High Order Nonlinear Numerical Schemes For Evolutionary Pdes


Download High Order Nonlinear Numerical Schemes For Evolutionary Pdes PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get High Order Nonlinear Numerical Schemes For Evolutionary Pdes book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.

Download

High Order Nonlinear Numerical Schemes for Evolutionary PDEs


High Order Nonlinear Numerical Schemes for Evolutionary PDEs

Author: Rémi Abgrall

language: en

Publisher: Springer

Release Date: 2014-05-19


DOWNLOAD





This book collects papers presented during the European Workshop on High Order Nonlinear Numerical Methods for Evolutionary PDEs (HONOM 2013) that was held at INRIA Bordeaux Sud-Ouest, Talence, France in March, 2013. The central topic is high order methods for compressible fluid dynamics. In the workshop, and in this proceedings, greater emphasis is placed on the numerical than the theoretical aspects of this scientific field. The range of topics is broad, extending through algorithm design, accuracy, large scale computing, complex geometries, discontinuous Galerkin, finite element methods, Lagrangian hydrodynamics, finite difference methods and applications and uncertainty quantification. These techniques find practical applications in such fields as fluid mechanics, magnetohydrodynamics, nonlinear solid mechanics, and others for which genuinely nonlinear methods are needed.

Implicit-Explicit Methods for Evolutionary Partial Differential Equations


Implicit-Explicit Methods for Evolutionary Partial Differential Equations

Author: Sebastiano Boscarino

language: en

Publisher: SIAM

Release Date: 2024-12-12


DOWNLOAD





Implicit-explicit (IMEX) time discretization methods have proven to be highly effective for the numerical solution of a wide class of evolutionary partial differential equations (PDEs) across various contexts. These methods have become mainstream for solving evolutionary PDEs, particularly in the fields of hyperbolic and kinetic equations. The first book on the subject, Implicit-Explicit Methods for Evolutionary Partial Differential Equations provides an in-depth yet accessible approach. The authors summarize and illustrate the construction, analysis, and application of IMEX methods using examples, test cases, and implementation details; guide readers through the various methods and teach them how to select and use the one most appropriate for their needs; and demonstrate how to identify stiff terms and effectively implement high-order methods in time for a variety of systems of PDEs. Readers interested in learning modern techniques for the effective numerical solution of evolutionary PDEs with multiple time scales will find in this book a unified, compact, and accessible treatment. This book is intended for applied mathematicians, scientists, and engineers who use or are interested in learning about IMEX schemes. Readers should have some background in numerical methods for ODE systems and basic finite difference and finite volume discretization of evolutionary PDEs, along with a basic understanding of the relevant mathematical models. The book is suitable for students who have had a basic course in numerical analysis and are familiar with partial differential equations.

Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2018


Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2018

Author: Spencer J. Sherwin

language: en

Publisher: Springer Nature

Release Date: 2020-08-11


DOWNLOAD





This open access book features a selection of high-quality papers from the presentations at the International Conference on Spectral and High-Order Methods 2018, offering an overview of the depth and breadth of the activities within this important research area. The carefully reviewed papers provide a snapshot of the state of the art, while the extensive bibliography helps initiate new research directions.