Simulation methodology for impact damage and failure of aero-engine components made of textile composites

Sitnikova, E., Pan, Q., Yu, Tianhong, Kong, W., Zhao, Xiantao, Li, Shuguang, Brooks, Richard, Long, A., Hu, Shoufeng, Wang, Z. and Zhang, J. (2015) Simulation methodology for impact damage and failure of aero-engine components made of textile composites. 20th International Conference on Composite Materials, ICCM 2015, , Copenhagen, Denmark. 19 - 24 Jul 2015.

Abstract

A multi-scale modelling strategy is developed for predicting the constitutive behaviour of textile composites under impact loading with a view to their applications in fan blade containment casings of modern turbofan aero-engines, where the critical loading condition is the impact in the event of fan blade off (FBO). At a micro- and meso-scale, the unit cell modelling concept was employed to characterize the 3D composite material with a glass-fibre woven textile reinforcement, based on the mechanical properties of the constituent materials, fibres and resin, and structure and geometry of the textile weave. All the modelling parameters involved have a clear physical meaning and are quantifiable experimentally. In addition to that, forming process modelling has been carried out in order to provide a comprehensive solution to the design problem of composite components. In particular, the influence of the variability in the internal geometry of fabric on permeability of the fabric has been investigated. Material characterization at micro- and meso-scales involves predictions of elastic and strength effective properties, and also incorporates progressive damage modelling. The validation of the models built is carried out by carrying out sanity checks and comparing the predictions with the coupon test data. Additionally, measured rate sensitivity data for the resin are presented and the procedure for assigning the rate-dependence to a textile composite is outlined. At a macro-scale, the composite is treated as a monolithic material, and its constitutive behaviour is predicted based on an artificial neural network (ANN) algorithm. Validation has been assessed with the simulation of a high rate impact on a composite plate and this is further developed to a mixed finite element model of an aero engine fan casing undergoing a blade-off event.

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Contributors

Author: E. Sitnikova

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