Computational fluid dynamics | Numerical differential equations
In applied mathematics, the name finite pointset method is a general approach for the numerical solution of problems in continuum mechanics, such as the simulation of fluid flows. In this approach (often abbreviated as FPM) the medium is represented by a finite set of points, each endowed with the relevant local properties of the medium such as density, velocity, pressure, and temperature. The sampling points can move with the medium, as in the to fluid dynamics or they may be fixed in space while the medium flows through them, as in the . A mixed Lagrangian-Eulerian approach may also be used. The Lagrangian approach is also known (especially in the computer graphics field) as particle method. Finite pointset methods are meshfree methods and therefore are easily adapted to domains with complex and/or time-evolving geometries and moving phase boundaries (such as a liquid splashing into a container, or the blowing of a glass bottle) without the software complexity that would be required to handle those features with . They can be useful in non-linear problems involving viscous fluids, heat and mass transfer, linear and non-linear elastic or plastic deformations, etc. (Wikipedia).
Finite Difference Method for finding roots of functions including an example and visual representation. Also includes discussions of Forward, Backward, and Central Finite Difference as well as overview of higher order versions of Finite Difference. Chapters 0:00 Intro 0:04 Secant Method R
From playlist Root Finding
From playlist ℕumber Theory
The Geometry of Finite Geometric Sums (visual proof; series)
This is a short, animated visual proof demonstrating the finite geometric for any ratio x with x greater than 1. This series (and its infinite analog when x less than 1) is important for many results in calculus, discrete mathematics, and combinatorics. #mathshorts #mathvideo #math #cal
From playlist Finite Sums
Determine Infinite Limits of a Rational Function Using a Table and Graph (Squared Denominator)
This video explains how to determine a limits and one-sided limits. The results are verified using a table and a graph.
From playlist Infinite Limits
Approximating the Jacobian: Finite Difference Method for Systems of Nonlinear Equations
Generalized Finite Difference Method for Simultaneous Nonlinear Systems by approximating the Jacobian using the limit of partial derivatives with the forward finite difference. Example code on GitHub https://www.github.com/osveliz/numerical-veliz Chapters 0:00 Intro 0:13 Prerequisites 0:3
From playlist Solving Systems of Nonlinear Equations
General Method for Integer Power Sum Formula
Calculus: We give a general method for deriving the closed formula for sums of powers of 1 through N. The technique uses the partial sum formula for geometric power series.
From playlist *** The Good Stuff ***
Cut-And-Project Quasicrystals: Patch Frequency and Moduli Spaces by Rene Rühr
PROGRAM SMOOTH AND HOMOGENEOUS DYNAMICS ORGANIZERS: Anish Ghosh, Stefano Luzzatto and Marcelo Viana DATE: 23 September 2019 to 04 October 2019 VENUE: Ramanujan Lecture Hall, ICTS Bangalore Ergodic theory has its origins in the the work of L. Boltzmann on the kinetic theory of gases.
From playlist Smooth And Homogeneous Dynamics
Self Similar Geometric Series: Sums of powers of 7 (and all integers larger than 3)
This is a short, animated visual proof demonstrating the finite geometric sum formula for any integer n with n greater than 3 (explicitly showing the cases n=7 and n=9 with k=3). This series (and its infinite analog when x less than 1) is important for many results in calculus, discrete ma
From playlist Finite Sums
Mathieu Desbrun (7/28/22): Connection-based Dimensionality Reduction
Abstract: A common and oft-observed assumption for high-dimensional datasets is that they sample (possibly with added noise) a low-dimensional manifold embedded in a high-dimensional space. In this situation, Non-linear Dimensional Reduction (NLDR) offers to find a low-dimensional embeddin
From playlist Applied Geometry for Data Sciences 2022
Geometric series: sums of powers of 8 (visual proof)
This is a short, animated (wordless) visual proof demonstrating the sums of finite geometric series of powers of 8 using cubes. #math #manim #mathvideo #calculus #mtbos #animation #theorem #pww #proofwithoutwords #visualproof #proof #iteachmath #geometricsums #series #squares #fi
From playlist Finite Sums
Ari Stern: Hybrid finite element methods preserving local symmetries and conservation laws
Abstract: Many PDEs arising in physical systems have symmetries and conservation laws that are local in space. However, classical finite element methods are described in terms of spaces of global functions, so it is difficult even to make sense of such local properties. In this talk, I wil
From playlist Numerical Analysis and Scientific Computing
Numerical Homogenization by Localized Orthogonal Decomposition (Lecture 3) by Daniel Peterseim
DISCUSSION MEETING Multi-Scale Analysis: Thematic Lectures and Meeting (MATHLEC-2021, ONLINE) ORGANIZERS: Patrizia Donato (University of Rouen Normandie, France), Antonio Gaudiello (Università degli Studi di Napoli Federico II, Italy), Editha Jose (University of the Philippines Los Baño
From playlist Multi-scale Analysis: Thematic Lectures And Meeting (MATHLEC-2021) (ONLINE)
Convergent Evolving Surface Finite Element Algorithms for Geometric Evolution Equations
Professor Christian Lubich University of Tübingen, Germany
From playlist Distinguished Visitors Lecture Series
Numerical Homogenization by Localized Orthogonal Decomposition (Lecture 1) by Daniel Peterseim
DISCUSSION MEETING Multi-Scale Analysis: Thematic Lectures and Meeting (MATHLEC-2021, ONLINE) ORGANIZERS: Patrizia Donato (University of Rouen Normandie, France), Antonio Gaudiello (Università degli Studi di Napoli Federico II, Italy), Editha Jose (University of the Philippines Los Baño
From playlist Multi-scale Analysis: Thematic Lectures And Meeting (MATHLEC-2021) (ONLINE)
Lecture 24 (CEM) -- Introduction to Variational Methods
This lecture introduces to the student to variational methods including finite element method, method of moments, boundary element method, and spectral domain method. It describes the Galerkin method for transforming a linear equation into matrix form as well as populating the global matr
From playlist UT El Paso: CEM Lectures | CosmoLearning.org Electrical Engineering
Central Difference Approximation | Lecture 61 | Numerical Methods for Engineers
How to approximate the first and second derivatives by a central difference formula. Join me on Coursera: https://www.coursera.org/learn/numerical-methods-engineers Lecture notes at http://www.math.ust.hk/~machas/numerical-methods-for-engineers.pdf Subscribe to my channel: http://www.yo
From playlist Numerical Methods for Engineers
David Corwin, Kim's conjecture and effective Faltings
VaNTAGe seminar, on Nov 24, 2020 License: CC-BY-NC-SA.
From playlist ICERM/AGNTC workshop updates