Analysis of 3D random chopped fiber reinforced composites using FEM and random sequential adsorption

Pan, Yun; Iorga, Lucian; Pelegri, Assimina A.

doi:10.1016/j.commatsci.2007.12.016

Cited by 126 publications

(69 citation statements)

References 27 publications

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“…Various particle shapes have been considered for this type of geometry generation, including spherical or spherocylindrical particles [Coelho et al 1997;Williams and Philipse 2003] or cylindrical rods [Williams and Philipse 2003;Duschlbauer et al 2006;Kari et al 2007;Pan et al 2007]. The specific algorithm's application and implementation on random chopped fiber composites are described in detail elsewhere [Pan et al 2007] and we will only briefly outline it here, for the sake of completeness.…”

Section: Microscale Geometry Generationmentioning

confidence: 99%

“…No intersection between two cylinders is accepted, with the minimum distance between cylinders being set to 5% of the cylinder radius, to avoid both the generation of excessively steep stress gradients and meshing difficulties. An investigation of the influence of the minimum distance on the local stress fields is detailed in [Pan et al 2007]. A provision is made in the current algorithm for the generation of periodic RVE geometries, that is, fiber arrangements that ensure material continuity across the boundaries when multiple RVEs are aggregated for the generation of a macrostructure.…”

Section: Microscale Geometry Generationmentioning

confidence: 99%

See 1 more Smart Citation

Numerical characterization of material elastic properties for random fiber composites

Iorga

Pan

Pelegri

2008

JOMMS

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This paper presents a numerical investigation of the material elastic properties for short-length mostly in-plane random fiber composites, based on microscale geometrical modeling. The particular case considered is that of materials in which the majority of fibers' orientations are contained or slightly deviate from a dominant plane. Representative volume elements for two types of random fiber composite material geometries with different fiber aspect ratios and volume fractions are generated using a novel technique. The elastic properties of the equivalent homogeneous material are determined using direct three-dimensional finite element analysis. A windowing-type analysis is employed to investigate the influence of the fiber distribution homogeneity on the homogenized elastic properties. The results are compared and validated using two alternative approaches -first, by orientation averaging of the stiffness tensor of the equivalent unidirectional composite determined by direct FEM analysis and, second, by employing the laminated random strand method.

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Section: Microscale Geometry Generationmentioning

confidence: 99%

Section: Microscale Geometry Generationmentioning

confidence: 99%

Numerical characterization of material elastic properties for random fiber composites

Iorga

Pan

Pelegri

2008

JOMMS

Self Cite

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“…Three dimensional hard models have previously been developed [27,28] using continuum elements to represent the fibre bundles. Bundles were assumed to be straight with circular cross section, limiting the maximum achievable volume fraction to ~13.5%.…”

Section: Introductionmentioning

confidence: 99%

3D geometric modelling of discontinuous fibre composites using a force-directed algorithm

Harper

Qian

Luchoo

et al. 2016

Journal of Composite Materials

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A geometrical modelling scheme is presented to produce representative architectures for discontinuous fibre composites, enabling downstream modelling of mechanical properties. The model generates realistic random fibre architectures containing high filament count bundles (>3k) and high (~50%) fibre volume fractions. Fibre bundles are modelled as thin shells using a multi-dimension modelling strategy, in which fibre bundles are distributed and compacted to simulate pressure being applied from a matched mould tool. FE simulations are performed to benchmark the in-plane mechanical properties obtained from the numerical model against experimental data, with a detailed study presented to evaluate the tensile properties at various fibre volume fractions and specimen thicknesses. Tensile modulus predictions are in close agreement (less than 5% error) with experimental data at volume fractions below 45%.Ultimate tensile strength predictions are within 4.2% of the experimental data at volume fractions between 40%-55%. This is a significant improvement over existing 2D modelling approaches, as the current model offers increased levels of fidelity, capturing dominant failure mechanisms and the influence of out-of-plane fibres.

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“…The former [10] can overcome the limitation of hard-core model [14] . However, when the fibre volume content was reached, the fibre may not be extended to the corner of RVE and it was easy to appear in the middle or somewhere centralized.…”

Section: The Random Sequence Generation Algorithm (Rsga)mentioning

confidence: 99%

“…The algorithm generates fibre distance and fibre radius to model the micro structure with statistical data through analyzing 2D material cross-sectional images. Then, an equivalent model is re-established based on both classic hard-core hypothesis model [14] and the SEM images which represent actual fibre distribution.…”

Section: The Random Sequence Generation Algorithm (Rsga)mentioning

confidence: 99%

The mechanical property prediction of fibre-reinforced composite materials based on a new generating random fibre distributions method

Huang¹,

Zhao

Dai³

et al. 2015

Proceedings of the 3rd International Conference on Material, Mechanical and Manufacturing Engineering

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This paper focuses on the issues of the fibre-reinforced composite material microstructure and presents a new numerical method to generate random fibre distributions and predict the macroscopic mechanical properties of composite materials based on the represent volume element (RVE). The method, named the random sequence generation algorithm (RSGA), obtains fibre radius distributions and positional relationships by image processing to generate a statistical equivalence RVE effectively. On this basis, the composite material microstructure finite element model is established to predict its macroscopic elastic properties by Python language in ABAQUS. Comparative analysis shows the algorithm is in good agreement with experimental results and has the statistical equivalence herein. The research of this paper on the algorithm for composite materials of fibre distributions provides a useful alternative to generate random numerical models that can be used in micromechanical analysis of composite materials.

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Analysis of 3D random chopped fiber reinforced composites using FEM and random sequential adsorption

Cited by 126 publications

References 27 publications

Numerical characterization of material elastic properties for random fiber composites

Numerical characterization of material elastic properties for random fiber composites

3D geometric modelling of discontinuous fibre composites using a force-directed algorithm

The mechanical property prediction of fibre-reinforced composite materials based on a new generating random fibre distributions method

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