Heterogeneity Assessment Based on Average Variations of Morphological Tortuosity for Complex Porous Structures Characterization

Authors

  • Johan Chaniot IFP Energies nouvelles, Rond-point de l’échangeur de Solaize, BP 3, 69360 Solaize, France, Université de Lyon, Université Jean Monnet de Saint-Etienne, CNRS UMR 5516, Laboratoire Hubert Curien, F-42000 Saint-Etienne, France http://orcid.org/0000-0001-9646-064X
  • Maxime Moreaud IFP Energies nouvelles, Rond-point de l’échangeur de Solaize, BP 3, 69360 Solaize, France MINES ParisTech, PSL-Research University, CMM, 35 rue Saint Honoré, 77305 Fontainebleau, France https://orcid.org/0000-0002-4908-401X
  • Loic Sorbier IFP Energies nouvelles, Rond-point de l’échangeur de Solaize, BP 3, 69360 Solaize, France, https://orcid.org/0000-0001-5591-9848
  • Dominique Jeulin MINES ParisTech, PSL-Research University, CMM, 35 rue Saint Honoré, 77305 Fontainebleau, France
  • Jean-Marie Becker Université de Lyon, Université Jean Monnet de Saint-Etienne, CNRS UMR 5516, Laboratoire Hubert Curien, F-42000 Saint-Etienne, France
  • Thierry Fournel Université de Lyon, Université Jean Monnet de Saint-Etienne, CNRS UMR 5516, Laboratoire Hubert Curien, F-42000 Saint-Etienne, France

DOI:

https://doi.org/10.5566/ias.2370

Keywords:

geodesic distance transform, heterogeneity, Monte Carlo algorithms, morphological tortuosity, multi-scale porous network

Abstract

Morphological characterization of porous media is of paramount interest, mainly due to the connections between their physicochemical properties and their porous microstructure geometry. Heterogeneity can be seen as a geometric characteristic of porous microstructures. In this paper, two novel topological descriptors are proposed, based on the M-tortuosity formalism. Using the concept of geometric tortuosity or morphological tortuosity, a first operator is defined, the H-tortuosity. It estimates the average variations of the morphological tortuosity as a function of the scale, based on Monte Carlo method and assessing the heterogeneity of porous networks. The second descriptor is an extension, named the H-tortuosity-by-iterativeerosions, taking into account different percolating particle sizes. These two topological operators are applied on Cox multi-scale Boolean models, to validate their behaviors and to highlight their discriminative power.

References

Adler PM (1992). Porous media: geometry and

transports. Butterworth-Heineman, Boston, MA,

Adler PM, Thovert J-F (1998). Real porous media:

Local geometry and macroscopic properties. Appl

Mech Rev 51(9):537–585.

Baddeley A, Jensen EBV (2004). Stereology for

statisticians. Mg Stat Pro 103:03.

Balberg I, Anderson CH, Alexander S, Wagner N

(1984). Excluded volume and its relation to the

onset of percolation. Phys Rev B 30(7):3933.

Barman S, Rootzén H, Bolin D (2019). Prediction

of diffusive transport through polymer films from

characteristics of the pore geometry. AIChE J

(1), 446–57.

Batista ATF, Baaziz W, Taleb A-L, Chaniot J,

Moreaud M, Legens C, Aguilar-Tapia A, Proux

O, Hazemann J-L, Diehl F, Chizallet C, Gay A-S,

Ersen O, Raybaud P (2020). Atomic scale insight

into the formation, size and location of platinum

nanoparticles supported on g-alumina. ACS Catal

(7):4193–204.

Berrocal CG, Löfgren I, Lundgren K, Görander N,

Halldén C (2016). Characterisation of bending

cracks in R/FRC using image analysis. Cement

Concrete Res 90:104–16.

Bini F, Pica A, Marinozzi A, Marinozzi F (2019).

A 3D Model of the Effect of Tortuosity and

Constrictivity on the Diffusion in Mineralized

Collagen Fibril. Sci Rep-UK 9(1):2658.

Borgefors G (1986). Distance transformations in

digital images. Comput Vision Graph 34(3):344–

Bortolussi V, Figliuzzi B, Willot F, Faessel M, Jeandin

M (2018). Morphological modeling of cold spray

coatings. Image Anal Stereol 37(2):145–58.

Caflisch RE (1998). Monte Carlo and quasi-Monte

Carlo methods. Acta Numer 7:1–49.

Carman PC (1937). Fluid flow through granular beds.

Trans Inst Chem Eng 15:150–66.

Chaniot J, Moreaud M, Sorbier L, Becker J-M, Fournel

T (2019). Tortuosimetric operator for complex

porous media characterization. Image Anal Stereol

(1):25–41.

Chiu SN, Stoyan D, Kendall WS, Mecke J (2013).

Stochastic geometry and its applications. John

Wiley & Sons.

Clennell MB (1997). Tortuosity: a guide through the

maze. Geol Soc Spec Publ 122(1):299–344.

Criminisi A, Sharp T, Rother C, Pérez P (2010).

Geodesic image and video editing. ACM T

Graphic 29(5):134–1.

Decker L, Jeulin D, Tovena I (1998). 3D

morphological analysis of the connectivity of

a porous medium. Acta Stereol 17(1).

Dullien FAL (1979). Porous media: fluid transport and

pore structure. Academic press.

Ghanbarian B, Hunt AG, Ewing RP, Sahimi M (2013).

Tortuosity in porous media: a critical review. Soil

Sci Soc Am J 77(5):1461–77.

Ghanbarian B, Hunt AG, Sahimi M, Ewing RP,

Skinner TE (2013). Percolation theory generates

a physically based description of tortuosity in

saturated and unsaturated porous media. Soil Sci

Soc Am J 77(6):1920–29.

Gouéré J-B, Théret M (2017). Positivity of the time

constant in a continuous model of first passage

percolation. Electron J Probab 22.

Graham D (1957). Geometric heterogeneity in the

adsorption of nitrogen on graphitized carbon

surfaces. J Phys Chem-US 61(10):1310–13.

Grujicic M, Cao G, Roy WN (2004). A computational

analysis of the percolation threshold and the

electrical conductivity of carbon nanotubes filled

polymeric materials. J Mater Sci 39(14):4441–9.

Hill R (1963). Elastic properties of reinforced solids:

some theoretical principles. J Mech Phys Solids

(5):357–72.

Hollewand MP, Gladden LF (1995). Transport

heterogeneity in porous pellets—I. PGSE NMR

studies. Chem Eng Sci 50(2):309–26.

Holzer L, Wiedenmann D, Münch B, Keller L, Prestat

M, Gasser Ph, Robertson I, Grobéty B (2013). The

influence of constrictivity on the effective transport

properties of porous layers in electrolysis and fuel

cells. J Mater Sci 48(7):2934–52.

Jean A, Jeulin D, Forest S, Cantournet S, N’Guyen

F (2011). A multiscale microstructure model of

carbon black distribution in rubber. J Microsc

(3):243–60.

Jeulin D (1993). Damage simulation in heterogeneous

materials from geodesic propagations. Eng

Computation 10(1):81–91.

Jeulin D (1996). Modeling heterogeneous materials

by random structures. Invited lecture, European

Workshop on Application of Statistics and

Probabilities in Wood Mechanics, Bordeaux , N-

/96/MM, Paris School of Mines Publication.

Jeulin D (1997). Advances in Theory and Applications

of Random Sets. In : Advances In Theory And

Applications Of Random Sets: Proceedings Of The

Symposium. World Scientific 105.

Jeulin D, Moreaud M (2006). Percolation of

multi-scale fiber aggregates. S4G (Stereology,

Spatial Statistics and Stochastic Geometry) 6th

International Conference, Prague, Czech Republic.

Jeulin D (2010). Multi scale random models of

complex microstructures. Mater Sci Forum

:81–6.

Jeulin D (2012). Morphology and effective properties

of multi-scale random sets: A review. CR

Mecanique 340(4-5):219–29.

Kanit T, Forest S, Galliet I., Mounoury V., Jeulin

D. (2003). Determination of the size of the

representative volume element for random

composites: statistical and numerical approach. Int

J Solids Struct 40(13-14):3647–79.

Karimpouli S, Tahmasebi P (2019). 3D multifractal

analysis of porous media using 3D

digital images: considerations for heterogeneity

evaluation. Geophys Prospect 67(4):1082–93.

Kingman JFC (1993). Poisson Processes. Oxford

Science Publications, Oxford Studies in

Probability 3.

Lantuéjoul C, Beucher S (1981). On the use of the

geodesic metric in image analysis. J Microsc

(1):39–49.

Lohou C, Bertrand G (2005). A 3D 6-subiteration

curve thinning algorithm based on P-simple points.

Discrete Appl Math 151(1):198–228.

Matheron G (1975). Random sets and integral

geometry. Wiley New York.

Moreaud M, Chaniot J, Fournel T, Becker J-M, Sorbier

L (2018). Multi-scale stochastic morphological

models for 3D complex microstructures. 17th

Workshop on Information Optics (WIO), Quebec,

Canada, IEEE, 1–3.

Neumann M, Charry, EM, Zojer K, Schmidt V

(2020). On variability and interdependence of local

porosity and local tortuosity in porous materials: a

case study for sack paper. Methodol Comput Appl

–15.

Neumann M, Hirsch C, Stanˇek J, Beneš V, Schmidt

V (2019). Estimation of geodesic tortuosity and

constrictivity in stationary random closed sets.

Scand J Stat 46:848–84.

Neumann M, Abdallah B, Holzer L, Willot F, Schmidt

V (2019). Stochastic 3D Modeling of Three-

Phase Microstructures for Predicting Transport

Properties: A Case Study. Transport Porous Med,

–22.

Newman MEJ, Ziff RM (2001). Fast Monte Carlo

algorithm for site or bond percolation. Phys Rev

E 64(1):016706.

Neyman J (1934). On the two different aspects of

the representative method: the method of stratified

sampling and the method of purposive selection. J

R Stat Soc 97(4):558–625.

Ohser J, Ferrero C, Wirjadi O, Kuznetsova A, Duell

J, Rack A (2012). Estimation of the probability of

finite percolation in porous microstructures from

tomographic images. Int J Mater Res 103(2):184–

Petersen EE (1958). Diffusion in a pore of varying

cross section. AIChE J 4(3):343–5.

Peyrega C, Jeulin D (2013). Estimation of tortuosity

and reconstruction of geodesic paths in 3D. Image

Anal Stereol 32(1):27–43.

Raybaud P, Toulhoat H (2013). Catalysis by transition

metal sulphides: From molecular theory to

industrial application. Editions Technip.

Rigby SP, Gladden LF (1996). NMR and fractal

modelling studies of transport in porous media.

Chem Eng Sci 51(10):2263–72.

Rosenfeld A, Pfaltz JL (1968). Distance Functions on

Digital Pictures. Pattern Recogn 1:33–61.

Rutovitz D (1968). Data structures for operations on

digital images. Pictorial pattern recognition 105–

Saha PK, Borgefors G, Di Baja GS (2016). A survey on

skeletonization algorithms and their applications.

Pattern Recogn Lett 76:3–12.

Savary L, Jeulin D, Thorel A (1999). Morphological

analysis of carbon-polymer composite materials

from thick sections. Acta Stereol 18(3):297–303.

Serra J (1982). Image Analysis and Mathematical

Morphology. Academic Press, London.

Toivanen PJ (1996). New geodesic distance transforms

for gray-scale images. Pattern Recogn Lett

(5):437–50.

Tran V-D, Moreaud M, Thiébaut E, Denis L, Becker

J-M (2014). Inverse problem approach for the

alignment of electron tomographic series. Oil Gas

Sci Technol 69(2):279–91.

Van Brakel J, Heertjes PM (1974). Analysis of

diffusion in macroporous media in terms of a

porosity, a tortuosity and a constrictivity factor. Int

J Heat Mass Tran 17(9):1093–103.

Vogel H (2002). Topological characterization of

porous media. Morphology of condensed matter

–92.

Wang H, Pietrasanta A, Jeulin D, Willot F, Faessel

M, Sorbier L, Moreaud M (2015). Modelling

mesoporous alumina microstructure with 3D

random models of platelets. J Microsc 260(3):287–

Warren JE, Price HS (1961). Flow in heterogeneous

porous media. Soc Petrol Eng J 1(3):153–69.

Wernert V, Bouchet R, Denoyel R (2010). Influence of

molecule size on its transport properties through a

porous medium. Anal Chem 82(7):2668–79.

Willot F (2015) The power laws of geodesics in

some random sets with dilute concentration of

inclusions. ISMM 2015 535–46.

”plug im!” an open access and customizable

software for signal and image processing.

https://www.plugim.fr (2018).

Downloads

Published

2020-06-22

Issue

Section

Original Research Paper

How to Cite

Chaniot, J., Moreaud, M., Sorbier, L., Jeulin, D., Becker, J.-M., & Fournel, T. (2020). Heterogeneity Assessment Based on Average Variations of Morphological Tortuosity for Complex Porous Structures Characterization. Image Analysis and Stereology, 39(2), 111-128. https://doi.org/10.5566/ias.2370

Most read articles by the same author(s)

1 2 3 > >>