Generating virtual textile composite specimens using statistical data from micro-computed tomography: 1D tow representations for the Binary Model

Blacklock, Matthew; Bale, Hrishikesh; Begley, Matthew R.; Cox, Brian N.

doi:10.1016/j.jmps.2011.11.010

Cited by 98 publications

(109 citation statements)

References 24 publications

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“…As for the angle interlock weave of Blacklock et al, 14 no significant inter-tow correlations for the same genus are presented. Hence, the plain-weave composites do not exhibit significant inter-tow correlations.…”

Section: Generation Of Tow Centroid Deviations With the Markov Chain mentioning

confidence: 97%

“…14,23 On the basis of statistical parameters defined in Table 1, two 2 3 2 unit cells are generated for the plain-weave DLR-XT laminate. The difference between the two finite element models lies in the tow waviness, where the systematic model has no waviness and the stochastic model has random waviness, as shown in Figures 6 and 7.…”

Section: Unit Cell Binary Model Generated From Virtual Specimen Genmentioning

confidence: 99%

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Effects of stochastic tow waviness on stiffness and strength of plain-weave ceramic matrix composites

Chen

Blacklock

Zhang

et al. 2017

Advances in Mechanical Engineering

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This article presents the development of a finite element model, which considers stochastic tow waviness using a Markov Chain algorithm and non-linear material properties using Binary Model, to predict the stress-strain and fracture behaviour of plain-weave ceramic matrix composites under uniaxial extension. The stochastic waviness is described by fluctuations in the centroid coordinates of tow positioning. The tow deviations are generated by marching sequentially from one grid point to next along a tow path. The deviations depend only on the deviation of the previous point using a probability transition matrix. A non-linear orthotropic constitutive model was implemented in a commercial finite element code Abaqus using a user-defined subroutine. Two 2 3 2 unit cell models of a plain-weave ceramic matrix composite laminate are created using stochastic tow elements generated by the virtual specimen generator, which was developed on the basis of the Markov Chain algorithm. A comparison has been made between the systematic and stochastic models to assess the effects of stochastic tow waviness on the stiffness and strength of the laminate. The numerical results have been validated by the comparison of predictions with the experimental data. The stochastic model which considers random waviness correlates well with the experimental data.

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Section: Generation Of Tow Centroid Deviations With the Markov Chain mentioning

confidence: 97%

Section: Unit Cell Binary Model Generated From Virtual Specimen Genmentioning

confidence: 99%

Effects of stochastic tow waviness on stiffness and strength of plain-weave ceramic matrix composites

Chen

Blacklock

Zhang

et al. 2017

Advances in Mechanical Engineering

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“…When cross-correlation between adjacent tows are not taken into account, the procedure by Blacklock et al [17] is used. The representation is done using a Markov process.…”

Section: Modelling Strategymentioning

confidence: 99%

Identification of Uncertainty and Quantification of Variability in Woven Composite Materials Based on Carbon Fibre Weaves

Vanaerschot¹,

Lomov²,

Moens³

et al. 2015

Proceedings of the 1st International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECO

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Abstract. Composite materials are created as a quite complex architecture which includes a fibre reinforcement structure and matrix material. Many material parameters play a role when composite structures are modelled, e.g. in finite element models. In addition to the properties of the raw fibre and matrix materials which are used, also geometrical parameters have a significant effect on structural characteristics.With the multitude of model parameters which have to be taken into account, the effect of uncertainty becomes even more complicated. For many parameters the range or the distribution is not well known. The objective of this paper is to develop a consistent approach to identify and to quantify the effect of uncertainty and variability as concisely as possible, in order to allow for structural analysis which takes into account variability in a realistic way.In addition to the identification of probability distribution functions which are established, parameter correlations between different positions along a tow and between two tows are also determined.

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“…indicates an average value. The periodic trends are compiled by exploiting the nominal translational invariance of the textile: Data from all points on nominally equivalent tows throughout the specimen are collated onto a single periodic cycle of that type of tow, a process termed reference period collation (9,74). This process maximizes the information content of the relatively small specimens that can be imaged at high resolution.…”

Section: Characteristics At the Scale Of The Unit Cellmentioning

confidence: 99%

Stochastic Virtual Tests for High-Temperature Ceramic Matrix Composites

Cox

Bale

Begley

et al. 2014

Annu. Rev. Mater. Res.

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We review the development of virtual tests for high-temperature ceramic matrix composites with textile reinforcement. Success hinges on understanding the relationship between the microstructure of continuous-fiber composites, including its stochastic variability, and the evolution of damage events leading to failure. The virtual tests combine advanced experiments and theories to address physical, mathematical, and engineering aspects of material definition and failure prediction. Key new experiments include surface image correlation methods and synchrotron-based, micrometer-resolution 3D imaging, both executed at temperatures exceeding 1,500• C. Computational methods include new probabilistic algorithms for generating stochastic virtual specimens, as well as a new augmented finite element method that deals efficiently with arbitrary systems of crack initiation, bifurcation, and coalescence in heterogeneous materials. Conceptual advances include the use of topology to characterize stochastic microstructures. We discuss the challenge of predicting the probability of an extreme failure event in a computationally tractable manner while retaining the necessary physical detail. 17.1

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Generating virtual textile composite specimens using statistical data from micro-computed tomography: 1D tow representations for the Binary Model

Cited by 98 publications

References 24 publications

Effects of stochastic tow waviness on stiffness and strength of plain-weave ceramic matrix composites

Effects of stochastic tow waviness on stiffness and strength of plain-weave ceramic matrix composites

Identification of Uncertainty and Quantification of Variability in Woven Composite Materials Based on Carbon Fibre Weaves

Stochastic Virtual Tests for High-Temperature Ceramic Matrix Composites

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