Finding fibres and their contacts within 3D images of disordered fibrous media

Viguié, Jérémie; Latil, P.; Orgéas, Laurent; Dumont, Pierre; Roscoat, Sabine Rolland Du; Bloch, Jean‐Francis; Marulier, C.; Guiraud, Olivier

doi:10.1016/j.compscitech.2013.09.023

Cited by 54 publications

(50 citation statements)

References 23 publications

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“…The fibres may thus be partially hollow and partially solid, hindering the use of above methods. Algorithms introduced in [22][23][24] are based on analysis of the local orientation of fibres in order to separate them from each other, and thus seem to be better suited for fibres of irregular shape.…”

Section: Introductionmentioning

confidence: 99%

Non-destructive automatic determination of aspect ratio and cross-sectional properties of fibres

Miettinen

Ojala

Wikström

et al. 2015

Composites Part A: Applied Science and Manufacturing

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A novel method for computerized estimation of the aspect ratio distribution and various cross-sectional geometrical properties of fibres in short-fibre reinforced composites is proposed. The method, based on X-ray microcomputed tomography, is non-destructive and does not require user intervention. Based on results on specially fabricated model material, the accuracy and precision of the method seems adequate. The method is applied in analysing a manufacturing process of wood fibre reinforced thermoplastic composite. The results indicate a significant decrease of the aspect ratio of fibres during the processing steps. Finally, the feasibility of the method is assessed by estimating parameters of a micromechanical model for flax fibre composites and comparing the results with those from tensile tests.

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Section: Introductionmentioning

confidence: 99%

Non-destructive automatic determination of aspect ratio and cross-sectional properties of fibres

Miettinen

Ojala

Wikström

et al. 2015

Composites Part A: Applied Science and Manufacturing

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“…Examples of fibre reinforced composites include the combined segmentation and voxel-based fibre tracking algorithm [14], the simplified marching cubes method [15][16][17], the fibre contacts and orientation method [18,19] and the intersecting fibre cluster method [20]. The main advantage of direct segmentation for fibre composites is that various 3D skeletonisation algorithms can be applied to extract fibre centrelines [18,20] after segmentation, so that the fibres can be modelled as exact cylinders.…”

mentioning

confidence: 99%

Generation of micro-scale finite element models from synchrotron X-ray CT images for multidirectional carbon fibre reinforced composites

Sencu

Yang

Wang

et al. 2016

Composites Part A: Applied Science and Manufacturing

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This paper develops a new fibre tracking algorithm to efficiently locate fibre centrelines (skeletons), from X-ray Computed Tomography (X-ray CT) images of carbon fibre reinforced polymer (CFRP), which are then used to generate micro-scale finite element models. Threedimensional images with 330nm voxel resolution of multidirectional [+45/90/-45/0] CFRP specimens were obtained by fast synchrotron X-ray CT scanning. Conventional image processing techniques, such as a combination of filters, delineation of plies, binarisation of images, and fibre identification by local maxima and ultimate eroding points, were tried first but found insufficient to produce continuous fibre centrelines for segmentation, especially in regions with highly congested fibres. The new algorithm uses a global overlapping stack filtering step followed by a local fibre tracking step. Both steps are based on the Bayesian inference theory.The new algorithm is found capable of efficiently define fibre centrelines for the generation of micro-scale finite element models with high fidelity.

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“…This information is also valuable for changes in the network structure, for example, due to refining. A common limitation, when imaging samples for further analysis, is the size of a test piece (see, for example, He, Batchelor, & Johnston, 2004;Viguié et al, 2013). It is natural to expect variations between the test samples, and therefore the quality of statistical data that is able to be represented is questionable.…”

Section: Variation Between the Test Piecesmentioning

confidence: 99%

“…We merge the data from two analyzed samples to create a comprehensive set with 250 demarcated fibers. A few independent studies by different research groups have been presented lately (Malmberg et al, 2011;Tan et al, 2006;Viguié et al, 2013). In the recent study by Marulier et al, (2015), the influence of papermaking conditions in terms of fiber orientation, pressing levels, and drying conditions was analysed regarding the geometry of fibers and fiber-to-fiber bonds.…”

mentioning

confidence: 99%

“…In turn, this has created a niche for developing image analysis methods for non-destructive wood fiber segmentation applicable to fiber-based materials. A number of partially and fully automated methods have been proposed (Dokládal, Jeulin, 2009;Marulier et al, 2012;Wernersson et al, 2009;Viguié et al, 2013;Yamakawa, Chinga-Carrasco, 2010). Previously, we presented the methods of describing the internal characteristics of fiber networks in paper using X-ray tomography, adapted for estimation of the number of bonds in paper (see Wernersson et al, 2014).…”

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confidence: 99%

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Extracting fiber and network connectivity data using microtomography images of paper

Borodulina¹,

Wernersson

Kulachenko³

et al. 2016

Nordic Pulp &Amp; Paper Research Journal

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SUMMARY:We apply image analysis methods based on micro-computed tomography (µCT) to extract the parameters that characterize the structure and bonding parameters in the fiber network of paper. The scaling and variational properties of µCT images are examined by analyzing paper structural properties of two 1 × 1 mm2 test pieces, which have been cut out from a low-grammage handsheet. We demonstrate the applicability of the methods for extracting the free fiber length, fiber cross-sectional data, the distances between the fibers, and the number of fiber-to-fiber bonds, which are the key properties required for the adequate representation of the network in numerical models. We compare the extracted connectivity data with the early reported analytical estimations and conclude that the number of contacts in three-dimensional networks is controlled by the fiber aspect ratio. In addition, we compare the cross-sectional data with those measured by the fiber morphology characterization tools and estimate the fiber shrinkage from completely wet to dry state to be nearly 20%. ADDRESSES OF THE AUTHORS: Svetlana Borodulina(svebor@kth.se), Artem Kulachenko (artem@kth.se): KTH,

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Finding fibres and their contacts within 3D images of disordered fibrous media

Cited by 54 publications

References 23 publications

Non-destructive automatic determination of aspect ratio and cross-sectional properties of fibres

Non-destructive automatic determination of aspect ratio and cross-sectional properties of fibres

Generation of micro-scale finite element models from synchrotron X-ray CT images for multidirectional carbon fibre reinforced composites

Extracting fiber and network connectivity data using microtomography images of paper

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