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Titlebook: Random Heterogeneous Materials; Microstructure and M Salvatore Torquato Book 2002 Springer Science+Business Media New York 2002 Clustering.

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Monodisperse Spherese Figure 3.4). At high densities, overlapping spheres can be used to model consolidated media such as sandstones and sintered materials (Torquato 1986b). Figure 5.1 shows a distribution of identical overlapping disks at a very high density that resembles the sandstone depicted in Figure 1.3.
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Microstructural Descriptorsbook is to develop a machinery to characterize statistically this broad class of microstructures, i.e., to develop a ., ., . 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 characterizatio
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Monodisperse Spheresdentical (i.e., monodisperse) spheres of radius . Such models are not as restrictive as one might initially surmise. For example, one can vary the connectedness of the particle phase (and therefore its percolation threshold) by allowing the spheres to interpenetrate one another in varying degrees. W
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Polydisperse Spheresimportance, including composite solid propellant combustion (Kerstein 1987), sintering of powders (Rahaman 1995), colloids (Russel et al. 1989), transport and mechanical properties of particulate composite materials (Christensen 1979), and flow in packed beds (Scheidegger 1974). The effect of partic
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Anisotropic Media important class of random heterogeneous materials. Examples include stratified geological media, aligned short and long fiber composites, and laminates (Postma 1955, Dullien 1979, Christensen 1979, Adler 1992). The optimization of the properties of anisotropic media rests on a precise description o
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