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Erschienen in: Journal of Materials Science 12/2016

23.03.2016 | Original Paper

Strength prediction for bi-axial braided composites by a multi-scale modelling approach

verfasst von: Chen Wang, Yucheng Zhong, P. F. Bernad Adaikalaraj, Xianbai Ji, Anish Roy, Vadim V. Silberschmidt, Zhong Chen

Erschienen in: Journal of Materials Science | Ausgabe 12/2016

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Abstract

Braided textile-reinforced composites have become increasingly attractive as protection materials thanks to their unique inter-weaving structures and excellent energy-absorption capacity. However, development of adequate models for simulation of failure processes in them remains a challenge. In this study, tensile strength and progressive damage behaviour of braided textile composites are predicted by a multi-scale modelling approach. First, a micro-scale model with hexagonal arrays of fibres was built to compute effective elastic constants and yarn strength under different loading conditions. Instead of using cited values, the input data for this micro-scale model were obtained experimentally. Subsequently, the results generated by this model were used as input for a meso-scale model. At meso-scale, Hashin’s 3D with Stassi’s failure criteria and a modified Murakami-type stiffness-degradation scheme was employed in a user-defined subroutine developed in the general-purpose finite-element software Abaqus/Standard. An overall stress–strain curve of a meso-scale representative unit cell was verified with the experimental data. Numerical studies show that bias yarns suffer continuous damage during an axial tension test. The magnitudes of ultimate strengths and Young’s moduli of the studied braided composites decreased with an increase in the braiding angle.

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Metadaten
Titel
Strength prediction for bi-axial braided composites by a multi-scale modelling approach
verfasst von
Chen Wang
Yucheng Zhong
P. F. Bernad Adaikalaraj
Xianbai Ji
Anish Roy
Vadim V. Silberschmidt
Zhong Chen
Publikationsdatum
23.03.2016
Verlag
Springer US
Erschienen in
Journal of Materials Science / Ausgabe 12/2016
Print ISSN: 0022-2461
Elektronische ISSN: 1573-4803
DOI
https://doi.org/10.1007/s10853-016-9901-z

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