Simplicial Partitions With Applications To The Finite Element Method
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Simplicial Partitions with Applications to the Finite Element Method
This monograph focuses on the mathematical and numerical analysis of simplicial partitions and the finite element method. This active area of research has become an essential part of physics and engineering, for example in the study of problems involving heat conduction, linear elasticity, semiconductors, Maxwell's equations, Einstein's equations and magnetic and gravitational fields. These problems require the simulation of various phenomena and physical fields over complicated structures in three (and higher) dimensions. Since not all structures can be decomposed into simpler objects like d-dimensional rectangular blocks, simplicial partitions are important. In this book an emphasis is placed on angle conditions guaranteeing the convergence of the finite element method for elliptic PDEs with given boundary conditions. It is aimed at a general mathematical audience who is assumed to be familiar with only a few basic results from linear algebra, geometry, and mathematical and numerical analysis.
Monotone Discretizations for Elliptic Second Order Partial Differential Equations
Author: Gabriel R. Barrenechea
language: en
Publisher: Springer Nature
Release Date: 2025-03-18
This book offers a comprehensive presentation of numerical methods for elliptic boundary value problems that satisfy discrete maximum principles (DMPs). The satisfaction of DMPs ensures that numerical solutions possess physically admissible values, which is of utmost importance in numerous applications. A general framework for the proofs of monotonicity and discrete maximum principles is developed for both linear and nonlinear discretizations. Starting with the Poisson problem, the focus is on convection-diffusion-reaction problems with dominant convection, a situation which leads to a numerical problem with multi-scale character. The emphasis of this book is on finite element methods, where classical (usually linear) and modern nonlinear discretizations are presented in a unified way. In addition, popular finite difference and finite volume methods are discussed. Besides DMPs, other important properties of the methods, like convergence, are studied. Proofs are presented step by step, allowing readers to understand the analytic techniques more easily. Numerical examples illustrate the behavior of the methods.
Large-Scale Scientific Computing
This book constitutes revised selected papers from the 13th International Conference on Large-Scale Scientific Computing, LSSC 23021, which was held in Sozopol, Bulgaria, during June 7-11, 2021. The 60 papers included in this book were carefully reviewed and selected from a total of 73 submissions. The volume also includes two invited talks in full paper length. The papers were organized in topical sections as follows: Fractional diffusion problems: numerical methods, algorithms and applications; large-scale models: numerical methods, parallel computations and applications; application of metaheuristics to large-scale problems; advanced discretizations and solvers for coupled systems of partial differential equations; optimal control of ODEs, PDEs and applications; tensor and matrix factorization for big-data analysis; machine learning and model order reduction for large scale predictive simulations; HPC and big data: algorithms and applications; and contributed papers.