The Gradient Discretisation Method

The Gradient Discretisation Method
Author :
Publisher : Springer
Total Pages : 501
Release :
ISBN-10 : 9783319790428
ISBN-13 : 3319790420
Rating : 4/5 (28 Downloads)

Book Synopsis The Gradient Discretisation Method by : Jérôme Droniou

Download or read book The Gradient Discretisation Method written by Jérôme Droniou and published by Springer. This book was released on 2018-07-31 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents the Gradient Discretisation Method (GDM), which is a unified convergence analysis framework for numerical methods for elliptic and parabolic partial differential equations. The results obtained by the GDM cover both stationary and transient models; error estimates are provided for linear (and some non-linear) equations, and convergence is established for a wide range of fully non-linear models (e.g. Leray–Lions equations and degenerate parabolic equations such as the Stefan or Richards models). The GDM applies to a diverse range of methods, both classical (conforming, non-conforming, mixed finite elements, discontinuous Galerkin) and modern (mimetic finite differences, hybrid and mixed finite volume, MPFA-O finite volume), some of which can be built on very general meshes.span style="" ms="" mincho";mso-bidi-font-family:="" the="" core="" properties="" and="" analytical="" tools="" required="" to="" work="" within="" gdm="" are="" stressed,="" it="" is="" shown="" that="" scheme="" convergence="" can="" often="" be="" established="" by="" verifying="" a="" small="" number="" of="" properties.="" scope="" some="" featured="" techniques="" results,="" such="" as="" time-space="" compactness="" theorems="" (discrete="" aubin–simon,="" discontinuous="" ascoli–arzela),="" goes="" beyond="" gdm,="" making="" them="" potentially="" applicable="" numerical="" schemes="" not="" (yet)="" known="" fit="" into="" this="" framework.span style="font-family:" ms="" mincho";mso-bidi-font-family:="" this="" monograph="" is="" intended="" for="" graduate="" students,="" researchers="" and="" experts="" in="" the="" field="" of="" numerical="" analysis="" partial="" differential="" equations./ppiiiiibr/i/i/i/i/i/p


The Gradient Discretisation Method Related Books

The Gradient Discretisation Method
Language: en
Pages: 501
Authors: Jérôme Droniou
Categories: Mathematics
Type: BOOK - Published: 2018-07-31 - Publisher: Springer

DOWNLOAD EBOOK

This monograph presents the Gradient Discretisation Method (GDM), which is a unified convergence analysis framework for numerical methods for elliptic and parab
Sobolev Gradients and Differential Equations
Language: en
Pages: 287
Authors: John Neuberger
Categories: Mathematics
Type: BOOK - Published: 2009-12-01 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

A Sobolev gradient of a real-valued functional on a Hilbert space is a gradient of that functional taken relative to an underlying Sobolev norm. This book shows
Gradient Flows
Language: en
Pages: 333
Authors: Luigi Ambrosio
Categories: Mathematics
Type: BOOK - Published: 2008-10-29 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

The book is devoted to the theory of gradient flows in the general framework of metric spaces, and in the more specific setting of the space of probability meas
The Hybrid High-Order Method for Polytopal Meshes
Language: en
Pages: 552
Authors: Daniele Antonio Di Pietro
Categories: Mathematics
Type: BOOK - Published: 2020-04-03 - Publisher: Springer Nature

DOWNLOAD EBOOK

This monograph provides an introduction to the design and analysis of Hybrid High-Order methods for diffusive problems, along with a panel of applications to ad
Non-standard Discretisation Methods in Solid Mechanics
Language: en
Pages: 561
Authors: Jörg Schröder
Categories: Technology & Engineering
Type: BOOK - Published: 2022-04-14 - Publisher: Springer Nature

DOWNLOAD EBOOK

This edited volume summarizes research being pursued within the DFG Priority Programme 1748: "Reliable Simulation Methods in Solid Mechanics. Development of non