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Statistical analysis of composites reinforced with randomly distributed fibers using a meshless method

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Abstract

This paper adopts a meshless method that combines the moving least-squares approximation and Galerkin weak form to investigate the mechanical properties of unidirectional fiber-reinforced composites under a lateral load. The degree of nonuniformity is adopted to quantify the spatial distribution of randomness during simulation, and then the numerical implementation is developed to generate a representative volume element (RVE) model with random distribution of fibers. A statistical analysis is carried out by using three descriptors, that is, inter-fiber distance, second-order intensity function and radial distribution function. Numerical examples are presented to illustrate the accuracy of the proposed multiscale meshless method, and excellent agreement is achieved in comparison with experiments and the finite element method. Finally, the performance of the proposed numerical technique is evaluated by considering the effects of RVE size, node influence domain, degree of nonuniformity and fiber volume fraction separately.

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Acknowledgements

The authors gratefully acknowledge the support ofNationalNatural Science Foundation of China (NNSFC) through Grant No. 11702006 and the General Program of Science and Technology Development Project of Beijing Municipal Education Commission of China through Grant No. KM201810005003.

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Authors and Affiliations

  1. Beijing Key Laboratory of Nonlinear Vibrations and Strength of Mechanical Structures, College of Mechanical Engineering, Beijing University of Technology, Beijing, 100124, China

    J. F. Wang, D. S. Huang & W. Zhang

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  1. J. F. Wang
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  2. D. S. Huang
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  3. W. Zhang
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Correspondence to W. Zhang.

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Wang, J.F., Huang, D.S. & Zhang, W. Statistical analysis of composites reinforced with randomly distributed fibers using a meshless method. Acta Mech 230, 2309–2324 (2019). https://doi.org/10.1007/s00707-019-02400-3

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  • DOI: https://doi.org/10.1007/s00707-019-02400-3

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