Second-order analysis by variograms for curvature measures of two-phase structures

Abstract. Second-order characteristics are important in the description of various geometrical structures occurring in foams, porous media, complex fluids, and phase separation processes. The classical second order characteristics are pair correlation functions, which are well-known in the context of point fields and mass distributions. This paper studies systematically these and further characteristics from a unified standpoint, based on four so-called curvature measures, volume, surface area, integral of mean curvature and Euler characteristic. Their statistical estimation is straightforward only in the case of the volume measure, for which the pair correlation function is traditionally called the two-point correlation function. For the other three measures a statistical method is described which yields smoothed surrogates for pair correlation functions, namely variograms. Variograms lead to an enhanced understanding of the variability of the geometry of two-phase structures and can help in finding suitable models. The use of the statistical method is demonstrated for simulated samples related to Poisson-Voronoi tessellations, for experimental 3D images of Fontainebleau sandstone and for two samples of industrial foams.

[1]  Daniel A. Klain,et al.  Introduction to Geometric Probability , 1997 .

[2]  William H. Press,et al.  Numerical recipes in Fortran 90: the art of parallel scientific computing, 2nd Edition , 1996, Fortran numerical recipes.

[3]  Salvatore Torquato,et al.  Microstructure of two-phase random media.III: The n-point matrix probability functions for fully penetrable spheres , 1983 .

[4]  G. Porod,et al.  Röntgenkleinwinkelstreuung an kolloiden Systemen Asymptotisches Verhalten der Streukurven , 1962 .

[5]  R. Schneider Convex Bodies: The Brunn–Minkowski Theory: Minkowski addition , 1993 .

[6]  Schwartz,et al.  Self-diffusion in a periodic porous medium: A comparison of different approaches. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[7]  K. Mecke,et al.  Morphological fluctuations of large-scale structure: The PSCz survey , 2001 .

[8]  D Stoyan,et al.  Improved estimation of the pair correlation function of random sets , 2000, Journal of microscopy.

[9]  D Stoyan,et al.  On the estimation variance for the specific Euler–Poincaré characteristic of random networks , 2003, Journal of microscopy.

[10]  Remo Guidieri Res , 1995, RES: Anthropology and Aesthetics.

[11]  Christoph H. Arns,et al.  Virtual Materials Design: Properties of Cellular Solids Derived from 3D Tomographic Images , 2005 .

[12]  W. B. Lindquist,et al.  Pore and throat size distributions measured from synchrotron X-ray tomographic images of Fontaineble , 2000 .

[13]  Klaus Mecke,et al.  Statistical Physics and Spatial Statistics , 2000 .

[14]  C Bozzi,et al.  Measurements of CP-violating asymmetries in B0-->K(0)(s)pi(0) decays. , 2004, Physical review letters.

[15]  Nicos Martys,et al.  Virtual permeametry on microtomographic images , 2004 .

[16]  Klaus Mecke,et al.  Simulating stochastic geometries: morphology of overlapping grains , 2002 .

[17]  M. P. Levin,et al.  Numerical Recipes In Fortran 90: The Art Of Parallel Scientific Computing , 1998, IEEE Concurrency.

[18]  Adrian Sheppard,et al.  Techniques for image enhancement and segmentation of tomographic images of porous materials , 2004 .

[19]  S. Torquato Random Heterogeneous Materials , 2002 .

[20]  Keith W. Jones,et al.  Synchrotron computed microtomography of porous media: Topology and transports. , 1994, Physical review letters.

[21]  D. Marcotte Fast variogram computation with FFT , 1996 .

[22]  W. Brent Lindquist,et al.  Image Thresholding by Indicator Kriging , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  W. B. Lindquist,et al.  Investigating 3D geometry of porous media from high resolution images , 1999 .

[24]  Tim Sawkins,et al.  X-ray tomography for mesoscale physics applications , 2004 .

[25]  J. Thovert,et al.  Grain reconstruction of porous media: application to a low-porosity Fontainebleau sandstone. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[26]  S. Torquato,et al.  Random Heterogeneous Materials: Microstructure and Macroscopic Properties , 2005 .

[27]  Jean-Paul Chilbs,et al.  Geostatistics , 2000, Technometrics.

[28]  I. R. Mcdonald,et al.  Theory of simple liquids , 1998 .

[29]  Christoph H. Arns,et al.  Computation of linear elastic properties from microtomographic images: Methodology and agreement between theory and experiment , 2002 .

[30]  Nicos Martys,et al.  Transport in sandstone: A study based on three dimensional microtomography , 1996 .

[31]  S. Torquato,et al.  Reconstructing random media , 1998 .

[32]  J. T. Fredrich,et al.  3D imaging of porous media using laser scanning confocal microscopy with application to microscale transport processes , 1999 .

[33]  P-M König,et al.  Morphological thermodynamics of fluids: shape dependence of free energies. , 2004, Physical review letters.

[34]  G. Porod,et al.  Die Röntgenkleinwinkelstreuung von dichtgepackten kolloiden Systemen , 1952 .

[35]  Exact Moments of Curvature Measures in the Boolean Model , 2001 .

[36]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[37]  Klaus Mecke,et al.  Integral Geometry in Statistical Physics , 1998 .

[38]  H. R. Anderson,et al.  Scattering by an Inhomogeneous Solid. II. The Correlation Function and Its Application , 1957 .

[39]  J. Ohser,et al.  Spectral theory for random closed sets and estimating the covariance via frequency space , 2003, Advances in Applied Probability.

[40]  A. Guinier,et al.  La diffraction des rayons X aux très petits angles : application à l'étude de phénomènes ultramicroscopiques , 1939 .

[41]  D. Stoyan,et al.  Random set models in the interpretation of small‐angle scattering data , 1981 .

[42]  Christoph H. Arns,et al.  Polymeric foam properties derived from 3D images , 2004 .

[43]  L. Rayleigh The Incidence of Light upon a Transparent Sphere of Dimensions Comparable with the Wave-Length , 1910 .

[44]  Christoph H. Arns,et al.  Accurate estimation of transport properties from microtomographic images , 2001 .

[45]  S. Torquato,et al.  Computer simulation results for the two-point probability function of composite media , 1988 .

[46]  K. Ball CONVEX BODIES: THE BRUNN–MINKOWSKI THEORY , 1994 .

[47]  S. Torquato,et al.  Reconstructing random media. II. Three-dimensional media from two-dimensional cuts , 1998 .

[48]  K. Mecke,et al.  Reconstructing complex materials via effective grain shapes. , 2003, Physical review letters.

[49]  E. Glandt,et al.  Spatial correlation functions from computer simulations , 1986 .

[50]  D. Stoyan,et al.  Statistical Analysis of Simulated Random Packings of Spheres , 2002 .