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An efficient SPH methodology for modelling mechanical characteristics of particulate composites

zheng, Z. J., Kulasegaram, S., Chen, P. and Chen, Y. Q. 2020. An efficient SPH methodology for modelling mechanical characteristics of particulate composites. Defence Technology 10.1016/j.dt.2020.04.003
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Abstract

Particulate composites are one of the widely used materials in producing numerous state-of-the-art components in biomedical, automobile, aerospace including defence technology. Variety of modelling techniques have been adopted in the past to model mechanical behaviour of particulate composites. Due to their favourable properties, particle-based methods provide a convenient platform to model failure or fracture of these composites. Smooth particle hydrodynamics (SPH) is one of such methods which demonstrate excellent potential for modelling failure or fracture of particulate composites in a Lagrangian setting. One of the major challenges in using SPH method for modelling composite materials depends on accurate and efficient way to treat interface and boundary conditions. In this paper, a master-slave method based multi-freedom constraints is proposed to impose essential boundary conditions and interfacial displacement constraints in modelling mechanical behaviour of composite materials using SPH method. The proposed methodology enforces the above constraints more accurately and requires only smaller condition number for system stiffness matrix than the procedures based on typical penalty function approach. A minimum cut-off value-based error criteria is employed to improve the computational efficiency of the proposed methodology. In addition, the proposed method is further enhanced by adopting a modified numerical interpolation scheme along the boundary to increase the accuracy and computational efficiency. The numerical examples demonstrate that the proposed master-slave approach yields better accuracy in enforcing displacement constraints and requires approximately the same computational time as that of penalty method.

Item Type: Article
Date Type: Published Online
Status: In Press
Schools: Engineering
Publisher: Elsevier
ISSN: 2214-9147
Date of First Compliant Deposit: 14 April 2020
Date of Acceptance: 1 April 2020
Last Modified: 15 Apr 2020 08:42
URI: http://orca.cf.ac.uk/id/eprint/130960

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