Parametrized Measures and Variational Principles

Weak convergence is a basic tool of modern nonlinear analysis because it enjoys the same compactness properties that finite dimensional spaces do: basically, bounded sequences are weak relatively compact sets. Nonetheless, weak conver­ gence does not behave as one would desire with respect to nonlin...

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Bibliographic Details
Main Author: Pedregal, Pablo
Format: eBook
Language:English
Published: Basel Birkhäuser 1997, 1997
Edition:1st ed. 1997
Series:Progress in Nonlinear Differential Equations and Their Applications
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
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505 0 |a 1. Introduction -- 2. Some Variational Problems -- 3. The Calculus of Variations under Convexity Assumptions -- 4. Nonconvexity and Relaxation -- 5. Phase Transitions and Microstructure -- 6. Parametrized Measures -- 7 Analysis of Parametrized Measures -- 8. Analysis of Gradient Parametrized Measures -- 9. Quasiconvexity and Rank-one Convexity -- 10. Analysis of Divergence-Free Parametrized Measures 
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520 |a Weak convergence is a basic tool of modern nonlinear analysis because it enjoys the same compactness properties that finite dimensional spaces do: basically, bounded sequences are weak relatively compact sets. Nonetheless, weak conver­ gence does not behave as one would desire with respect to nonlinear functionals and operations. This difficulty is what makes nonlinear analysis much harder than would normally be expected. Parametrized measures is a device to under­ stand weak convergence and its behavior with respect to nonlinear functionals. Under suitable hypotheses, it yields a way of representing through integrals weak limits of compositions with nonlinear functions. It is particularly helpful in comprehending oscillatory phenomena and in keeping track of how oscilla­ tions change when a nonlinear functional is applied. Weak convergence also plays a fundamental role in the modern treatment of the calculus of variations, again because uniform bounds in norm for se­ quences allow to have weak convergent subsequences. In order to achieve the existence of minimizers for a particular functional, the property of weak lower semicontinuity should be established first. This is the crucial and most delicate step in the so-called direct method of the calculus of variations. A fairly large amount of work has been devoted to determine under what assumptions we can have this lower semicontinuity with respect to weak topologies for nonlin­ ear functionals in the form of integrals. The conclusion of all this work is that some type of convexity, understood in a broader sense, is usually involved