Mechanics of Random Fiber Networks: Structure–Properties Relation

Picu, Catalin R.

doi:10.1007/978-3-030-23846-9_1

Cited by 8 publications

(3 citation statements)

References 106 publications

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“…These springs still gave rise to bulk stress–strain behavior that was nonlinear because of the progressive recruitment of collagen over the physiologically relevant strain range, but it is possible that fibers are more accurately represented by strain-stiffening springs. We did not include bending stiffness due to its effects being negligible in soft biological tissues 30 , likely because the length to width ratio of collagen fibers at the scale of an alveolus is so large. Permanent bonds between fibers at their crossing points are also somewhat unrealistic and may have led to artificially high stresses because the bonds were not allowed to break or slip.…”

Section: Discussionmentioning

confidence: 99%

Percolation of collagen stress in a random network model of the alveolar wall

Casey

Jawde

Herrmann

et al. 2021

Sci Rep

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Fibrotic diseases are characterized by progressive and often irreversible scarring of connective tissue in various organs, leading to substantial changes in tissue mechanics largely as a result of alterations in collagen structure. This is particularly important in the lung because its bulk modulus is so critical to the volume changes that take place during breathing. Nevertheless, it remains unclear how fibrotic abnormalities in the mechanical properties of pulmonary connective tissue can be linked to the stiffening of its individual collagen fibers. To address this question, we developed a network model of randomly oriented collagen and elastin fibers to represent pulmonary alveolar wall tissue. We show that the stress–strain behavior of this model arises via the interactions of collagen and elastin fiber networks and is critically dependent on the relative fiber stiffnesses of the individual collagen and elastin fibers themselves. We also show that the progression from linear to nonlinear stress–strain behavior of the model is associated with the percolation of stress across the collagen fiber network, but that the location of the percolation threshold is influenced by the waviness of collagen fibers.

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Section: Discussionmentioning

confidence: 99%

Percolation of collagen stress in a random network model of the alveolar wall

Casey

Jawde

Herrmann

et al. 2021

Sci Rep

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“…In the tensile test of a real tissue paper, the tissue strength depends on mechanisms such as interfibre bond rupture, strain localization, and non-affine deformation [18,21,35,36]. Since the above mechanisms are not considered in our study, the tensile test ends when the maximum force/width in the sheet reaches the specified value (f ws ), the corresponding value of strain is taken as stretch.…”

Section: Yielding and Failure Criteriamentioning

confidence: 99%

Influence of Crepe Structure on Tensile Properties of Tissue Paper

Agarwal,

Srivastava,

Green

et al. 2022

Trans. Of the XVIIth Fund. Res. Symp. Cambridge, 2022

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Tissue is a low-density paper product distinguished by a microscale crepe structure. We investigate the relationship between the macroscale tissue tensile response and crepe structure. We propose a parameter called the Crepe Index (CI) that can be measured from edge images of the creped sheet. Crepe Index correlates very well with the measured tensile failure strain (“stretch”), but its correlation with the measured initial elastic stiffness is unclear. A discrete elastoplastic model (DEM) is developed to explain the experimental results and understand the nonlinearity in the tensile curve. The model accounts for both material nonlinearity through a bilinear elastoplastic constitutive law for the sheet material, and the geometric nonlinearity arising from large deformations. The creped sheet is idealized as a triangular wave of prescribed wavelength and waveheight, with nonlinear bending and stretching effects. The model results show that the tensile response is governed by both the nonlinearity of the sheet material (fibre network) and crepe structure (geometry). The yielding in stretching and bending gives rise to an inflection in the tensile response. It is found that the initial stiffness depends not only on CI, but also on parameters such as sheet thickness to crepe-wavelength ratio, and stiffness of sheet material after creping. Thus, the variability in above parameters can be one of the reason for unclear correlation between measured initial stiffness and CI. For CI range of tested commercial tissues, both experiments and model show that stretch varies linearly with CI, with an almost unity slope and a positive intercept (i.e, stretch> CI). Thus, the overall stretch of creped tissue is a sum of CI and network stretching.

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“…It is well known that the macroscopic behaviour of fibrous materials is inherited from their microscopic composition and microstructure. 1 Their physical properties depend on the volume fraction of fibres but also on their geometries and 3D spatial repartitions (orientation and fibrefibre contacts). Their microstructures have been studied for the last 20 years using X-ray microtomography.…”

Section: Introductionmentioning

confidence: 99%

Individual fibre separation in 3D fibrous materials imaged by X‐ray tomography

Depriester

Roscoat

Orgéas

et al. 2022

Journal of Microscopy

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Modelling the physical behaviour of fibrous materials still remains a great challenge because it requires to evaluate the inner structure of the different phases at the phase scale (fibre or matrix) and the at constituent scale (fibre). X-ray computed tomography (CT) imaging can help to characterize and to model these structures, since it allows separating the phases, based on the grey level of CT scans. However, once the fibrous phase has been isolated, automatically separating the fibres from each other is still very challenging. This work aims at proposing a method which allows separating the fibres and localizing the fibre-fibre contacts for various fibres geometries, that is: straight or woven fibres, with circular or non-circular cross sections, in a way that is independent of the fibres orientations. This method uses the local orientation of the structure formed by 220

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Mechanics of Random Fiber Networks: Structure–Properties Relation

Cited by 8 publications

References 106 publications

Percolation of collagen stress in a random network model of the alveolar wall

Percolation of collagen stress in a random network model of the alveolar wall

Influence of Crepe Structure on Tensile Properties of Tissue Paper

Individual fibre separation in 3D fibrous materials imaged by X‐ray tomography

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