditional ways we solve the main problems of our society and allowed us to make more data-informed decisions. Energy systems and the ways we deliver electricity are not exceptions to this trend: cheap and pervasive sensing systems and new communication technologies have enabled the collection of large amounts of data that are being used to monitor and predict in real-time the behavior of this infrastructure. Bringing intelligence to the power grid creates many opportunities to integrate new renewable energy sources more efficiently, facilitate grid planning and expansion, improve reliability, optimize electricity …

Improving The Programmability Of Networked Energy Systems, Noman Bashir

Doctoral Dissertations

Global warming and climate change have underscored the need for designing sustainable energy systems. Sustainable energy systems, e.g., smart grids, green data centers, differ from the traditional systems in significant ways and present unique challenges to system designers and operators. First, intermittent renewable energy resources power these systems, which break the notion of infinite, reliable, and controllable power supply. Second, these systems come in varying sizes, spanning over large geographical regions. The control of these dispersed and diverse systems raises scalability challenges. Third, the performance modeling and fault detection in sustainable energy systems is still an active research area. Finally, …

X-Band Phased-Array Weather-Radar Polarimetry Testbed, William Heberling Iv

Doctoral Dissertations

Phased-array weather radar have potential to replace reflector dish radar in major weather radar networks such as NEXRAD, providing faster update times and greater scan flexibility. However, the use of electronic scanning introduces polarization errors on weather radar measurables, requiring polarimetric bias calibration. The sources of polarimetric bias have been described theoretically, but experimental verification is still limited. Additionally, no standard method of calibration for polarimetric bias exists for phased-arrays. Therefore, the University of Massachusetts Amherst (UMass) presents a fully operational X-Band phased-array weather radar polarimetric testbed. The testbed evaluates the calibration of a planar dual-polarization X-band phased-array radar through …

Tokamak 3d Heat Load Investigations Using An Integrated Simulation Framework, Thomas Looby

Doctoral Dissertations

Reactor class nuclear fusion tokamaks will be inherently complex. Thousands of interconnected systems that span orders of magnitude in physical scale must operate cohesively for the machine to function. Because these reactor class tokamaks are all in an early design stage, it is difficult to quantify exactly how each subsystem will act within the context of the greater systems. Therefore, to predict the engineering parameters necessary to design the machine, simulation frameworks that can model individual systems as well as the interfaced systems are necessary. This dissertation outlines a novel framework developed to couple otherwise disparate computational domains together into …

Model Based Force Estimation And Stiffness Control For Continuum Robots, Vincent A. Aloi

Doctoral Dissertations

Continuum Robots are bio-inspired structures that mimic the motion of snakes, elephant trunks, octopus tentacles, etc. With good design, these robots can be naturally compliant and miniaturizable, which makes Continuum Robots ideal for traversing narrow complex environments. Their flexible design, however, prevents us from using traditional methods for controlling and estimating loading on rigid link robots.

In the first thrust of this research, we provided a novel stiffness control law that alters the behavior of an end effector during contact. This controller is applicable to any continuum robot where a method for sensing or estimating tip forces and pose exists. …

Design And Development Of The Urban Population Health Observatory To Improve Disease Surveillance And Response, Whitney Brakefield

Doctoral Dissertations

Chronic and infectious diseases have a profound impact on the quality and length of life of populations that suffer from these conditions. Scientists, physicians, and health officials are seeking innovative approaches to decrease the morbidity and mortality of deadly diseases. Incorporating artificial intelligence and data science techniques across the health science domain could improve disease surveillance, intervention planning, and policymaking. In this dissertation, we describe the design and development of the Urban Population Health Observatory (UPHO), an explainable knowledge-based multimodal big data analytics platform. A common challenge for conducting multimodal big data analytics is integrating multidimensional heterogeneous data sources, which …

Chiral Mesogen-Free Liquid Crystalline Polyethers With Sulfonylated Side Chains And Patchy Brush Nanoparticles, Caleb A. Bohannon

Doctoral Dissertations

Ferroelectric liquid crystalline polymers (LCPs) hold promise for various applications driven by low electric fields, e.g., electrocaloric materials, because of the higher molecular motion in the liquid crystalline (LC) state. However, traditional chiral smectic C (SmC*) LCPs exhibit small spontaneous polarizations due to the bulky aromatic mesogens and weak polar groups. This dissertation research is focused on the design of mesogen-free sulfonylated LCPs with a goal of seeking the ferroelectric SmC* phase. Such LCPs are expected to exhibit high polarizations owing to the sulfonyl’s large dipole moment. A series of poly(oxypropylene)s (POPs), with chirality being introduced into either the backbone …

A High Rate Pixelated Neutron Detector For Neutron Reflectometry At The Spallation Neutron Source, Su-Ann Chong

Doctoral Dissertations

This work presents the development of a high-rate 6Li-based pixelated neutron detector for neutron reflectometry instruments at the Spallation Neutron Source (SNS), Oak Ridge National Laboratory. The current detector technology falls short on the instrument requirements, particularly on the counting rate capability. This detector was designed specifically to overcome the limitation in counting rate by having a fully pixelated design from neutron conversion layer to photodetector and readout system. For the neutron converting layer, a 6Li-based neutron scintillator was used. Each scintillator element was coupled to a photodetector, in this case, a silicon photomultiplier (SiPM). The output of each SiPM …

Modeling Chain Packing In Complex Phases Of Self-Assembled Block Copolymers, Anugu Abhiram Reddy

Doctoral Dissertations

Block copolymer (BCP) melts undergo microphase seperation and form ordered soft matter crystals with varying domain shapes and symmetries. We study the con- nection between diblock copolymer molecular designs and thermodynamic selection of ordered crystals by modeling features of variable sub-domain geometry filled with individual blocks within non-canonical sphere-like and network phases that together with layered, cylindrical and canonical spherical phases forms “natural forms” of self- assembled amphiphilic soft matter at large. First, we present a model to revise our understanding of optimal Frank-Kasper sphere-like morphologies by advancing the- ory to account for varying domain volumes. We then develop generic …

Moving Polygon Methods For Incompressible Fluid Dynamics, Chris Chartrand

Doctoral Dissertations

Hybrid particle-mesh numerical approaches are proposed to solve incompressible fluid flows. The methods discussed in this work consist of a collection of particles each wrapped in their own polygon mesh cell, which then move through the domain as the flow evolves. Variables such as pressure, velocity, mass, and momentum are located either on the mesh or on the particles themselves, depending on the specific algorithm described, and each will be shown to have its own advantages and disadvantages. This work explores what is required to obtain local conservation of mass, momentum, and convergence for the velocity and pressure in a …

Decision-Analytic Models Using Reinforcement Learning To Inform Dynamic Sequential Decisions In Public Policy, Seyedeh Nazanin Khatami

Doctoral Dissertations

We developed decision-analytic models specifically suited for long-term sequential decision-making in the context of large-scale dynamic stochastic systems, focusing on public policy investment decisions. We found that while machine learning and artificial intelligence algorithms provide the most suitable frameworks for such analyses, multiple challenges arise in its successful adaptation. We address three specific challenges in two public sectors, public health and climate policy, through the following three essays. In Essay I, we developed a reinforcement learning (RL) model to identify optimal sequence of testing and retention-in-care interventions to inform the national strategic plan “Ending the HIV Epidemic in the US”. …

Synthesis, Fabrication, And Assembly Of Mesoscale Polymer Filaments, Dylan M. Barber

Doctoral Dissertations

Mesoscale materials, with feature sizes in the range of one hundred nanometers to tens of micrometers, are ubiquitous in Nature. In organisms, mesoscale building blocks connect the properties of underlying molecular and nanoscructures to those of macroscale, organism-scale materials through hierarchical assemblies of recurring structural motifs. The collective action of large numbers of mesoscale features can afford stunning features like the structural color of the morpho butterfly wing, calcium ion-mediated movement in muscle, and wood structures like xylem that can support enormous external compressive loads and negative internal pressure to transport nutrients throughout an organism. In synthetic systems, the design, …

Designing Nonflammable Polymers And Blends Containing Deoxybenzoin Derivatives, Elizabeth Stubbs

Doctoral Dissertations

The importance of synthetic polymers in everyday life continues to grow, owing to their societal importance for improving our standard-of-living and enabling advances spanning medicine, electronics, construction materials, transportation. While niche applications occupy a small fraction of the overall volume of polymers produced, large scale applications tend to employ lower cost materials, such as polyethylene, polypropylene, and polystyrene. In addition to environmental considerations connected to these polymerized hydrocarbons, produced in excess of 380 million tons per year worldwide, their inherent flammability creates additional requirements associated with their manufacturing and use. Societal benefits of such polymers are extensive, and thus, there …

Tailoring Interfaces And Composition For Stable And Efficient Perovskite Solar Cells, Hamza Javaid

Doctoral Dissertations

Metal halide perovskite solar cells (PSCs) have revolutionized the field of thin film photovoltaics. Within a decade, the power conversion efficiencies (PCEs) have increased at a phenomenal rate, rising from 3.8% to more than 25% in single-junction devices, moving them ahead of the current silicon-based technology. The high efficiencies of perovskite solar cells (PSCs) and their other unique properties arise from a combination of organic and inorganic components and electronic-ionic conduction, making them excellent candidates for a plethora of applications. However, PSCs face a significant—and ironic—roadblock to commercialization: these light-harvesting materials degrade under sunlight—the very condition they would need …

Theoretical And Experimental Application Of Neural Networks In Spaceflight Control Systems, Pavel Galchenko

Doctoral Dissertations

“Spaceflight systems can enable advanced mission concepts that can help expand our understanding of the universe. To achieve the objectives of these missions, spaceflight systems typically leverage guidance and control systems to maintain some desired path and/or orientation of their scientific instrumentation. A deep understanding of the natural dynamics of the environment in which these spaceflight systems operate is required to design control systems capable of achieving the desired scientific objectives. However, mitigating strategies are critically important when these dynamics are unknown or poorly understood and/or modelled. This research introduces two neural network methodologies to control the translation and rotation …

Effects Of Vacancies And Electron Temperature On The Electron Phonon Coupling In Cubic Silicon Carbide And Their Connection To The Inelastic Thermal Spike, Salah Al-Smairat

Doctoral Dissertations

“The electron-phonon interaction is an important interaction in many solids as it influences transport phenomena and related quantities such as the electrical and thermal conductivities, especially in nuclear and space applications. The importance of the electron-phonon interaction in primary damage production in 3C-SiC is the subject of this research.

The electron-phonon coupling factor was calculated using a hybrid Density Functional Perturbation Theory - Classical Electron Gas model. The coupling factor was calculated as a function of electron temperature in pristine and defective 3C-SiC, and relaxed defective cells. The electron-phonon coupling is found to depend strongly on the electronic temperature and …

The Kanarra Fold-Thrust System -- The Leading Edge Of The Sevier Fold-Thrust Belt, Southwest Utah, William Joseph Michael Chandonia

Doctoral Dissertations

“The Jurassic to Eocene Sevier fold-thrust belt is the subject of continued scientific curiosity in tectonics, stratigraphy, and industry. Understanding its development in southwest Utah is hindered in part due to the multiple origins proposed for the Kanarra anticline, a major leading edge structure -- a drag fold along the Hurricane fault, Laramide monocline, Sevier fault propagation fold, or a combination of these -- which have confused its tectonic significance and regional context. This confusion results from the structural complexity of its exposed eastern limb, as well as displacement and burial of its crest and western limb beneath Neogene sediments …

Advances And Applications In High-Dimensional Heuristic Optimization, Samuel Alexander Vanfossan

Doctoral Dissertations

“Applicable to most real-world decision scenarios, multiobjective optimization is an area of multicriteria decision-making that seeks to simultaneously optimize two or more conflicting objectives. In contrast to single-objective scenarios, nontrivial multiobjective optimization problems are characterized by a set of Pareto optimal solutions wherein no solution unanimously optimizes all objectives. Evolutionary algorithms have emerged as a standard approach to determine a set of these Pareto optimal solutions, from which a decision-maker can select a vetted alternative. While easy to implement and having demonstrated great efficacy, these evolutionary approaches have been criticized for their runtime complexity when dealing with many alternatives or …