Discovery of Optimum Textile Composites

Home > Research > Feasibility Studies 2

Discovery of Optimum Textile Composites

Principal Investigator: Professor Andrew Long
Co-investigator: Dr Xuesen Zeng

Start Date: 1st April, 2015

Duration: 6 months

Aims

This programme aims to discover new 3D textile preform architectures for processing via resin transfer moulding. Computational modelling or “virtual testing” will be used to evaluate the utility of different textile designs within an optimization Framework to determine the best solution for a particular application. This framework will not be constrained to architectures that can be produced using existing manufacturing technologies such as weaving or braiding.

Optimum textile preforms will be realized by either modification of existing textile preforming processes or, where the potential benefits justify such an approach, by the development of entirely new, bespoke manufacturing technologies.

Within this feasibility study we will focus on the initial modelling stage to determine whether this can indeed identify new material forms which would justify the investment in a more substantial programme to achieve the above aims. Hence the objectives of this study are to:

  • Establish a computational framework for optimization of textile preforms
  • Validate the approach using model architectures produced by 3D printing

Step Change

Success in the overall programme would result in a step change in performance, leading to significant weight reductions and lower cycle times through routine use of automated manufacturing technologies. Our recent work on optimization of 3D woven preforms which produced using conventional machinery has suggested that a 50% weight saving could be achieved over standard fibre architectures for a specific application. If the fibre architecture is not constrained to orthogonal (in‐plane) yarns, we estimate that a further factor of two improvement is possible, hence we aim to achieve a 75% weight saving for structural applications.

Copyright © 2017 CIMComp