Classification and reconstruction of three-dimensional microstructures using support vector machines

Computational Materials Science

Volumn 32, Issue 2, 2005, Pages 223-239

  Sundararaghavan, Veeraraghavan ^a   Zabaras, Nicholas ^a  

^a Cornell University ^*  (United States)

Author keywords

Microstructure reconstruction; Pattern recognition; Principal component analysis; Reduced order representation; Support vector machines

Indexed keywords

COMPUTATIONAL METHODS; DATABASE SYSTEMS; GRAIN SIZE AND SHAPE; PATTERN RECOGNITION; POROSITY; PRINCIPAL COMPONENT ANALYSIS; STATISTICAL METHODS;

MICROSTRUCTURE RECONSTRUCTION; REDUCED ORDER REPRESENTATION; SUPPORT VECTOR MACHINES;

MICROSTRUCTURE;

EID: 9644278197     PISSN: 09270256     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.commatsci.2004.07.004     Document Type: Article

References (41)

1. M.S. Talukdar, O. Torsaeter, M.A. loannidis, J.J. Howard, Stochastic reconstruction, 3D characterization and network modeling of chalk, J. Petrol. Sci. Eng. 35 (1-2) (2002) 1-21.
2. A.P. Roberts, E.J. Garboczi, Elastic properties of a tungsten-silver composite by reconstruction and computation, J. Mech. Phys. Solids. 47 (1999) 2029-2055.
3. J. Fleig, J. Maier, The influence of laterally inhomogeneous contacts on the impedance of solid materials: A three-dimensional finite-element study, J. Electroceram. 1 (1) (1997) 73-89.
4. G. Dotelli, I.N. Lora, C. Schmid, C.M. Mari, Composite materials as electrolytes for solid oxide fuel cells: simulation of microstructure and electrical properties, Solid State Ionics 152-153 (2002) 509-515.
5. L.O.E. Santos, P.C. Philippi, M.C. Damiani, C.P. Fernandes, Using three-dimensional reconstructed microstructures for predicting intrinsic permeability of reservoir rocks based on a Boolean lattice gas method, J. Petrol. Sci. Eng. 35 (1-2) (2002) 109-124.
6. B. Bochenek, R. Pyrz, Reconstruction of random microstructures-a stochastic optimization problem, Comput. Mater. Sci. 31 (1-2) (2004) 93-112.
7. J.A. Quiblier, A new three-dimensional modeling technique for studying porous media, J. Colloid Interface Sci. 98 (1984) 84-102.
8. P.M. Adler, C.G. Jacquin, J.A. Quiblier, Flow in simulated porous media, Int. J. Multiphase Flow. 16 (4) (1990) 691-712.
9. R.D. Hazlett, Statistical characterization and stochastic modelling of pore networks in relation to fluid flow, Math. Geol. 29 (1997) 801-822.
10. C.L.Y. Yeong, S. Torquato, Reconstructing random media II. Three-dimensional media from two-dimensional cuts, Phys. Rev. E. 58 (1) (1998) 224-233.
11. B. Biswal, R. Hilfer, Microstructure analysis of reconstructed porous media, Physica A 266 (1999) 307-311.
12. P-E. Øren, S. Bakke, Reconstruction of Berea sandstone and pore-scale modelling of wettability effects, J. Petrol. Sci. Eng. 39 (3-4) (2003) 177-199.
13. I.F. Vasconcelos, I. Cantat, J.A. Glazier, Dynamics and topological aspects of a reconstructed two-dimensional foam time series using Potts Model on a pinned lattice, J. Comput. Phys. 192 (2003) 1-20.
14. Z. Liang, M.A. loannidis, I. Chatzis, Permeability and electrical conductivity of porous media from3D stochastic replicas of the microstructure, Chem. Eng. Sci. 55 (22) (2000) 5247-5262.
15. B. Biswal, C. Manwart, R. Hilfer, S. Bakke, P.-E. Øren, Quantitative analysis of experimental and synthetic microstructures for sedimentary rock, Physica A 273 (1999) 452475.
16. M.P. Anderson, D.J. Srolovitz, G.S. Grest, P.S. Sahni, Computer simulation of grain growth I. Kinetics, Acta Metall. 32 (5) (1984) 783-791.
17. J. Aldazabal, A. Martin-Meizoso, J.M. Martinez-Esnaola, Simulation of liquid phase sintering using the Monte-Carlo method, Mater. Sci. Eng. A 365 (1-2) (2004) 151-155.
18. S. Dumais, Using SVMs for text categorization, IEEE Intell. Syst. 13 (4) (1998) 21-23.
19. M. Pontil, A. Verri, Support vector machines for 3D object recognition, IEEE Trans. Pattern Anal. Mach. Intell. 20 (6) (1998) 637-646.
20. S. Li, J.T. Kwok, H. Zhu, Y. Wang, Texture classification using the support vector machines, Pattern Recogn. 36 (2003) 2883-2893.
21. N.J. Wittridge, R.D. Knutsen, A microtexture based analysis of the surface roughening behaviour of an aluminium alloy during tensile deformation, Mater. Sci. Eng. A 269 (1-2) (1999) 205-216.
22. G. F. Vander Voort, Metallography: principles and practice, McGraw-Hill Book Company, New York, 1984.
23. K. Mehnert, J. Ohser, P. Klimanek, Testing stereological methods for the estimation of spatial size distributions by means of computer-simulated grain structures, Mater. Sci. Eng. A 246 (1998) 207-212.
24. J. Ohser, F. Múcklich, Statistical Analysis of Microstructures in Materials Science, first ed., John Wiley and Sons, New York, 2000.
25. G.W. Milton, N. Phan-Thien, New bounds on effective elastic moduli of two-component materials, Proc. Roy. Soc. London A 380 (1982) 305-331.
26. M. Beran, J. Molyneux, Use of classical variational principles to determine bounds for the effective bulk modulus in heterogeneous media, Q. Appl. Math. 24 (1966) 107-118.
27. Z. Hashin, S. Shtrikman, A variational approach to the theory of the elastic behaviour of multi-phase materials, J. Mech. Phys. Solids. 11 (1963) 127-140.
28. J. Quintanilla, Microstructure and properties of random heterogeneous materials: A review of theoretical results, Poly. Engg. Sci. 39 (1999) 559-585.
29. S. Umekawa, R. Kotfila, O.D. Sherby, Elastic properties of a tungsten-silver composite above and below the melting point of silver, J. Mech. Phys. Solids 13 (4) (1965) 229-230.
30. M. Turk, A. Pentland, Eigenfaces for recognition, Int. J. Cogn. Neurosci. 3 (1) (1991) 71-86.
31. L. Sirovich, M. Kirby, Low-dimensional procedure for the characterization of human faces, J. Opt. Soc. Am 4 (1987) 519-524.
32. V. Sundararaghavan, N. Zabaras, A dynamic material library for the representation of single phase polyhedral microstructures, Acta Materialia 52 (14) (2004) 4111-4119.
33. V.N. Vapnik, Statistical Learning Theory, Wiley, New York, 1998.
34. C.C. Chang, C.J. Lin, LIBSVM: a library for support vector machines (2001) www.csie.ntu.edu.tw/∼cjlin/libsvm.
35. A.P. Roberts, S. Torquato, Chord-distribution functions of three-dimensional random media: Approximate firstpassage times of Gaussian processes, Phys. Rev. E. 59 (5) (1999) 4953-4963.
36. C. Manwart, R. Hilfer, Reconstruction of random media using Monte-Carlo methods, Phys. Rev. E. 59 (1999) 5596-5599.
37. C. Manwart, S. Torquato, R. Hilfer, Stochastic reconstruction of sandstones, Phys. Rev. E. 62 (2000) 893-899.
38. B. Lu, S. Torquato, N-point probability functions for a lattice model of heterogeneous media, Phys. Rev. B. 42 (7) (1990) 4453-4459.
39. E.J. Garboczi, NIST Internal Report 6269, (1998) www.ciks.cbt.nist.gov/ garboczi/, Chapter 2.
40. S. Ganapathysubramanian, N. Zabaras, On the synergy between classification of textures and process sequence selection, in: M.E. Schlesinger, (Ed), The proceedings of EPD Congress, 2004, The Minerals, Metals and Materials Society, Charlotte, 2004.
41. S. Torquato, Random heterogeneous media: microstructure and improved bounds on effective properties, Appl. Mech. Rev. 44 (1991) 37-76.