Numerical Analysis and Computation Commons^™

(R1494) Approximate Solutions Of The Telegraph Equation, Ilija Jegdić

Applications and Applied Mathematics: An International Journal (AAM)

In this paper the initial boundary value problems for the linear telegraph equation in one and two space dimensions are considered. To find approximate solutions, a recently proposed optimization-free approach that utilizes artificial neural networks with one hidden layer is used, in which the connecting weights from the input layer to the hidden layer are chosen randomly and the weights from the hidden layer to the output layer are found by solving a system of linear equations. One of the advantages of this method, in comparison to the usual discretization methods for the two-dimensional linear telegraph equation, is that this …

Grid Homology Invariants For Singular Legendrian Links, Richard Michael Shumate

Graduate Theses and Dissertations

If $\Lambda_{1}^{\ast}$ and $\Lambda_{2}^{\ast}$ are two oriented singular Legendrian links that are Legendrian isotopic, we first construct front diagram representations of $\Lambda_{1}^{\ast}$ and $\Lambda_{2}^{\ast}$ that have a natural allowable singular gird diagram associated to them. These allowable singular grid diagrams will always correspond to singular Legendrian links. The grid Legendrian invariants, $\lambda^{\pm}$, in the nonsingular grid homology theory have a natural extension to the singular grid theory, and are natural under the newly defined singular grid moves. This gives an invariant of singular Legendrian links, and in fact, a broader class of singular links.

Modeling Cherenkov Light Detection Timing For The Very Energetic Radiation Imaging Telescope Array System, Keilan Finn Ramirez

Physics

The Very Energetic Radiation Imaging Telescope Array System (VERITAS) is an array of four 12-meter telescopes which use the Imaging Atmospheric Cherenkov Technique to conduct high-energy gamma-ray astronomy. VERITAS detects magnitude and location information associated with Cherenkov light, and uses this information to indirectly observe gamma-rays through a software reconstruction process. VERITAS also records timing information corresponding to Cherenkov light detection, and this additional information could theoretically be incorporated into the reconstruction process to improve the accuracy of gamma-ray observations. The first step to including timing information is to understand when Cherenkov light detection would be expected from a known …

(R1504) Second-Order Modified Nonstandard Runge-Kutta And Theta Methods For One-Dimensional Autonomous Differential Equations, Madhu Gupta, John M. Slezak, Fawaz K. Alalhareth, Souvik Roy, Hristo V. Kojouharov

Applications and Applied Mathematics: An International Journal (AAM)

Nonstandard finite difference methods (NSFD) are used in physical sciences to approximate solutions of ordinary differential equations whose analytical solution cannot be computed. Traditional NSFD methods are elementary stable but usually only have first order accuracy. In this paper, we introduce two new classes of numerical methods that are of second order accuracy and elementary stable. The methods are modified versions of the nonstandard two-stage explicit Runge-Kutta methods and the nonstandard one-stage theta methods with a specific form of the nonstandard denominator function. Theoretical analysis of the stability and accuracy of both modified NSFD methods is presented. Numerical simulations that …

(R1458) A New Finite Difference Scheme For High-Dimensional Heat Equation, Jafar Biazar, Roxana Asayesh

Applications and Applied Mathematics: An International Journal (AAM)

In this research‎, ‎a new second-order finite difference scheme is proposed to solve two and three- dimensional heat equation‎. Finite difference equations are determined via a discretization approach in which spatial second order partial derivatives in x and y directions are approximated simultaneously‎ while in the classic method, each spatial partial derivative is replaced by a central finite difference approximation, separately. By this new discretization scheme and also using the forward difference to the first-order time derivative, a finite difference equation is obtained for the parabolic equation. This approach is explicit and similar to other explicit approaches, an interval for …

A Parallelized And Layered Model For The Shallow-Water Equations, Alexander Stevens

All Theses

An energy- and enstrophy-conserving and optimally-dispersive numerical scheme for the shallow- water equations is accelerated through implementation in the GPU environment. Previous research showed the viability of the numerical scheme under standard shallow-water test cases, but was limited in applications by computation time constraints. We overcome these limitations by paral- lelizing the numerical computation in the GPU environment. We also extend the capabilities of the implementation to support not just a single shallow-water layer, but multiple. These improvements significantly expand the range of tests that can be used to exercise the model, and enable better understanding of the power of …

Numerical Study Of Laminar Flow In A Suddenly Expanding Channel, Murodil Madaliev

Scientific-technical journal

The article presents the results of a numerical study of the flow structure in a flat channel in the zone of its sudden expansion in the form of a ledge. The calculations are based on the numerical solution of a system of non-stationary equations using Navier-Stokes. The results of the longitudinal velocity profiles in various sections of the channel after the ledge are obtained. For the difference approximation of the initial equations, the control volume method was used, and the relationship between velocities and pressure was found using the SIMPLE procedure. For the numerical solution of this problem, the McCormack …

Optimal Design Problems With State Constraints, Nha Van Tran

LSU Doctoral Dissertations

This thesis focuses on constrained optimization problems with constraints on the state variables. When the constraints involve partial differential equations or variational inequalities, the optimization problem is also known as Mathematical Programs with Equilibrium Constraints. First, we applied active-set properties of optimal solutions to transform variational inequality constraints into partial differential equation constraints and devised an active-set method which allowed us to solve the optimization problems using the adjoint approach. We extended our approach to evolution problems with constraints on the trajectory of the state variable, such as the irreversibility condition in fracture mechanics. We implemented a gradient descent algorithm …

Understanding The Dynamics Of Human Reliance And Trust On Automation, Carlos E. Bustamante Orellana, Lucero Rodriguez Rodriguez, Jordy Cevallos Chavez, Yun Kang

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Mathematical Modelling And Simulation Using An Efficient Pinns Algorithm To Understand Spread Of Infection In Enclosed Spaces, Long Nguyen, Arkaprovo Ghosal, Rudra Nagalia, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

The Impact Of Fungicide Treatment On The Dynamics Of Cocoa Black Pod Disease, Bismark Oduro

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Modeling, Analysis And Simulation Of Covid-19 Interaction Dynamics Between Local Community In Saudi Arabia And Visiting Sub-Population, Manal Badgaish, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Mathematical Model For Understanding The Spread Of Covid-19 In Saudi Arabia With Access To Vaccination, Maha Alshabrawi

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Mathematical Modeling Of Breast Cancer Cell Mcf-7 Growths Due To Curcumin Treatments, Widodo Samyono, Hildana Assefa, Kana Kassa

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Multi-Valued Solutions For The Equation Of Motion, Darcy-Jordan Model, As A Cauchy Problem: A Shocking Event, Chandler Shimp

Master's Theses

Shocks are physical phenomenon that occur quite often around us. In this thesis we examine the occurrence of shocks in finite amplitude acoustic waves from a numerical perspective. These waves, or jump discontinuities, yield ill-behaved solutions when solved numerically. This study takes on the challenge of finding both single- and multi-valued solutions.

The previously unsolved problem in this study is the representation of the Equation of Motion (EoM) in the form of the Darcy-Jordan model (DJM) and expressed as a dimensionless IVP Cauchy problem. Prior attempts to solve have resulted only in implicit solutions or explicit solutions with certain initial …

Towards Cnl-Based Verbalization Of Computational Contracts, Inari Listenmaa, Maryam Hanafiah, Regina Cheong, Andreas Kallberg

Centre for Computational Law (2022-2025)

We present a CNL, which is a component of L4, a domain-specific programming language for drafting laws and contracts. Along with formal verification, L4’s core functionalities include natural language generation. We present the NLG pipeline and an interactive process for ambiguity resolution.

On The Application Of Principal Component Analysis To Classification Problems, Jianwei Zheng, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Principal Component Analysis (PCA) is a commonly used technique that uses the correlation structure of the original variables to reduce the dimensionality of the data. This reduction is achieved by considering only the first few principal components for a subsequent analysis. The usual inclusion criterion is defined by the proportion of the total variance of the principal components exceeding a predetermined threshold. We show that in certain classification problems, even extremely high inclusion threshold can negatively impact the classification accuracy. The omission of small variance principal components can severely diminish the performance of the models. We noticed this phenomenon in …

Fast Multipole Methods For Wave And Charge Source Interactions In Layered Media And Deep Neural Network Algorithms For High-Dimensional Pdes, Wenzhong Zhang

Mathematics Theses and Dissertations

In this dissertation, we develop fast algorithms for large scale numerical computations, including the fast multipole method (FMM) in layered media, and the forward-backward stochastic differential equation (FBSDE) based deep neural network (DNN) algorithms for high-dimensional parabolic partial differential equations (PDEs), addressing the issues of real-world challenging computational problems in various computation scenarios.

We develop the FMM in layered media, by first studying analytical and numerical properties of the Green's functions in layered media for the 2-D and 3-D Helmholtz equation, the linearized Poisson--Boltzmann equation, the Laplace's equation, and the tensor Green's functions for the time-harmonic Maxwell's equations and the …

A Fast Method For Computing Volume Potentials In The Galerkin Boundary Element Method In 3d Geometries, Sasan Mohyaddin

Mathematics Theses and Dissertations

We discuss how the Fast Multipole Method (FMM) applied to a boundary concentrated mesh can be used to evaluate volume potentials that arise in the boundary element method. If $h$ is the meshwidth near the boundary, then the algorithm can compute the potential in nearly $\Ord(h^{-2})$ operations while maintaining an $\Ord(h^p)$ convergence of the error. The effectiveness of the algorithms are demonstrated by solving boundary integral equations of the Poisson equation.

Ensemble Data Fitting For Bathymetric Models Informed By Nominal Data, Samantha Zambo

Dissertations

Due to the difficulty and expense of collecting bathymetric data, modeling is the primary tool to produce detailed maps of the ocean floor. Current modeling practices typically utilize only one interpolator; the industry standard is splines-in-tension.

In this dissertation we introduce a new nominal-informed ensemble interpolator designed to improve modeling accuracy in regions of sparse data. The method is guided by a priori domain knowledge provided by artificially intelligent classifiers. We recast such geomorphological classifications, such as ‘seamount’ or ‘ridge’, as nominal data which we utilize as foundational shapes in an expanded ordinary least squares regression-based algorithm. To our knowledge …