A co-rotational based anisotropic elasto-plastic model for geometrically non-linear analysis of fibre reinforced polymer composites: Formulation and finite element implementation

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Dean, A.; Safdar, N.; Rolfes, R.: A co-rotational based anisotropic elasto-plastic model for geometrically non-linear analysis of fibre reinforced polymer composites: Formulation and finite element implementation. In: Materials 12 (2019), Nr. 11, 1816. DOI: https://doi.org/10.3390/ma12111816

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/8810

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Sum total of downloads: 159




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Abstract: 
Geometrical non-linearity is one of the aspects to be taken into account for accurate analysis of fibre reinforced polymers (FRPs), since large displacements and rotations may be observed in many of its structural applications such as in aircraft wings and wind turbine blades. In this paper, a co-rotational formulation and implementation of an invariant-based anisotropic plasticity model are presented for geometrically non-linear analysis of FRPs. The anisotropic constitutive equations are formulated in the format of isotropic tensors functions. The model assumes an anisotropic pressure-dependent yield function, and in addition to this, a non-associated plastic potential function in order to model realistic plastic deformations in FRPs. The formulation is then cast in the co-rotational framework to consider the geometrical non-linear effects in an efficient manner. The developed model is implemented in the commercial finite element (FE) software ABAQUS/Implicit via the means of the user-defined material subroutine (UMAT). The kinematics within the co-rotational frame is explained briefly while the important aspects regarding the numerical treatment and implementation are discussed in detail. Representative numerical examples at different scales are presented to demonstrate the applicability and robustness of the proposed development.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2019
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 90 56.60%
2 image of flag of United States United States 20 12.58%
3 image of flag of China China 12 7.55%
4 image of flag of No geo information available No geo information available 7 4.40%
5 image of flag of United Kingdom United Kingdom 5 3.14%
6 image of flag of India India 4 2.52%
7 image of flag of Vietnam Vietnam 3 1.89%
8 image of flag of Hong Kong Hong Kong 3 1.89%
9 image of flag of Indonesia Indonesia 2 1.26%
10 image of flag of Austria Austria 2 1.26%
    other countries 11 6.92%

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