Multiscale Model Reduction

CHF 191.45
Auf Lager
SKU
IPEP1N2UFJ0
Stock 1 Verfügbar
Geliefert zwischen Do., 13.11.2025 und Fr., 14.11.2025

Details

This monograph is devoted to the study of multiscale model reduction methods from the point of view of multiscale finite element methods.
Multiscale numerical methods have become popular tools for modeling processes with multiple scales. These methods allow reducing the degrees of freedom based on local offline computations. Moreover, these methods allow deriving rigorous macroscopic equations for multiscale problems without scale separation and high contrast. Multiscale methods are also used to design efficient solvers.
This book offers a combination of analytical and numerical methods designed for solving multiscale problems. The book mostly focuses on methods that are based on multiscale finite element methods. Both applications and theoretical developments in this field are presented. The book is suitable for graduate students and researchers, who are interested in this topic.

Introduces a systemic approach to theory, computation, and applications in multi-scale finite element methods Presents an accessible summary to a wide array of researchers in mathematics, science, and engineering Combines an exposition of key concepts and constructions with practical examples

Autorentext

Eric Chung is a Professor in the Department of Mathematics and an Outstanding Fellow of the Faculty of Science at the Chinese University of Hong Kong. His research focuses on numerical discretizations of partial differential equations and the development of computational multiscale methods for challenging applications.
Yalchin Efendiev is a Professor in the Department of Mathematics at the Texas A&M University.
Thomas Y. Hou is the Charles Lee Powell Professor of Applied and Computational Mathematics at the California Institute of Technology. His research focuses on multiscale analysis and computation, fluid interface problems, and singularity formation of 3D Euler and Navier-Stokes equations.

Inhalt
Introduction.- Homogenization and Numerical Homogenization of Linear Equations.- Local Model Reduction: Introduction to Multiscale Finite Element Methods.- Generalized Multiscale Finite Element Methods: Main Concepts and Overview.- Adaptive Strategies.- Selected Global Formulations for GMsFEM and Energy Stable Oversampling.- GMsFEM Using Sparsity in the Snapshot Spaces.- Space-time GMsFEM.- Constraint Energy Minimizing Concepts.- Non-local Multicontinua Upscaling.- Space-time GMsFEM.- Multiscale Methods for Perforated Domains.- Multiscale Stabilization.- GMsFEM for Selected Applications.- Homogenization and Numerical Homogenization of Nonlinear Equations.- GMsFEM for Nonlinear Problems.- Nonlinear Non-local Multicontinua Upscaling.- Global-local Multiscale Model Reduction Using GMsFEM.- Multiscale Methods in Temporal Splitting. Efficient Implicit-explicit Methods for Multiscale Problems.- References.- Index.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783031204081
    • Lesemotiv Verstehen
    • Genre Maths
    • Auflage 2023
    • Anzahl Seiten 508
    • Herausgeber Springer International Publishing
    • Größe H241mm x B160mm x T31mm
    • Jahr 2023
    • EAN 9783031204081
    • Format Fester Einband
    • ISBN 3031204085
    • Veröffentlichung 08.06.2023
    • Titel Multiscale Model Reduction
    • Autor Eric Chung , Thomas Y. Hou , Yalchin Efendiev
    • Untertitel Multiscale Finite Element Methods and Their Generalizations
    • Gewicht 1014g
    • Sprache Englisch

Bewertungen

Schreiben Sie eine Bewertung
Nur registrierte Benutzer können Bewertungen schreiben. Bitte loggen Sie sich ein oder erstellen Sie ein Konto.
Made with ♥ in Switzerland | ©2025 Avento by Gametime AG
Gametime AG | Hohlstrasse 216 | 8004 Zürich | Schweiz | UID: CHE-112.967.470