Failure criteria assessment of composite materials via micromechanics modelling under multiaxial loading conditions

Lei Wan*, Zahur Ullah, Brian G. Falzon

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Carbon Fibre Reinforced Polymer (CFRP) composites are widely used in many engineering applications due to their excellent design flexibility and high stiffness- and strength-to-weight ratios. However, the lack of comprehensive experimental data for the validation of computational failure models, especially for composite structures subjected to multiaxial loadings, has led to highly conservative designs. Here, high-fidelity finite element-based 3D representative volume element models are developed to analyse the failure mechanisms of IM7/8552 CFRP unidirectional (UD) composites subjected to biaxial loadings via periodic boundary conditions. The Drucker-Prager plastic damage constitutive model and cohesive zone model are utilised to simulate the mechanical response of the matrix and fibre-matrix interface, respectively. Fibres are assumed to be transversely isotropic and brittle materials. Fibres failure is predicted using the maximum principal stress criterion. Due to the transverse isotropy of the cross-section of UD lamina, nine out of fifteen loading stress combinations are selected. For the generation of failure points and representative modes, an average of ten load cases are considered for each selected biaxial stress combination. For a particular biaxial loading condition, there is main failure mode, which can be assigned to the corresponding loading case. The failure surface of the UD composite was then fitted by using the univariate spline function. The data points within this surface are defined as “safe”, and those beyond it are defined as “failure”. A database with half a million samples was used for training, validation and testing of artificial neural network (ANN). Six stress components are selected as inputs and 0/1 is selected as output (“safe/failure”). The accuracy of ANN can reach 98.5% after training.

Original languageEnglish
Title of host publicationProceedings of the 20th European Conference on Composite Materials (ECCM20): Composites meet sustainability
EditorsAnastasios P. Vassilopoulos, Véronique Michaud
PublisherMDPI AG
Pages26-33
Volume4 (D)
ISBN (Electronic)9782970161400
Publication statusPublished - 12 Dec 2022
Event20th European Conference on Composite Materials - Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Duration: 26 Jun 202230 Jun 2022
https://eccm20.org/

Publication series

NameEuropean Conference on Composite Materials: Proceedings

Conference

Conference20th European Conference on Composite Materials
Abbreviated titleECCM
Country/TerritorySwitzerland
CityLausanne
Period26/06/202230/06/2022
Internet address

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