A numerical study on the influence of composite wrinkle defect geometry on compressive strength

Xie, Ningbo; Smith, Robert A.; Mukhopadhyay, Supratik; Hallett, Stephen R

doi:10.1016/j.matdes.2017.11.034

Cited by 84 publications

(56 citation statements)

References 25 publications

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“…For the type of wrinkles considered here, no perturbations are visible on the inside or outside face of the component and the wrinkles were always localized to the corner radius. Again, without further data on their spatial statistics of the wrinkle distribution, we make the simplifying assumption of introducing decay function in both the x 1 and x 3 direction (as also considered in other publications [17,18], defined by…”

Section: Defining a Wrinkle Prior And Likelihood Definitionmentioning

confidence: 99%

“…First, denoted π 0 (ξ), we define the prior. This is done by analyzing each of four B-Scans and fitting the wrinkle function (18) in the least-squared sense using an optimizer (e.g. fminsearch in Matlab [37]).…”

Section: Defining a Wrinkle Prior And Likelihood Definitionmentioning

confidence: 99%

“…The formation of wrinkles not only disrupts the even distribution of fibre and resin, but can significantly increase interply shear stresses triggering failure at significantly reduced loads [5,[15][16][17]. Numerical studies have used wrinkle measurements, to perform parametric studies using finite elements to explore the deterministic effect of variations of wrinkle shape on structural integrity [5,15,18]. These studies include prediction of both, failure initiation [16,17] and mix-mode propagation [5].…”

Section: Introductionmentioning

confidence: 99%

“…al. explores the compressive strength of flat plate coupons containing internal wrinkles [18]. Here, the authors define wrinkles by a cosine function enveloped within a 3D Gaussian exponential.…”

Section: Introductionmentioning

confidence: 99%

“…In light of the findings and supporting literature [15,18,19] for slope-failure dependency, an engineer's model is proposed to predict failure based on maximum misalignment.…”

Section: Introductionmentioning

confidence: 99%

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A Bayesian framework for assessing the strength distribution of composite structures with random defects

Sandhu

Reinarz

Dodwell

2018

Composite Structures

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This paper presents a novel stochastic framework to quantify the knock down in strength from out-of-plane wrinkles at the coupon level. The key innovation is a Markov Chain Monte Carlo algorithm which rigorously derives the stochastic distribution of wrinkle defects directly informed from image data of defects. The approach significantly reduces uncertainty in the parameterization of stochastic numerical studies on the effects of defects. To demonstrate our methodology, we present an original stochastic study to determine the distribution of strength of corner bend samples with random out-plane wrinkle defects. The defects are parameterized by stochastic random fields defined using Karhunen-Loéve (KL) modes. The distribution of KL coefficients are inferred from misalignment data extracted from B-Scan data using a modified version of Multiple Field Image Analysis. The strength distribution is estimated, by embedding wrinkles into high fidelity FE simulations using the high performance toolbox dune-composites from which we observe severe knockdowns of 74% with a probability of 1/200. Supported by the literature our results highlight the strong correlation between maximum misalignment and knockdown in coupon strength. This observations allows us to define a surrogate model providing fast assessment of predicted strength informed from stochastic simulations utilizing both observed wrinkle data and high fidelity finite element models.

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Section: Defining a Wrinkle Prior And Likelihood Definitionmentioning

confidence: 99%

Section: Defining a Wrinkle Prior And Likelihood Definitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…In light of the findings and supporting literature [15,18,19] for slope-failure dependency, an engineer's model is proposed to predict failure based on maximum misalignment.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Bayesian framework for assessing the strength distribution of composite structures with random defects

Sandhu

Reinarz

Dodwell

2018

Composite Structures

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Interlayer interaction characteristics of multi‐layered plain woven glass fabric in hemisphere forming

Mei

Wei

et al. 2022

Polymer Composites

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Characterizing the interlayer interaction is beneficial to mitigate the manufacturing defects in the multi‐layered fabric forming of composite. However, the interlayer interactions including the force and sliding distance, and their effects on the defect generation have not been reported yet. Here, the monolayer and multi‐layered fabric hemisphere forming were conducted by experiments. Firstly, the forming force and deformation modes at different hemisphere regions are confirmed in the monolayer fabric forming as a reference. Then, in the multi‐layered forming, the interlayer interaction is confirmed to still exist in the configuration with the same ply orientations, whereas the forming force, forming force rate, and interlayer sliding are smaller than that in the configuration with different ply orientations. In addition, with the increase of layer number, the extent of interlayer interaction is improved, which intensifies the defect from the out of plane yarn buckling to the macro wrinkle in the tensile direction. Especially, it is revealed that the tensile direction of lower layer should be avoided under the shear direction of upper layer to reduce the interlayer sliding. These results obtained here provide an important reference to the multi‐layered plain woven fabric forming.

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Microscale and mesoscale modeling for compressive failure in unidirectional carbon fiber reinforced polymer composites with random distribution of fiber misalignments

Xie,

Ning

2024

Polymer Composites

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Compressive strength and failure mode of carbon fiber reinforced polymer (CFRP) composites are affected by the severity of fiber misalignment. In this paper, numerical models based on computational micromechanics are proposed to investigate the correlation between fiber misalignment and compression failure. A single‐fiber micromodel including fiber, matrix, and interface phases is first developed to capture the influence of misalignment severity on the material failure mode. The failure longitudinal stress distribution in the fiber predicted by the micromodel indicates that the failure mode depending on the initial misalignment can be identified as uniform compression failure, compression‐bending combination collapse, and fiber buckle. A mesoscale 2D model with multiple fibers is then constructed to investigate the kink band formation. This model takes into account the distribution of fiber misalignments to capture the key geometric features of fiber misalignment that influent the compression failure in realistic composite materials at the structural scale. The results show that fiber misalignment angle amplitude, misalignment dispersion (characterized by the standard deviation), and misalignment wavelength are the key parameters of fiber misalignment, which have significant effects on compression strength and kink band geometry.Highlights Single‐fiber model to capture the effect of misalignment severity on failure mode. Multi‐fiber model with randomly distributed fiber misalignments. Failure mode depending on the severity of initial misalignment was identified. Key parameters of misalignment on compression strength and kink band geometry.

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A numerical study on the influence of composite wrinkle defect geometry on compressive strength

Cited by 84 publications

References 25 publications

A Bayesian framework for assessing the strength distribution of composite structures with random defects

A Bayesian framework for assessing the strength distribution of composite structures with random defects

Interlayer interaction characteristics of multi‐layered plain woven glass fabric in hemisphere forming

Microscale and mesoscale modeling for compressive failure in unidirectional carbon fiber reinforced polymer composites with random distribution of fiber misalignments

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