Representative volume element for parallel fiber bundles: Model and size convergence

Stapleton, Scott E.; Appel, Lars Florian; Simon, Jaan‐Willem; Reese, Stefanie

doi:10.1016/j.compositesa.2016.04.018

Cited by 27 publications

(5 citation statements)

References 34 publications

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“…Five periodic RVEs were generated comprised of a random dispersion of IM7 carbon fibers (fiber diameter of 6 𝜇m) in the epoxy matrix. The five microstructure renditions (Figure 3) were produced at a fiber volume fraction of 60% with the aid of a random RVE generator developed by Stapleton et al [46,47]. Perfect bonding was assumed between the fiber and the matrix.…”

Section: Rve Generationmentioning

confidence: 99%

Multiscale Process Modeling of a Carbon Fiber/Epoxy Composite for Predicting Residual Stress and Strength

Deshpande

Olaya

Krieg

et al. 2023

Preprint

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During the manufacturing of composite structures, cure shrinkage of the thermoset matrix and differential thermal contraction mismatch between the matrix and fiber reinforcement cause the formation of residual stresses, which can result in a loss in structural durability. New multiscale computational process modeling is essential for linking material chemistry, processing parameters, residual stress evolution, and optimizing mechanical performance. This study establishes a new multiscale process modeling method to accurately predict residual stresses in a unidirectional carbon fiber/epoxy composite using molecular dynamics and finite element analysis simulation techniques. The results of this work demonstrate that process-induced residual stresses have a significant impact on the composite strength in transverse tension, out-of-plane shear, and in-plane shear, with a maximum reduction in strength of 35%. Moving forward, this method can be used as a design and optimization tool for future composite structures for specific engineering applications and can provide processing parameters that can maximize desirable composite properties and/or minimize composite manufacturing energy and cost.

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Section: Rve Generationmentioning

confidence: 99%

Multiscale Process Modeling of a Carbon Fiber/Epoxy Composite for Predicting Residual Stress and Strength

Deshpande

Olaya

Krieg

et al. 2023

Preprint

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“…Stapleton et al.’s study [28] indicates that fiber volume fraction can achieve up to 90.7% by unidirectionally filling, which can improve maximum fiber volume fraction significantly and is adopted in the first stage of initial filling. During initial filling process, fibers are arranged in one sublayer in the direction of boldS1 or in another sublayer in the direction of boldS2 as shown in the schematic diagram in Figure 4.…”

Section: The Scheme Of the Algorithmmentioning

confidence: 99%

A novel algorithm for significantly increasing the fiber volume fraction in the reconstruction model with large fiber aspect ratio

Liu

Xue

et al. 2021

Journal of Industrial Textiles

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Geometric reconstruction is an important precondition for the computational micromechanics analysis of chopped fiber reinforced composites. When fiber aspect ratio increases, the maximum fiber volume fraction in reconstruction model reduces rapidly because of jamming limit, which greatly limits the application of reconstruction methods. A novel algorithm is proposed to significantly increase the fiber volume fraction in the reconstruction model of the chopped fiber reinforced composites with large fiber aspect ratio. The algorithm is made up of two stages. At the first stage, fibers are packed into the sublayers of initial filling space to preliminarily design fiber orientation distribution. The unidirectional arrangement of fibers is adopted to achieve high fiber volume fraction. At the second stage, a new multi-step fiber shaking strategy is used to introduce randomness into reconstruction model. The high fiber volume fraction over 30% is achieved within the wide range of fiber aspect ratio from 50 to 200 while the results of the existing methods are not more than 10%, showing the remarkable increase of the fiber volume fraction under large fiber aspect ratio. The proposed algorithm is verified by the statistical results of the four representative microstructural characteristics from reconstruction model and realistic material.

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“…Multi-scale mechanical modeling of thin fiber networks is a powerful technique aimed at predicting the mechanical response at the macro-mechanical level, based on properties at the meso-and microscale. The up-scaling methodology in multi-scale methods generally relies on either SVEs [18] or RVEs [25][26][27][28][29]. In the former, elements are characterized by a stochastic variation in their mechanical response.…”

Section: Multi-scale Modelingmentioning

confidence: 99%

Stochastic Constitutive Model of Isotropic Thin Fiber Networks Based on Stochastic Volume Elements

et al. 2019

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Thin fiber networks are widely represented in nature and can be found in man-made materials such as paper and packaging. The strength of such materials is an intricate subject due to inherited randomness and size-dependencies. Direct fiber-level numerical simulations can provide insights into the role of the constitutive components of such networks, their morphology, and arrangements on the strength of the products made of them. However, direct mechanical simulation of randomly generated large and thin fiber networks is characterized by overwhelming computational costs. Herein, a stochastic constitutive model for predicting the random mechanical response of isotropic thin fiber networks of arbitrary size is presented. The model is based on stochastic volume elements (SVEs) with SVE size-specific deterministic and stochastic constitutive law parameters. The randomness in the network is described by the spatial fields of the uniaxial strain and strength to failure, formulated using multivariate kernel functions and approximate univariate probability density functions. The proposed stochastic continuum approach shows good agreement when compared to direct numerical simulation with respect to mechanical response. Furthermore, strain localization patterns matched the one observed in direct simulations, which suggests an accurate prediction of the failure location. This work demonstrates that the proposed stochastic constitutive model can be used to predict the response of random isotropic fiber networks of arbitrary size.

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Representative volume element for parallel fiber bundles: Model and size convergence

Cited by 27 publications

References 34 publications

Multiscale Process Modeling of a Carbon Fiber/Epoxy Composite for Predicting Residual Stress and Strength

Multiscale Process Modeling of a Carbon Fiber/Epoxy Composite for Predicting Residual Stress and Strength

A novel algorithm for significantly increasing the fiber volume fraction in the reconstruction model with large fiber aspect ratio

Stochastic Constitutive Model of Isotropic Thin Fiber Networks Based on Stochastic Volume Elements

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