Variational and Potential Methods for a Class of Linear Hyperbolic Evolutionary Processes (Springer Monographs in Mathematics)

Igor Chudinovich/ Christian Constanda

ISBN 10: 1852338881 / ISBN 13: 9781852338886

Published by Springer Verlag, 2004

About this Item

1st edition. 148 pages. 9.25x6.25x0.50 inches. In Stock.

Seller Inventory # x-1852338881

Bibliographic Details

• Title: Variational and Potential Methods for a Class of Linear Hyperbolic Evolutionary Processes (Springer Monographs in Mathematics)
• Publisher: Springer Verlag
• Publication Date: 2004
• Language: English
• ISBN 10: 1852338881
• ISBN 13: 9781852338886
• Binding: Hardcover
• Condition: Brand New

About this title

Synopsis

Variational and boundary integral equation techniques are two of the most useful methods for solving time-dependent problems described by systems of equations of the form 2 ? u = Au, 2 ?t 2 where u = u(x,t) is a vector-valued function, x is a point in a domain inR or 3 R,and A is a linear elliptic di?erential operator. To facilitate a better und- standing of these two types of methods, below we propose to illustrate their mechanisms in action on a speci?c mathematical model rather than in a more impersonal abstract setting. For this purpose, we have chosen the hyperbolic system of partial di?erential equations governing the nonstationary bending of elastic plates with transverse shear deformation. The reason for our choice is twofold. On the one hand, in a certain sense this is a “hybrid” system, c- sistingofthreeequationsforthreeunknownfunctionsinonlytwoindependent variables, which makes it more unusual―and thereby more interesting to the analyst―than other systems arising in solid mechanics. On the other hand, this particular plate model has received very little attention compared to the so-called classical one, based on Kirchho?’s simplifying hypotheses, although, as acknowledged by practitioners, it represents a substantial re?nement of the latter and therefore needs a rigorous discussion of the existence, uniqueness, and continuous dependence of its solution on the data before any construction of numerical approximation algorithms can be contemplated.

About the Author

Igor Chudinovich is Professor of Mathematics at the University of Guanajuato, Mexico, and Christian Constanda is Oliphant Professor of Mathematical Sciences at the University of Tulsa, USA.