Numerical reconstruction of graphite/epoxy composite microstructure based on sub-micron resolution X-ray computed tomography

Czabaj, Michael W.; Riccio, Mark L.; Whitacre, William W.

doi:10.1016/j.compscitech.2014.10.017

Cited by 107 publications

(51 citation statements)

References 36 publications

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“…11 shows two such cases used to estimate the threshold values based on the two corresponding shifted probability distributions. One may note that [2] proposed a similar fibre tracking algorithm using the Kalman filtering.…”

Section: Calibration Of Local Inference Modelmentioning

confidence: 99%

“…New numerical reconstruction methods with advanced image filtering and stack conditioners have thus been developed for fibre tracking and noise reduction. For example, Czabaj and co-workers developed a template matching algorithm to determine the fibre centre points from X-ray CT images of unidirectional carbon fibre reinforced polymers (CFRP) [2,21]. The fibre centre points are then converted into higher-order splines followed by sweeping non-overlapping 3D volumes along each spline.…”

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confidence: 99%

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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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Section: Calibration Of Local Inference Modelmentioning

confidence: 99%

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

View full text Add to dashboard Cite

show abstract

“…As a result, the parameter estimation is robust even for a very small number of projections. Most algorithms trying to estimate fiber parameters use several thousands of projection images to compute quantities on their fiber specimen [4,7,10]. However, Parametric Reconstruction (PARE) is limited by a couple of factors.…”

Section: Discussionmentioning

confidence: 99%

“…The resulting volumetric image is then further processed to characterize features, such as the fiber direction or spatial distribution of the fibers, which have an influence on B Tim Elberfeld the mechanical properties of the materials. Current methods to characterize the structural properties of GFRP from high resolution µCT images rely on a sequential work flow comprised of volumetric reconstruction from a large number of projections (typically > 1000) and subsequent fiber segmentation and image analysis [2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data—A Simulation Study

et al. 2018

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We present a new approach to estimate geometry parameters of glass fibers in glass fiber-reinforced polymers from simulated X-ray micro-computed tomography scans. Traditionally, these parameters are estimated using a multi-step procedure including image reconstruction, pre-processing, segmentation and analysis of features of interest. Each step in this chain introduces errors that propagate through the pipeline and impair the accuracy of the estimated parameters. In the approach presented in this paper, we reconstruct volumes from a low number of projection angles using an iterative reconstruction technique and then estimate position, direction and length of the contained fibers incorporating a priori knowledge about their shape, modeled as a geometric representation, which is then optimized. Using simulation experiments, we show that our method can estimate those representations even in presence of noisy data and only very few projection angles available.

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“…Trabalharam com amostras de tamanhos pequenos, podendo escolher amostras maiores, mas isto gerava um aumento no tempo de exposição e perda de resolução. Os dados segmentados mostraram uma representação do modelo sólido das fibras e da resina, utilizando um software comercialmente disponível de elementos finitos (FE) (27).…”

Section: Figura 219: Imagem 3d Do Materials Compósito Analisado (24)unclassified

Caracterização Tridimensional De Compósitos De Matriz Epóxi Reforçados Por Fibras De Vidro

ALFORD¹

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Numerical reconstruction of graphite/epoxy composite microstructure based on sub-micron resolution X-ray computed tomography

Cited by 107 publications

References 36 publications

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

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

Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data—A Simulation Study

Caracterização Tridimensional De Compósitos De Matriz Epóxi Reforçados Por Fibras De Vidro

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