In situ statistical measurement of local morphology in carbon-epoxy composites using synchrotron X-ray computed tomography

Rosini, Sebastian; Mavrogordato, Mark; Egorova, O.; Matthews, Emily S.; Jackson, Samuel E.; Spearing, S.M.; Sinclair, Ian

doi:10.1016/j.compositesa.2019.105543

Cited by 25 publications

(26 citation statements)

References 45 publications

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“…Characterizing volumetric material deformation and damage, is however, notoriously challenging, due to the opacity of the materials, the three-dimensional (3D) multi-scale nature of damage, the coupling of multiple micromechanisms and the difficulty of distinguishing damage caused by load from cutting and polishing artefacts associated with traditional metallographic approaches. A significant step forward has been achieved in recent years by the use of X-ray Computed Tomography (CT) combined with in situ loading to identify detailed sequences of damage accumulation down to fibre-level, in 3D, within the bulk of representative materials under load [3], [4], [5], [6], [7]. As a natural evolution, the coupling of CT with Digital Volume Correlation (DVC) was identified.…”

Section: Introductionmentioning

confidence: 99%

“…A significant step forward has been achieved in recent years by the use of X-ray computed tomography (CT) combined with in situ loading to identify detailed sequences of damage accumulation down to fibre level, in 3D, within the bulk of representative materials under load. [3][4][5][6][7] As a natural evolution, the coupling of CT with Digital Volume Correlation (DVC) was identified.…”

Section: Introductionmentioning

confidence: 99%

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Fibre direction strain measurement in a composite ply under pure bending using Digital Volume Correlation and Micro-focus Computed Tomography

Schöberl

Mavrogordato

Sinclair

et al. 2020

Journal of Composite Materials

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This paper presents an experimental demonstration and validation of high-resolution three-dimensional experimental strain measurement using Digital Volume Correlation (DVC) on Carbon Fibre-Reinforced Polymers, via through-thickness strain analysis under a state of pure bending. To permit the application of DVC to displacements and/or strain measurements parallel to the fibre direction in well-aligned unidirectional materials at high volume fractions, a methodology was developed for the insertion of sparse populations of 400 nm BaTiO3 particles within the matrix to act as displacement trackers (i.e. fiducial markers). For this novel material system, measurement sensitivity and noise are considered, along with the spatial filtering intrinsic to established DVC data processing. In conjunction with Micro-focus Computed Tomography, the technique was applied to a simple standard specimen subjected to a four-point flexural test, which resulted in a linear strain distribution through the beam thickness. The high-resolution, fibre-level strain distributions (imaged at a voxel resolution of ∼0.64 µm) were compared against the classical beam theory (Euler–Bernoulli) in incrementally decreasing averaging schemes and different sub-set sizes. Different sampling and averaging strategies are reported, showing that DVC outputs can be obtained that are in very good agreement with the analytical solution. A practical lower limit for the spatial resolution of strain is discerned for the present materials and methods. This study demonstrates the effectiveness of DVC in measuring local strains parallel to the fibre direction, with corresponding potential for calibration and validation of micromechanical models predicting various fibre-dominated damage mechanisms.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fibre direction strain measurement in a composite ply under pure bending using Digital Volume Correlation and Micro-focus Computed Tomography

Schöberl

Mavrogordato

Sinclair

et al. 2020

Journal of Composite Materials

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“…These clusters consist of multiple interacting fibre breaks, prior to the onset of unstable failure. 1,4,5,[17][18][19][20] • The propagation of a 'critical cluster' in an unstable, self-sustaining manner. This is associated with the catastrophic failure of the composite.…”

Section: Introductionmentioning

confidence: 99%

“…This is associated with the catastrophic failure of the composite. 9,13,18,20 Acknowledging that damage in composite materials is a three-dimensional (3D) problem, and in the endeavour to validate these underpinning assumptions of fibre failure-based strength theories, recent years have seen a departure from 'traditional' damage assessment methods (e.g. optical microscopy and material sectioning, 21 acoustic emission, 2,6,21 scanning electron microscopy 22 etc.)…”

Section: Introductionmentioning

confidence: 99%

“…6,[24][25][26] The pairing of SRCT with in situ tensile loading has led to a paradigm shift in identifying detailed sequences of damage accumulation down to fibre-level, in 3D, within the bulk of real engineering materials under load. 1,4,19,20,27,28 As such, considerable progress was made in terms of model validation 29 by specifically studying the evolution of breaks with ongoing loading. 1,4,19,20 Recently, developments have seen the use of uninterrupted scan strategies 19 (but at the expense of image quality), mainly aimed at capturing the critical nature of damage required to trigger final failure.…”

Section: Introductionmentioning

confidence: 99%

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A novel particle-filled carbon-fibre reinforced polymer model composite tailored for the application of digital volume correlation and computed tomography

Schöberl

Breite

Rosini

et al. 2020

Journal of Composite Materials

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This paper presents the development of novel Carbon-Fibre Reinforced Polymer (CFRP) laminates, tailored for the application of Digital Volume Correlation (DVC) and Computed Tomography (CT) to experimental mechanics analyses of these materials. Analogous to surface-based Digital Image Correlation (DIC), DVC is a relatively novel volumetric method that utilizes CT data to quantify internal three-dimensional (3D) displacements and implicit strain fields. The highly anisotropic and somewhat regular/self-similar microstructures found in well-aligned unidirectional (UD) materials at high fibre volume fractions are intrinsically challenging for DVC, especially along the fibre direction at microstructural length-scales on the order of a few fibre diameters. To permit the application of DVC to displacement and/or strain measurements parallel to the fibre orientation, the matrix was doped with a sparse population of sub-micrometre particles to act as displacement trackers ( i.e. fiducial markers). Barium titanate particles (400 nm, ∼1.44 vol. %) were found to offer the most favourable compromise between contrast in CT images and the ability to obtain a homogeneous distribution in 3D space with sufficient particle compactness for local DVC analyses. This property combination was selected following an extensive Micro-focus Computed Tomography (µCT)-based qualitative assessment on a wide test matrix, that included 38 materials manufactured with a range of possible particle compositions, mean sizes and concentrations. By comparing the tensile behaviour of the particle-adapted material alongside its particle-free counterpart, we demonstrate through the application of in situ Synchrotron Radiation Computed Tomography (SRCT) that the macro- and micromechanical responses of the newly developed CFRP are consistent with standard production materials indicating its suitability as a model system for mechanistic investigations.

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Deep Learning Unlocks X‐ray Microtomography Segmentation of Multiclass Microdamage in Heterogeneous Materials

Kopp

Joseph

et al. 2022

Advanced Materials

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Disparate natural [9,10] and synthetic [11][12][13][14] constituent materials discoveries, concomitant with the growing diversity of combinatory processing techniques for design of microstructure [15,16] and interphase, [17,18] has expanded both the range and knowledgebase of heterogeneous and composite materials, leading to synergistic mechanical property enhancements in bulk stiffness, strength, and toughness over traditional homogeneous engineering materials, [19][20][21] while often also permitting interdisciplinary strategies for multifunctionality (thermal, electrical, optical, etc.). [22,23] Several cross-cutting research themes have emerged for mechanical property engineering via composite nano-and microstructural heterogeneity and anisotropy, including additive manufacturing, [24][25][26] biomimetics, [27][28][29] and hybrid advanced composites. [30,31] However, incomplete understanding of complex structure-property relationships, [32,33] particularly progressive damage in tough heterogeneous systems built from brittle constituents, has emerged as a unifying theme limiting further performance enhancement among the breadth of cutting-edge advanced materials for structural applications. Fundamental knowledge of heterogeneous material mechanics across scales, particularly as related to "failure," strongly limits performance predictive capabilities as well as rational nano/microstructural design toward optimization. [34][35][36] Motivated by ongoing failure prediction challenges faced globally by academia, government, and industry, aerospace-grade advanced composites exemplify the reality of costly (≈$100M [37] and up to 20 years [38,39] for new materials insertion), experimentally driven qualification campaigns, incurring materials design restrictions and conservative safety margins that undercut theoretical structural efficiency. [40,41] The next advances in mechanical performance understanding are underpinned by higher-fidelity experimental characterizations (especially temporal data) [33] of complex failure processes comprising multiscale, multimodal (multiclass) interacting progressive damage [23,35,36] that inform and validate predictive models for design. Relative to conventional destructive microscale damage characterization techniques [42] like optical and electron microscopy (2D) and acoustic signaling/scanning (low resolution, <3D), synchrotron radiation computed Four-dimensional quantitative characterization of heterogeneous materials using in situ synchrotron radiation computed tomography can reveal 3D sub-micrometer features, particularly damage, evolving under load, leading to improved materials. However, dataset size and complexity increasingly require time-intensive and subjective semi-automatic segmentations. Here, the first deep learning (DL) convolutional neural network (CNN) segmentation of multiclass microscale damage in heterogeneous bulk materials is presented, teaching on advanced aerospace-grade composite damage using ≈65 000 (trained) human-segmented tomograms. The trained CNN mach...

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In situ statistical measurement of local morphology in carbon-epoxy composites using synchrotron X-ray computed tomography

Cited by 25 publications

References 45 publications

Fibre direction strain measurement in a composite ply under pure bending using Digital Volume Correlation and Micro-focus Computed Tomography

Fibre direction strain measurement in a composite ply under pure bending using Digital Volume Correlation and Micro-focus Computed Tomography

A novel particle-filled carbon-fibre reinforced polymer model composite tailored for the application of digital volume correlation and computed tomography

Deep Learning Unlocks X‐ray Microtomography Segmentation of Multiclass Microdamage in Heterogeneous Materials

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