A novel technique for determining the 3D spatial distribution of glass fibres in polymer composites

Clarke, Ashley; Archenhold, G.; Davidson, N.

doi:10.1016/0266-3538(95)00087-9

Cited by 93 publications

(50 citation statements)

References 27 publications

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“…Methods for computing the fibre direction distribution proposed so far usually required precise segmentations of fibres either in 2D (Clarke et al, 1995;Lee et al, 2002;Kiderlen and Pfrang, 2005), or in 3D (Yang and Lindquist, 2000;Tan et al, 2006). In contrast to that, Eq.…”

Section: Image Binarisationmentioning

confidence: 99%

“…However, a fibre direction is not uniquely determined by the corresponding cross-section. To overcome this problem, Clarke et al (1995) and Eberhardt and Clarke (2001) used confocal laser scanning microscopy to determine fibre directions by tracking individual fibres in glass fibre reinforced polymers through a depth of up to 150 µm. Nevertheless, this type of stereological reconstruction of the three-dimensional fibre directions from planar sections is error-prone in particular for curved fibres or for straight fibres which are parallel to the section plane.…”

Section: Introductionmentioning

confidence: 99%

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Estimating Fibre Direction Distributions of Reinforced Composites From Tomographic Images

et al. 2016

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Fibre reinforced composites constitute a relevant class of materials used chiefly in lightweight constructions for example in fuselages or car bodies. The spatial arrangement of the fibres and in particular their direction distribution have huge impact on macroscopic properties and, thus, its determination is an important topic of material characterisation. The fibre direction distribution is defined on the unit sphere, and it is therefore preferable to work with fully three-dimensional images of the microstructure as obtained, e.g., by computed micro-tomography. A number of recent image analysis algorithms exploit local grey value variations to estimate a preferred direction in each fibre point. Averaging these local results leads estimates of the volume-weighted fibre direction distribution. We show how the thus derived fibre direction distribution is related to quantities commonly used in engineering applications. Furthermore, we discuss four algorithms for local orientation analysis, namely those based on the response of anisotropic Gaussian filters, moments and axes of inertia derived from directed distance transforms, the structure tensor, or the Hessian matrix. Finally, the feasibility of these algorithms is demonstrated for application examples and some advantages and disadvantages of the underlying methods are pointed out.

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Section: Image Binarisationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimating Fibre Direction Distributions of Reinforced Composites From Tomographic Images

et al. 2016

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“…Previously, 3D fibre orientation distributions obtained from analysis of 3D data has been explored in relation to the characterisation of collagen matrices (Wu, et al, 2003), fibre reinforced composites (Clarke, et al, 1995;Eberhardt & Clarke, 2002), bonded fibre networks such as those produced by solid state sintering (Tan, et al, 2006) as well as nonwovens (Eberhardt & Clarke, 2002;Yang & Lindquist, 2000) by employing various techniques.…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Fiber Segment Orientation Distribution Using X-Ray Microtomography

et al. 2014

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The orientation of fibres in assemblies such as nonwovens has a major influence on the anisotropy of properties of the bulk structure and is strongly influenced by the processes used to manufacture the fabric. To build a detailed understanding of a fabric's geometry and architecture it is important that fibre orientation in three dimensions is evaluated since out of plane orientations may also contribute to the physical properties of the fabric. In this study, a technique for measuring fibre segment orientation as proposed by Eberhardt and Clarke

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“…Links between processing parameters, mesostructure and mechanical performance are vital if successful progress in this area is to be made (Darlington & McGinley, 1975;Folkes, 1982;Vincent & Agassant, 1986;Fischer & Eyerer, 1988;Haritos et al, 1988;Bay, 1990;McClelland & Gibson, 1990;O'Connell & Ducket, 1991;O'Donnell & White, 1991;Truckenmuller & Fritz, 1991;Hine et al, 1993;Toll & Andersson, 1993;Ludwig et al, 1994). Following previous work in developing image analysis algorithms to measure mesostructural parameters quantitatively (Clarke & Davidson, 1992;Clarke et al, 1993), this paper describes how these methods can be applied to the measurement of fibre orientations over a large sample area (mm × mm).…”

Section: Introductionmentioning

confidence: 99%

Large‐area, high‐resolution image analysis of composite materials

Davidson

Clarke

Archenhold

1997

Journal of Microscopy

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An image analysis system based on a small network of parallel processors hosted within a PC has been developed to measure the orientations of glass and carbon fibres in a polymer matrix from a polished section using optical microscopy. A computer‐controlled XY translation stage is used to scan a large sample area (mm × mm), at a high magnification to minimize measurement errors. The distance that the stage moves between adjacent image frames is accurately measured allowing partial images at the edges of image frames to be reconstructed and so produce a continuous area. By removing a small amount of material from the sample by polishing and rescanning the same sample area, data from a number of serial sections can be obtained. Pattern matching is then used to correlate the fibre images from each section, allowing full three‐dimensional orientation data to be extracted, overcoming the limitations of measurements from a single, two‐dimensional section plane.

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A novel technique for determining the 3D spatial distribution of glass fibres in polymer composites

Cited by 93 publications

References 27 publications

Estimating Fibre Direction Distributions of Reinforced Composites From Tomographic Images

Estimating Fibre Direction Distributions of Reinforced Composites From Tomographic Images

Three-Dimensional Fiber Segment Orientation Distribution Using X-Ray Microtomography

Large‐area, high‐resolution image analysis of composite materials

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