Digital Commons Network^™

Computationally Modeling The Human-Structure Interaction Response Of An Occupied Cantilevered Structure, Brennan Smith

Honors Theses

There is a limited understanding of the impact that passive human occupants have on a dynamic structural system, referred to as Human-Structure Interaction (HSI). Cantilevers are naturally prone to excessive vibrations due to their long unsupported spans, and cantilevered structures such as those commonly found in the seating area of a stadium facility or concert hall are designed to support a high density of occupancy.

This study determined that HSI in cantilevered structures can be modeled using a simple two-degree-of-freedom system. The results of the model were validated by data that was collected on a small-scale laboratory structure intentionally designed …

Performance Optimization For A Scintillating Glass Electromagnetic Calorimeter At The Eic, J. Crafts, Renee H. Fatemi, T. Horn, D. Kalinkin

Physics and Astronomy Faculty Publications

The successful realization of the EIC scientific program requires the design and construction of high-performance particle detectors. Recent developments in the field of scientific computing and increased availability of high performance computing resources have made it possible to perform optimization of multi-parameter designs, even when the latter require longer computational times (for example simulations of particle interactions with matter). Procedures involving machine-assisted techniques used to inform the design decision have seen a considerable growth in popularity among the EIC detector community. Having already been realized for tracking and RICH PID detectors, it has a potential application in calorimetry designs. A …

Mathematical Formulae For Neutron Self-Shielding Properties Of Media In An Isotropic Neutron Field, Elsayed Salama, Elsayed K. Elmaghraby, Ateia W. Mahmoud, A. Elghazaly, S. A. El-Fiki

Basic Science Engineering

In the current study, an ab initio derivation of the neutron self-shielding factor to solve the complex neutron transport problem of the decrease of the neutron flux as it penetrates into a material placed in an isotropic neutron field having equal flux in all directions. The theory of steady-state neutron transport was employed, starting from Stuart’s formula, to derive simple analytical formulae based on the integral cross-section parameters. The formulae could be adopted by the user according to various variables, such as the neutron flux distribution and geometry of the simulation at hand. The concluded formulae of the self-shielding factors …

General Physics Ii - Lab Manual, David Goldberg, Peter Glass

Open Educational Resources

No abstract provided.

Ltspice Modeling For Gan-Git Hemt Including Cryogenic Temperature, Md Maksudul Hossain, Yuqi Wei, H. Alan Mantooth

Electrical Engineering Faculty Publications and Presentations

Highly efficient electrically driven avionics have led to a renewed interest in cryogenic propulsion systems with the goal of reducing carbon emission footprint. Although cryogenic converters promise better efficiency and improved power density, the successful design is incumbent upon the appropriate switching device selection and simulation-based analyses prior to initial prototyping. In this work, a datasheet-driven compact model for a gallium nitride (GaN) Gate Injection Transistor (GIT) has been proposed and implemented in LTspice, a versatile, high performance, and free circuit simulator in order to investigate the merit of the chosen device in a power electronic system.

Dynamic Exchange-Correlation Functional For Bandgap Optimization: Reparametrization And Machine Learning, Viviana Faride Dovale Farelo

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation explores predicting the physical properties of solids using first-principles methods, with a focus on Density Functional Theory (DFT). DFT uses the electronic density within a material to predict its properties, simplifying the treatment of electron-electron interactions and allowing the study of realistic systems with a balanced treatment between accuracy and computational efficiency. Additionally, machine learning (ML) is employed to create correlations between some physical properties of solids and other properties or parameters that are more difficult to calculate.

The main problem addressed in this study is adjusting the parameters in the Strongly Constrained and Appropriately Normed (SCAN) semilocal …

Processing, Stability, And High-Temperature Properties Of Doped Lacro3-Based Refractory Ceramics And Composites For Harsh Environments Sensing Applications, Javier A. Mena

Graduate Theses, Dissertations, and Problem Reports (ETD)

In order to test and monitor the operational stability and conditions of various energy, transportation, and manufacturing systems and their components, accurate sensors capable of operating at temperatures over 1000 °C in various environments for long durations are required. In addition, many of these harsh environmental systems do not permit sensors to be directly inserted into the environment, so the sensors need to be embedded into the surrounding support or thermal protective materials. Some technological and industrial applications that require the use of harsh environment conditions sensing include nuclear and chemical reactors, jet engines, heavyduty gas turbines, rotating bearings in …

Investigating Microphysical Variability And Entrainment In Clouds Using Airborne Digital Holography, Machine Learning, And Large Eddy Simulations, Nithin Allwayin

Dissertations, Master's Theses and Master's Reports

Advancing our understanding of cloud microphysics—the processes governing cloud particles' formation, growth, and interactions—is essential for accurate weather and climate modeling. In this work, we investigate how droplet size distributions vary in a cloud and explore how microphysical properties such as droplet size and number concentration respond to entrainment and mixing.

In the first part of the work, a novel algorithm is developed combining hypothesis testing with density-based clustering to identify characteristic cloud droplet size distribution types in marine stratocumulus clouds. Applied to data from the airborne Holographic Detector for Clouds (HOLODEC), the algorithm successfully identifies a relatively small set …

Interpreting Neural Operators: How Nonlinear Waves Propagate In Non-Reciprocal Solids, Jonathan Colen, Alexis Poncet, Denis Bartolo, Vincenzo Vitelli

Data Science Faculty Publications

We present a data-driven pipeline for model building that combines interpretable machine learning, hydrodynamic theories, and microscopic models. The goal is to uncover the underlying processes governing nonlinear dynamics experiments. We exemplify our method with data from microfluidic experiments where crystals of streaming droplets support the propagation of nonlinear waves absent in passive crystals. By combining physics-inspired neural networks, known as neural operators, with symbolic regression tools, we generate the solution, as well as the mathematical form, of a nonlinear dynamical system that accurately models the experimental data. Finally, we interpret this continuum model from fundamental physics principles. Informed by …

Beyond Cryptic Equations: Reimagining Concepts In Physics Through Metaheuristics And Fantasy Stories Using Neutrosophic Venn Diagram, Victor Christianto, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Physics, the grand narrative of the universe, bas long been viewed as realm of cold, hard equations. But what if we looked beyond the formulas and considered a more imaginative origin for some of its concepts? This article explores the intriguing possibility that physics, and even cosmology, might share a surprising kinship with metaheuristics and fantastical fiction.

Partial Collisions Of Unmater-Matter, Unmatter-Antimatter, And Unmatter1-Unmatter2 To Generate High Energy, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we present the possibility of partial collisions between unmatter with matter, and unmatter with antimatter, and two or more different types of unmatters colliding between themselves to create high energy. In general, the collisions between unmatter with matter, or with antimatter, or with other type of unmatter, because being partial, they release less energy than the matter-unmatter collision which is a total collision. But the unmatter may be easier to produce in laboratory than antimatter.

Ermakov Equations Can Be Derived From Zel’Dovich Pancake, And They Are Cold And Nonlocal Through Using Neutrosophic Venn Diagram, Victor Christianto, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

As we argue in a previous article, the labyrinthine worlds of Jorge Luis Borges are more than captivating narratives; they are portals to a deeper understanding of existence. By weaving elements of science-fiction fantasy with philosophical and ethical inquiries, Borges's short stories bridge the seemingly disparate realms of physics and the humanities, offering fertile ground for contemporary physics research. The present-day universe consists of galaxies, galaxy clusters, one-dimensional filaments and two-dimensional sheets or pancakes, all of which combine to form the cosmic web. The so called ”Zeldovich pancakes”, are very difficult to observe, because their overdensity is only slightly greater …

Remark On Falaco Soliton As A Tunneling Mechanism In A Navier-Stokes Universe, Victor Christianto, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

This paper is a follow up to our previous article [1] suggesting that it is possible to find tunneling time solutions for Schrodinger equation considering quasicrystalline as interstellar matter, by virtue of quasicrystalline potential. The paper also discusses the mapping of these equations to Riccati equations, a class of nonlinear differential equations. This mapping can provide insights into the behavior of the Navier-Stokes equations and may lead to new methods for solving them. The Navier-Stokes equations, a set of nonlinear partial differential equations, are fundamental in fluid mechanics. They describe the motion of viscous fluids. In three dimensions, these equations …

Plausible Photomolecular Effect And Microwave In Phase Transition Of Water As A New Dawn For Renewable Energy And Ensemble-Holistic Approach To Health Management, Victor Christianto, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Interaction among light and water molecules have baffled scientists for many decades, and even centuries. In this regards, photons in the visible spectrum, where bulk water normally doesn't absorb light, can surprisingly cleave off large water clusters from the water-vapor interface, according to a recent study by Tu and Chen (2023). This discovery, termed the "photomolecular effect," opens exciting possibilities for not only revolutionizing renewable energy but also paving the way for a more integrated-ensemble approach to health management (cf. Smarandache & Christianto, 2010; Tu & Chen, 2023; Tu et al., 2024). In a sense, other than with green or …

Bayesian Inference In Reinforcement Learning Neural Networks During A Markov Decision Processes?, Katherine Graham

Scripps Senior Theses

The predictive mind theory proposes that brains work in a way that makes predictions about future stimuli to process information efficiently and accurately. Bayesian brain theory suggests that the brain utilizes Bayesian probability models to make predictions, while the free-energy minimization hypothesis proposes that these predictions are made to minimize energy or uncertainty, ensuring accurate perceptions. Vertechi et al. (2020) explored animal participants’ utilization of stimulus-bound strategy versus inference-based strategy to solve a Markov decision process with a 2-state environment, one of which is always active. These sites have a certain probability of switching to a different site and the …

Plant Root Hair Adhesion Mediated Through Variation In Sodium Ion Concentration, Natasha Mulenga

Honors Program Theses

This study investigates the effects of sodium ion (Na+) concentration on the adhesion of Brassica Rapa root hairs using atomic force microscopy (AFM). Plant root hair adhesion to soil particles plays a crucial role in anchoring plants and facilitating nutrient uptake. Previous research has shown that calcium ions (Ca2+) cross-link pectin molecules in the cell wall, increasing rigidity and reducing adhesion. As Na+ binds to pectin without cross-linking, we expected that root hairs exposed to sodium chloride (NaCl) solutions would exhibit longer adhesive interactions and similar binding forces compared to those exposed to calcium chloride (CaCl2) solutions of equal concentrations. …

Transient Diode Laser Absorption Spectroscopy For Measuring Collisional Quenching Rates Of Co And Its Potential For Studying H2o, Jordan M. Polvere

Master’s Theses

Motivated by the necessity of non-LTE models that account for species that are not in Local Thermodynamic Equilibrium (LTE) in Titan’s and Earth’s atmospheres, collisional quenching rates of CO and H2O_(g) have been studied. Providing more accurate and precise values of collisional quenching rate coefficients is crucial in the development of more advanced atmospheric models, which are important to fields of science such as meteorology and astronomy. Rates of collisional quenching of CO(v=1,2) by CO and CO(v=2) by N₂ at approximately 301-321 K were measured by transient diode laser absorption spectroscopy. The rate coefficients of CO(v=1)-CO, CO(v=2)-CO, and …

“Zero” Porosity High Loading Nmc622 Positive Electrodes For Li-Ion Batteries, Haidar Y. Alolaywi, Kubra Uzun, Yang-Tse Cheng

Chemical and Materials Engineering Faculty Publications

LiNi0.6 Mn0.2Co0.2 O 2 (NMC622) is a widely used positive electrode material for lithium-ion batteries, including electric vehicles. In this work, we investigated the effects of porosity, ranging from “zero” to the typical 35%, on the electrochemical behavior of high- loading NMC622 electrodes. Although it is well known that the energy density of the electrode increases with increasing areal capacity and decreasing porosity, NMC-positive electrodes with exceedingly low porosity (e.g., near zero) and high loading (e.g., 4 mAh cm−2 ) have not been investigated. Here, we report an intriguing observation that the “zero porosity” NMC electrode can have higher capacity …

The Oral-Microbiome-Brain Axis: A Thorough Review On The Relationship Between Periodontitis And Alzheimer’S Disease And A Proposed Innovative Application Of Biomagnetism As A Means Of Alternative Therapy., Taha Al Hassan, Noah Al-Hassan, Maria Quiñones-Peña, Juan Lopez-Alvarenga, Seratna Guadarrama-Beltran

MEDI 9331 Scholarly Activities Clinical Years

The relationship between periodontitis and Alzheimer's disease (AD) has garnered significant attention due to the potential influence of chronic oral inflammation on neurodegenerative processes. Our hypothesis is supported by the oral-microbiome-brain axis and highlights the possibility that chronic periodontitis contributes to cognitive decline by promoting systemic inflammation and neuroinflammation, mediated by specific pathogenic microorganisms within the oral microbiome. Our findings reveal a strong association between elevated levels of Porphyromonas gingivalis and Treponema denticola, red complex bacteria, and markers of systemic inflammation, such as C-reactive protein (CRP) and pro-inflammatory cytokines. Additionally studies have demonstrated that beta amyloid plaque in rat …

Revisiting The Divergent Multipole Expansion Of Atom-Surface Interactions: Hydrogen And Positronium, Α -Quartz, And Physisorption, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

We revisit the derivation of multipole contributions to the atom-wall interaction previously presented in Łach et al. [G. Łach, M. DeKieviet, and U. D. Jentschura, Phys. Rev. A 81, 052507 (2010)10.1103/PhysRevA.81.052507]. A careful reconsideration of the angular momentum decomposition of the second-, third-, and fourth-rank tensors composed of the derivatives of the electric-field modes leads to a modification for the results for the quadrupole, octupole, and hexadecupole contributions to the atom-wall interaction. Asymptotic results are given for the asymptotic long-range forms of the multipole terms, in both the short-range and long-range limits. Calculations are carried out for hydrogen and positronium …

Robust Inverse Parameter Fitting Of Thermal Properties From The Laser-Based Angstrom Method In The Presence Of Measurement Noise Using Physics-Informed Neural Networks (Pinns), Shanmukhi Sripada, Aalok U. Gaitonde, Justin A. Weibel, Amy M. Marconnet

CTRC Research Publications

The two-dimensional laser-based Ångstrom method measures the in-plane thermal properties for anisotropic film-like materials. It involves periodic laser heating at the center of a suspended film sample and records its transient thermal response by infrared imaging. These spatiotemporal temperature data must be analyzed to extract the unknown thermal conductivity values in the orthotropic directions, an inverse parameter fitting problem. Previous demonstration of the metrology technique used a least-squares fitting method that relies on numerical differentiation to evaluate the second-order partial derivatives in the differential equation describing transient conduction in the physical system. This fitting approach is susceptible to measurement noise, …

An Exploration Of Misconceptions In Introductory Physics, Christopher Mattthew Wheatley

Graduate Theses, Dissertations, and Problem Reports (ETD)

The study of student misconceptions about physics concepts has long been an important area of inquiry in physics education research (PER). The research discussed in this dissertation builds upon the developments in PER by exploring the prevalence of consistently held undergraduate student misconceptions in introductory calculus-based physics. This thesis explores the nature of student misconceptions, mistakes, and naive answering patterns in both introductory undergraduate Newtonian mechanics and electromagnetism by applying a network analytic technique called module analysis to student responses to different concept inventories from institutions of various levels of incoming physics preparation. Each study applying these methods also demonstrates …

Design And Performance Of Superconducting Switches For Nanowire Detectors In Magnetic Fields, Timothy James Draher

Graduate Research Theses & Dissertations

Superconducting nanowire devices fit a broad spectrum of applications, including particle detection and quantum computing, and their expanding use across various fields highlights their role in the hybridization of superconducting and conventional semiconductor electronics. Despite their potential, the low signal output of these devices raises challenges in scalability and integration, particularly in applications for nuclear and high-energy physics, where resilience in magnetic fields is becoming a critical optimization factor. The superconducting nanowire cryotron (nTron) addresses these issues by providing operational gain and logic switching in superconducting nanowire circuits, demonstrating adaptability to multiple materials. This dissertation focuses on modifying the conventional …

Gan Hemt And Air Core Magnetics Based Power Converters Evaluations At Cryogenic Temperature, Yuqi Wei, Md Maksudul Hossain, H. Alan Mantooth

Electrical Engineering Faculty Publications and Presentations

Cryogenic power electronics is both advantageous and indispensable in many applications, like deep space probe, military electric vehicle, magnetic resonance imaging etc. Among different semiconductors, the gallium nitride (GaN) high electron mobility transistor (HEMT) is the most promising candidate for cryogenic applications with significant conduction loss and switching loss reductions. Moreover, there is no carrier freeze out effect for the GaN HEMTs, which is applicable in extreme low temperature operating conditions. In this work, the efficiency of GaN HEMTs based power converters with different power levels (from several Watts to several kiloWatts) are evaluated at cryogenic temperature. Three different commercial …

Higher-Derivative Quantum Field Theory And Its Implications For Hawking Radiation And Nonlocality, Gordon Kanan

Physics Dissertations - Archive

One of the fundamental equations of quantum field theory is the Klein-Gordon equation which can be constructed using irreducible representations of the Poincar ́e group and describes the dynamics of spin-0 matter. The higher derivative Klein- Gordon equations are also constructed using irreducible representations of the Poincar ́e group and are, thus, invariant under operations of this group. These higher derivative Klein-Gordon equations can be placed into two series depending on the power of the derivative, one for odd powers of the derivative and one for even powers, whose solu- tions yield timelike and spacelike fields. Applying these higher derivative …

Photoluminescence Of Beryllium-Related Defects In Gallium Nitride, Mykhailo Vorobiov, Mykhailo Vorobiov

Theses and Dissertations

This study explores the potential of beryllium (Be) as an alternative dopant to magnesium (Mg) for achieving higher hole concentrations in gallium nitride (GaN). Despite Mg prominence as an acceptor in optoelectronic and high-power devices, its deep acceptor level at 0.22 eV above the valence band limits its effectiveness. By examining Be, this research aims to pave the way to overcoming these limitations and extend the findings to aluminum nitride and aluminum gallium nitride (AlGaN) alloy. Key contributions of this work include. i)Identification of three Be-related luminescence bands in GaN through photoluminescence spectroscopy, improving the understanding needed for further material …

Frieze And Tiling Groups In The Lorentz-Minkowski Plane, Michael O. Lynch

Honors Undergraduate Theses

In this thesis, there is a presentation of the isometries from the Lorentz-Minkowski Plane and a solution to the Frieze Patterns. There is a suggestion for a solution for the Tiling Patterns. Since the construction of these mathematical structures is well understood in the Euclidean plane, one can follow a similar approach to the construction of such objects to find the unique number of groups that describe all possible frieze patterns while there is a suggestion of the number for the tiling case. There is a reflection of these results in a computational and cosmological context.

Cross-Layer Design Of Highly Scalable And Energy-Efficient Ai Accelerator Systems Using Photonic Integrated Circuits, Sairam Sri Vatsavai

Theses and Dissertations--Electrical and Computer Engineering

Artificial Intelligence (AI) has experienced remarkable success in recent years, solving complex computational problems across various domains, including computer vision, natural language processing, and pattern recognition. Much of this success can be attributed to the advancements in deep learning algorithms and models, particularly Artificial Neural Networks (ANNs). In recent times, deep ANNs have achieved unprecedented levels of accuracy, surpassing human capabilities in some cases. However, these deep ANN models come at a significant computational cost, with billions to trillions of parameters. Recent trends indicate that the number of parameters per ANN model will continue to grow exponentially in the foreseeable …

Enhance Students’ Learning Outcomes By Redesigning Individual Learning Activities Into Group Activities For Introductory Level Physics Courses, Kalani Hettiarachchilage, Neel Haldolaarachchige

Publications and Research

The evolution of science education is a dynamic process driven by advances in pedagogy, technology, and especially, our understanding of how students learn. Educators are exploring innovative teaching and learning methodologies such as active learning, incorporated technology, interdisciplinary approaches, flipped classrooms, personalized teaching, and many more. The goal of all these evolving methodologies is to empower students with not only a strong foundation in scientific knowledge but also with the skills and mindset required to thrive in the future world. By adopting these innovative approaches, educators can help students become effective problem solvers, critical thinkers, and life-learning citizens. Our focus …

Exploiting Quadratic Unconstrained Binary Optimization And Column Generation For Solving Vehicle Routing Problem With Discretized Time Windows, Krittin Phornsiricharoenphant

Chulalongkorn University Theses and Dissertations (Chula ETD)

No abstract provided.