Predictive FE modelling of prepreg forming to determine optimum processing conditions

Lin, H., Long, A., Clifford, M., Wang, J. and Harrison, P. (2007) Predictive FE modelling of prepreg forming to determine optimum processing conditions. In: 10th ESAFORM Conference on Materials Forming, Zaragosa, Spain, 18-20 April 2007, pp. 1092-1097. ISBN 9780735404144 (doi:10.1063/1.2729660)

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Publisher's URL: http://dx.doi.org/10.1063/1.2729660

Abstract

In this study, FE simulations of the forming of viscous textile composite over a hemisphere and a helmet were conducted using a rate/temperature-dependent hybrid FE model in a commercial Finite Element code, Abaqus ExplicitTM. Optimum forming parameters such as the normal force distribution across the edges of a blank, blank size, forming temperature and forming rate, are predicted. Predictions are evaluated by a series of case studies of press-formed components. The results from the simulation and the experiments have good correlation and show that the forming performance of the viscous textile composite can be enhanced by optimizing the force distribution around the edge of the manufacturing tool and by careful choice of forming temperature and forming rate. The proposed model allows users to simulate all aspects of press-forming including mould geometry, processing parameters and evaluate forming performance including fibre orientation and forming defects.

Item Type:Conference Proceedings
Keywords:Forming processes, finite element analysis, optimisation, condition monitoring, composite materials, polymer fibres.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Harrison, Dr Philip
Authors: Lin, H., Long, A., Clifford, M., Wang, J., and Harrison, P.
Subjects:T Technology > TS Manufactures
T Technology > TA Engineering (General). Civil engineering (General)
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
University Centres > Glasgow Materials Research Initiative
Publisher:American Institute of Physics
ISBN:9780735404144

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