Prediction of size effects in open-hole laminates using only the Young's modulus, the strength, and the R-curve of the 0 degrees ply

• Type: Article in International Scientific Journal
• Date: 2017

Authors

Furtado, C (Author) FEUP; Arteiro, A (Author) FEUP; Bessa, MA (Author) Other; Wardle, BL (Author) Other; Camanho, PP (Author) FEUP

Journal

Title: Composites Part A: Applied Science and Manufacturing

Vol. 101

Pages: 306-317

ISSN: 1359-835X

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 19 Citations

Scopus - 22 Citations

Other information

Authenticus ID: P-00N-2VG

DOI: 10.1016/j.compositesa.2017.04.014

Abstract (EN): Advanced non-linear Finite Element models for the strength prediction of composite laminates normally result in long computing times that are not suitable for preliminary sizing and optimisation of structural details. Macro -mechanical analytical models, in spite of providing quick predictions, are based on properties determined from tests performed at the laminate level, making preliminary design and optimisation of composite structures still too costly in terms of testing requirements. To overcome these disadvantages, an analytical framework is proposed to predict the notched response of balanced carbon fibre -reinforced polymer laminates using only three ply properties as inputs: the longitudinal Young's modulus, the longitudinal strength, and the R-curve of the 0 degrees plies. This framework is based on invariant -based approaches to predict the stiffness and the strength of general laminates, and an analytical model to estimate the 7Z -curve of balanced laminates. These laminate properties are then used in a Finite Fracture Mechanics model to predict size effects. The predictions for open-hole tension and compression tests are compared with experimental results obtained from the literature for five different material systems. Good agreement is observed considering that only three ply properties are used as inputs for the analytical framework

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12