Variational Methods for Numerical Solution of Nonlinear Elliptic Problems

Roland Glowinski

ISBN 10: 1611973775 / ISBN 13: 9781611973778

Edité par Society for Industrial and Applied Mathematics,U.S., US, 2015

A propos de cet article

Addresses computational methods that have proven efficient for the solution of a large variety of nonlinear elliptic problems. These methods can be applied to many problems in science and engineering, but this book focuses on their application to problems in continuum mechanics and physics.This book differs from others on the topic by:Presenting examples of the power and versatility of operator-splitting methods.Providing a detailed introduction to alternating direction methods of multipliers and their applicability to the solution of nonlinear (possibly non-smooth) problems from science and engineering.Showing that nonlinear least-squares methods, combined with operator-splitting and conjugate gradient algorithms, provide efficient tools for the solution of highly nonlinear problems.

N° de réf. du vendeur LU-9781611973778

Détails bibliographiques

• Titre: Variational Methods for Numerical Solution of Nonlinear Elliptic Problems
• Éditeur: Society for Industrial and Applied Mathematics,U.S., US
• Date de parution: 2015
• Langue: anglais
• ISBN à 10 chiffres: 1611973775
• ISBN à 13 chiffres: 9781611973778
• Reliure: Paperback
• État de l'article: New

A propos de ce titre

Synopsis

The computational methods that have proven essential for the solution of a large variety of nonlinear elliptic problems are discussed in detail in this book, with particular focus on their application to problems in continuum mechanics and physics. Unlike many books on this topic, the author presents examples of the power and versatility of operator-splitting methods, as well as providing readers with a detailed introduction to alternating direction methods of multipliers and their applicability to the solution of nonlinear (possibly non-smooth) problems from science and engineering. The book also shows how nonlinear least-squares methods, combined with operator-splitting and conjugate gradient algorithms, provide efficient tools for the solution of highly nonlinear problems. Recommended for advanced graduate students and researchers in applied and computational mathematics, as well as research engineers, mathematical physicists, and systems engineers.

À propos de l?auteur

Roland Glowinski is Cullen Professor of Mathematics at the University of Houston and an Emeritus Professor of the Université Pierre et Marie Curie (Paris VI). He is a member of the French National Academy of Sciences, the French National Academy of Technology, and the Academia Europaea. He is also a Fellow of both SIAM and the AMS and past recipient of the Theodore von Kármán Prize for the notable application of mathematics to mechanics and/or the engineering sciences.