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Stochastic Modeling of Microstructures. Softcover reprint of the original 1st ed. 2001.
・ISBN 978-1-4612-6622-8 paper EUR 49.99
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| 著者・編者 | Sobczyk, Kazimierz / Kirkner, David J., |
|---|---|
| シリーズ | Modeling and Simulation in Science, Engineering and Technology |
| 出版社 | (Springer-Verlag New York Inc., US) |
| 出版年月 | 2012 |
| ページ数 | 270 pp. |
| 言語 | ENG |
| ニュース番号 | <M25-17079> |
解説
A major challenge in applied mathematics and mechanics of materials is to describe various types of material microstructures. The details of the microstructure of most natural and engineered materials are usually obscure; uncertainty and randomness are the inherent features. This complexity due to material heterogeneity has not been A major challenge in applied mathematics and mechanics of materials is to describe various types of material microstructures. The details of the microstructure of most natural and engineered materials are usually obscure; uncertainty and randomness are the inherent features. This complexity due to material heterogeneity has not been adequately described by current classical models and theories. Stochastic Modeling of Microstructures presents a concise and unified presentation of the basic principles and tools for the modeling of real materials, natural and man-made, that possess complex, random heterogeneity. The book uses the language and methods of random field theory combined with the basic constructs of stochastic geometry and geometrical/spatial statistics in order to give the reader the knowledge necessary to model various types of material microstructures. The application of the theoretical constructs reviewed in the first three chapters to the analysis of empirical data via the tools of statistical inference is also discussed. The final chapters address practical aspects of specific modeling problems. Features- u First comprehensive introduction to the comparatively new field of stochastic modeling of material microstructures u Presentation of basic tools required from the diverse subjects of random field theory, stochastic geometry and spatial statistics u Provides background concepts from probability theory and stochastic processes are provided u Applications from various fields are discussed, including stochastic wave propagation and the mechanics of