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

doi:10.1016/j.commatsci.2021.110433

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

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Article number	110433
Journal	Computational Materials Science
Volume	194
DOIs	https://doi.org/10.1016/j.commatsci.2021.110433
Publication status	Published - 2021 Jun 15

Bibliographical note

Funding Information:
This work was financially supported by Vinnova (project number 2018–00424) as part of the CoSiMa project, as well as by the Swedish Research Council (VR 2018-03986) and by the Swedish Foundation for Strategic Research (SSF AM13-0066). The authors would like to thank Claudia Redenbach and Katja Schladitz of the Technical University of Kaiserslautern and the Fraunhofer Institute for Industrial Mathematics for their hospitality and informative discussions during a research visit to Kaiserslautern. We are also very grateful for the valuable comments given by the anonymous reviewers.

Funding Information:
This work was financially supported by Vinnova (project number 2018?00424) as part of the CoSiMa project, as well as by the Swedish Research Council (VR 2018-03986) and by the Swedish Foundation for Strategic Research (SSF AM13-0066). The authors would like to thank Claudia Redenbach and Katja Schladitz of the Technical University of Kaiserslautern and the Fraunhofer Institute for Industrial Mathematics for their hospitality and informative discussions during a research visit to Kaiserslautern. We are also very grateful for the valuable comments given by the anonymous reviewers.

Publisher Copyright:
© 2021 The Author(s)

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

Subject classification (UKÄ)

Paper, Pulp and Fiber Technology

Free keywords

Fiber structures
Mass transport
Parameter estimation
Permeability
Stochastic modelling
X-ray microtomography

Access to Document

10.1016/j.commatsci.2021.110433Licence: CC BY

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Hall, S. (Manager) & Engqvist, J. (Contact)
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Cite this

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title = "Stochastic modelling of 3D fiber structures imaged with X-ray microtomography",

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.",

keywords = "Fiber structures, Mass transport, Parameter estimation, Permeability, Stochastic modelling, X-ray microtomography",

author = "Philip Townsend and Emanuel Larsson and Tomas Karlson and Hall, {Stephen A.} and Malin Lundman and Per Bergstr{\"o}m and Charlotta Hanson and Niklas Lor{\'e}n and Tobias Geb{\"a}ck and Aila S{\"a}rkk{\"a} and Magnus R{\"o}ding",

note = "Funding Information: This work was financially supported by Vinnova (project number 2018–00424) as part of the CoSiMa project, as well as by the Swedish Research Council (VR 2018-03986) and by the Swedish Foundation for Strategic Research (SSF AM13-0066). The authors would like to thank Claudia Redenbach and Katja Schladitz of the Technical University of Kaiserslautern and the Fraunhofer Institute for Industrial Mathematics for their hospitality and informative discussions during a research visit to Kaiserslautern. We are also very grateful for the valuable comments given by the anonymous reviewers. Funding Information: This work was financially supported by Vinnova (project number 2018?00424) as part of the CoSiMa project, as well as by the Swedish Research Council (VR 2018-03986) and by the Swedish Foundation for Strategic Research (SSF AM13-0066). The authors would like to thank Claudia Redenbach and Katja Schladitz of the Technical University of Kaiserslautern and the Fraunhofer Institute for Industrial Mathematics for their hospitality and informative discussions during a research visit to Kaiserslautern. We are also very grateful for the valuable comments given by the anonymous reviewers. Publisher Copyright: {\textcopyright} 2021 The Author(s) Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",

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AU - Townsend, Philip

AU - Larsson, Emanuel

AU - Karlson, Tomas

AU - Hall, Stephen A.

AU - Lundman, Malin

AU - Bergström, Per

AU - Hanson, Charlotta

AU - Lorén, Niklas

AU - Gebäck, Tobias

AU - Särkkä, Aila

AU - Röding, Magnus

N1 - Funding Information: This work was financially supported by Vinnova (project number 2018–00424) as part of the CoSiMa project, as well as by the Swedish Research Council (VR 2018-03986) and by the Swedish Foundation for Strategic Research (SSF AM13-0066). The authors would like to thank Claudia Redenbach and Katja Schladitz of the Technical University of Kaiserslautern and the Fraunhofer Institute for Industrial Mathematics for their hospitality and informative discussions during a research visit to Kaiserslautern. We are also very grateful for the valuable comments given by the anonymous reviewers. Funding Information: This work was financially supported by Vinnova (project number 2018?00424) as part of the CoSiMa project, as well as by the Swedish Research Council (VR 2018-03986) and by the Swedish Foundation for Strategic Research (SSF AM13-0066). The authors would like to thank Claudia Redenbach and Katja Schladitz of the Technical University of Kaiserslautern and the Fraunhofer Institute for Industrial Mathematics for their hospitality and informative discussions during a research visit to Kaiserslautern. We are also very grateful for the valuable comments given by the anonymous reviewers. Publisher Copyright: © 2021 The Author(s) Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/6/15

Y1 - 2021/6/15

N2 - 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.

AB - 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.

KW - Fiber structures

KW - Mass transport

KW - Parameter estimation

KW - Permeability

KW - Stochastic modelling

KW - X-ray microtomography

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DO - 10.1016/j.commatsci.2021.110433

M3 - Article

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SN - 0927-0256

VL - 194

JO - Computational Materials Science

JF - Computational Materials Science

M1 - 110433

ER -

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

Abstract

Bibliographical note

Subject classification (UKÄ)

Free keywords

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