Abstract
We have seen that random heterogeneous materials exhibit a remarkably broad spectrum of rich and complex microstructures. Our focus in Part I of this book is to develop a machinery to characterize statistically this broad class of microstructures, i.e., to develop a statistical, or stochastic, geometry of heterogeneous materials. How or where does one begin to address this challenging task? The answer, of course, depends on what is the goal of the statistical characterization. Our goal is ultimately the prediction of the macroscopic or effective physical properties of the random heterogeneous material, and thus this determines our starting point. The diverse effective properties that we are concerned with in this book naturally and necessarily lead to a wide variety of microstructural descriptors, generically referred to as microstructural correlation functions. As we noted in Chapter 1, such descriptors have applicability in other seemingly disparate fields, such as cosmology (Peebles 1993, Saslaw 2000) and ecology (Pielou 1977, Diggle 1983, Durrett and Levin 1994).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer Science+Business Media New York
About this chapter
Cite this chapter
Torquato, S. (2002). Microstructural Descriptors. In: Random Heterogeneous Materials. Interdisciplinary Applied Mathematics, vol 16. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-6355-3_2
Download citation
DOI: https://doi.org/10.1007/978-1-4757-6355-3_2
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4757-6357-7
Online ISBN: 978-1-4757-6355-3
eBook Packages: Springer Book Archive