Stochastic Elasticity : A Nondeterministic Approach to the Nonlinear Field Theory / L. Angela Mihai

By:

Mihai, L. Angela [VerfasserIn]

Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Springer eBook Collection | Interdisciplinary applied mathematics ; Volume55Publisher: Cham : Springer, 2022Description: 1 Online-Ressource (XVII, 275 Seiten) : IllustrationenISBN:

9783031066924

Subject(s):

Additional physical formats: 9783031066917 | 9783031066931 | 9783031066948 | Erscheint auch als: 9783031066917 Druck-Ausgabe | Erscheint auch als: 9783031066931 Druck-Ausgabe | Erscheint auch als: 9783031066948 Druck-AusgabeDOI: DOI: 10.1007/978-3-031-06692-4Online resources:

Summary: 1 Introduction -- 2 Finite elasticity as prior information -- 3 Are elastic materials like gambling machines? -- 4 Elastic instabilities -- 5 Oscillatory motions -- 6 Liquid crystal elastomers -- 7 Conclusion -- Appendix A Notation -- Appendix B Fundamental concepts -- Bibliography -- Index.Summary: Stochastic elasticity is a fast developing field that combines nonlinear elasticity and stochastic theories in order to significantly improve model predictions by accounting for uncertainties in the mechanical responses of materials. However, in contrast to the tremendous development of computational methods for large-scale problems, which have been proposed and implemented extensively in recent years, at the fundamental level, there is very little understanding of the uncertainties in the behaviour of elastic materials under large strains. Based on the idea that every large-scale problem starts as a small-scale data problem, this book combines fundamental aspects of finite (large-strain) elasticity and probability theories, which are prerequisites for the quantification of uncertainties in the elastic responses of soft materials. The problems treated in this book are drawn from the analytical continuum mechanics literature and incorporate random variables as basic concepts along with mechanical stresses and strains. Such problems are interesting in their own right but they are also meant to inspire further thinking about how stochastic extensions can be formulated before they can be applied to more complex physical systems.PPN: PPN: 1815860340Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SMA | ZDB-2-SXMS

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