4.5 Article

Multi-scale integrated modelling for high performance flexible materials

期刊

COMPUTATIONAL MATERIALS SCIENCE
卷 65, 期 -, 页码 276-286

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.commatsci.2012.07.017

关键词

Multi-scale modelling; Textile yarns and fabrics; Mechanical properties

资金

  1. Technology Strategy Board's collaborative research and development programme [TP/5/MAT/6/I/H 0558C]
  2. Technology Strategy Board
  3. EPSRC [EP/I033513/1] Funding Source: UKRI
  4. Engineering and Physical Sciences Research Council [EP/I033513/1] Funding Source: researchfish

向作者/读者索取更多资源

Highly structured and hierarchal textiles may be modelled at three scales, ranging from micro modelling of individual fibres within a yarn via meso-scale modelling of a fabric unit cell through to macro-scale modelling of a whole product. The performance of the product can be designed and optimised effectively by variation of the structure at every level. This paper presents an integration of the fibre-yarn, yarn-fabric models. The micro-scale model is developed using an energy-based argument combined with elastica methods to incorporate non-linear frictional behaviour. The meso-scale model is developed using the finite element method, with the yarn modelled as a continuum. The output of the micro-scale model is used to determine constitutive materials properties at the meso-scale model for fabric deformation. The main features of this modelling approach are that many critical design parameters of a yarn and a fabric are being addressed and the friction is incorporated at each scale since inter-fibre and inter-yarn friction may be directly affected by finishing treatments. This paper shows how predictions at the micro scales can pass up the hierarchy to the meso scale to enable designers/engineers to understand and quantify how changes in yarn properties and fabric architectures influence the performance of the fabric, thereby facilitating the design and optimisation of fabric properties by variation of its constituent structural components. (C) 2012 Elsevier B.V. All rights reserved.

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