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Multiscale computational homogenisation to predict the long-term durability of composite structures

Ullah, Zahur, Kaczmarczyk, L. and Pearce, C. J. (2015) Multiscale computational homogenisation to predict the long-term durability of composite structures. In: 23rd UK Conference of the Association for Computational Mechanics in Engineering (ACME), University of Swansea, Swansea, UK. University of Swansea, Swansea, UK. 4 pp. [Conference contribution]

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URL: http://www.swansea.ac.uk/engineering/research/acme2015/programmeproceedings/proceedings/


A fully coupled hygro-thermo-mechanical computational framework based on the multi-scale computa- tional homogenisation is proposed for fibre reinforced polymers. At each macrostructure Gauss point, constitutive matrices for thermal, moisture transport and mechanical responses were calculated from the computational homogenisation of underlying representative volume element (RVE). A degradation model, developed from experimental data relating evolution of mechanical properties over time for a given exposure temperature and moisture concentration was also incorporated in the proposed compu- tational framework. A unified approach is used to impose the RVE boundary conditions, which allows convenient switching between displacement, traction and periodic boundary conditions. A plain weave textile composite RVE consisting of matrix and yarns embedded in the matrix is considered in this case. Both matrix and yarns within the RVE were considered as isotropic materials. Furthermore, the compu- tational framework utilises the flexibility of hierarchic basis functions and distributed memory parallel programming.

Item Type:Conference contribution (Paper)
Keywords:Multiscale computational homogenisation; Hygro-thermo-mechanical analysis; Fibre rein- forced polymer; Textile composites
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Engineering
ID Code:38578
Deposited By: Dr Zahur Ullah
Deposited On:05 Sep 2017 10:58
Last Modified:17 Oct 2017 16:31

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