journal article·2021-06Open access

Stochastic modelling of 3D fiber structures imaged with X-ray microtomography

Philip Townsend, Emanuel Larsson, Tomas Karlson, Stephen A. Hall, Malin Lundman, Per Bergström, Charlotta Hanson, Niklas Lorén, Tobias Gebäck, Aila Särkkä, Magnus Röding

Abstract

Many products incorporate into their design fibrous material with particular levels of permeability as a way to control the retention and flow of liquid. The production and experimental testing of these materials can be expensive and time consuming, particularly if it needs to be optimised to a desired level of absorbency. We consider a parametric virtual fiber model as a replacement for the real material to facilitate studying the relationship between structure and properties in a cheaper and more convenient manner. 3D image data sets of a sample fibrous material are obtained using X-ray microtomography and the individual fibers isolated. The segmented fibers are used to estimate the parameters of a 3D stochastic model for generating softcore virtual fiber structures. We use several spatial measures to show the consistency between the real and virtual structures, and demonstrate with lattice Boltzmann simulations that our virtual structure has good agreement with respect to the permeability of the physical material.
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Research context

OpenAlex topics: Composite Material Mechanics · Lattice Boltzmann Simulation Studies · Generative Adversarial Networks and Image Synthesis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (30)

Show source-provided references
1. Magnus Röding, Erich Schuster, Katarina Logg, Malin Lundman, Per Bergström, Charlotta Hanson, Tobias Gebäck, and Niklas Lorén. Computational high-throughput screening of fluid permeability in heterogeneous fiber materials. Soft Matter, 12: 6293–6299, 2016. DOI: 10.1039/C6SM01213B. doi: 10.1039/C6SM01213B.10.1039/C6SM01213B ↗
2. Zhengyuan Pan, Yun Liang, Min Tang, Zhaoxia Sun, Jian Hu, Jing Wang, Simulation of performance of fibrous filter media composed of cellulose and synthetic fibers, Cellulose 26 (12) (2019) 7051–7065. DOI: 10.1007/s10570-019-02605-8. doi: 10.1007/s10570-019-02605-8.10.1007/s10570-019-02605-8 ↗
3. 3d analysis, modeling and simulation of transport processes in compressed fibrous microstructures, using the lattice boltzmann method10.1016/j.electacta.2013.04.071 ↗
4. Skeleton-based tracing of curved fibers from 3d x-ray microtomographic imaging10.1016/j.rinp.2016.03.008 ↗
5. Joachim Ohser and Katja Schladitz. 3D Images of Materials Structures: Processing and Analysis. Wiley-VCH, 06 2010. ISBN 978-3-527-31203-0. DOI: 10.1002/9783527628308.10.1002/9783527628308 ↗
6. Stochastic characterisation methodology for 3-D textiles based on micro-tomography10.1016/j.compstruct.2017.03.107 ↗
7. Gerd Gaiselmann, Dieter Froning, Christian Tötzke, Christian Quick, Ingo Manke, Werner Lehnert, Volker Schmidt, Stochastic 3d modeling of non-woven materials with wet-proofing agent. International Journal of Hydrogen Energy, 38 (20) (2013) 8448–8460. doi: 10.1016/j.ijhydene.2013.04.144. http://www.sciencedirect.com/science/article/pii/S0360319913011221.10.1016/j.ijhydene.2013.04.144 ↗
8. Characterizing nonwoven materials via realistic microstructural modeling10.1016/j.seppur.2018.10.018 ↗
9. Modeling of composite fibrous porous diffusion media10.1016/j.ijhydene.2014.04.011 ↗
10. Yi Li, Zhangxing Chen, Lingxuan Su, Wei Chen, Xuejun Jin, Hongyi Xu, Stochastic reconstruction and microstructure modeling of smc chopped fiber composites, Composite Structures 200 (2018) 153–164. doi: 10.1016/j.compstruct.2018.05.079. http://www.sciencedirect.com/science/article/pii/S0263822317324224.10.1016/j.compstruct.2018.05.079 ↗
11. Random walk based stochastic modeling of 3D fiber systems
12. 3D Modelling of random cellulosic fibrous networks based on X-ray tomography and image analysis10.1016/j.compscitech.2004.12.038 ↗
13. Gerd Gaiselmann, Ralf Thiedmann, Ingo Manke, Werner Lehnert, Volker Schmidt, Stochastic 3d modeling of fiber-based materials, Computational Materials Science 59 (2012) 75–86. doi: 10.1016/j.commatsci.2012.02.038. http://www.sciencedirect.com/science/article/pii/S0927025612001267.10.1016/j.commatsci.2012.02.038 ↗
14. Gerd Gaiselmann, Ingo Manke, Werner Lehnert, Volker Schmidt, Extraction of curved fibers from 3d data, Image Analysis & Stereology 32 (1) (2013) 57–63. ISSN 1854-5165. DOI: 10.5566/ias.v32.p57-63. https://www.ias-iss.org/ojs/IAS/article/view/979.10.5566/ias.v32.p57-63 ↗
15. A supervised iterative approach to 3D microstructure reconstruction from acquired tomographic data of heterogeneous fibrous systems10.1016/j.compstruct.2018.08.029 ↗
16. Microstructure reconstruction of fibrous C/C composites from X-ray microtomography10.1016/j.carbon.2007.01.021 ↗
17. A lattice Boltzmann method for the advection-diffusion equation with Neumann boundary conditions10.4208/cicp.161112.230713a ↗
18. J. Schindelin et al., Fiji: an open-source platform for biological-image analysis, Nature Methods 9 (2012) 676–682. 10.1038/nmeth.2019. https://doi.org/10.1038/nmeth.2019.10.1038/nmeth.2019 ↗
19. Z. Püspöki, M. Storath, D. Sage, M. Unser, Transforms and operators for directional bioimage analysis: a survey, Focus on Bio-Image Informatics (2016) 69–93, 2016.10.1007/978-3-319-28549-8_3 ↗
20. Anisotropic analysis of fibrous and woven materials part 1: Estimation of local orientation10.1016/j.commatsci.2020.109631 ↗
21. Kanti Mardia, Peter Jupp, Directional Statistics. Wiley Series in Probability and Statistics. Wiley, vol. 01, 1999. ISBN 978-0-471-95333-3. DOI: 10.1002/9780470316979.10.1002/9780470316979 ↗
22. Dylan Muir (2019). vmrand(fMu, fKappa, varargin) (https://www.mathworks.com/matlabcentral/fileexchange/37241-vmrand-fmu-fkappa-varargin), MATLAB Central File Exchange. Retrieved November 14, 2019.
23. 1997 · vol. 1
24. Jean Gallier, Curves and Surfaces in Geometric Modelling: Theory and Algorithms, The Morgan Kaufmann Series in Computer Graphics. Morgan Kaufmann, 1999. ISBN 978-1558605992.
25. David Coeurjolly, Stina Svensson, Estimation of curvature along curves with application to fibres in 3d images of paper, in: Josef Bigun, Tomas Gustavsson, eds., Image Analysis, Berlin, Heidelberg, 2003, pp. 247–254. Springer, Berlin Heidelberg. ISBN 978-3-540-45103-7.10.1007/3-540-45103-X_34 ↗
26. MATLAB · 2018
27. Clustering on the unit hypersphere using von mises-fisher distributions
28. S. Barman, D. Bolin, C. Fager, T. Geback, N. Lorén, E. Olsson, H. Rootzen, A. Sarkka, MIST – a program package for visualization and characterization of 3D geometries, 2019.
29. Modelling spatial patterns10.1111/j.2517-6161.1977.tb01615.x ↗
30. Sung Nok Chiu, Dietrich Stoyan, Wilfred S. Kendall, Joseph Mecke, Stochastic Geometry and its Applications, Wiley Series in Probability and Statistics, Wiley, vol. 08, 2013. ISBN 987-0-470-66481-0. DOI: 10.1002/9781118658222.10.1002/9781118658222 ↗