Probabilistic failure assessment of Fibreglass composites. (15th January 2017)

• Record Type: Journal Article
• Authors: Carpinteri, Andrea; Fernández-Canteli, Alfonso; Fortese, Giovanni; Muñiz-Calvente, Miguel; Ronchei, Camilla; Scorza, Daniela; Vantadori, Sabrina
• Is Part Of: Composite structures. Volume 160(2017)
• Page Start: 1163
• Page End: 1170
• Publication Date: 2017-01-15
• Subjects: Failure assessment -- Fibreglass composite -- Generalised Probabilistic Approach -- Weibull distribution; Composite construction -- Periodicals; Composites -- Périodiques; 624.18
• DOI: 10.1016/j.compstruct.2016.11.010
• Languages: English
• ISSNs: 0263-8223

Abstract

Highlights: The failure behaviour of short fibre-reinforced materials is analysed. The approach employed is the Generalised Probabilistic Approach (GPA) An experimental campaign is performed on a Fibreglass composite. The Primary Cumulative Distribution Function of Failure (PCDFF) is determined by GPA. A comparison between experimental failure probability values and PCDFF is provided. Abstract: In this paper, the Generalised Probabilistic Approach (GPA) recently proposed by some of the present authors is applied in order to analyse the short fibre-reinforced materials behaviour at failure. Firstly, an experimental campaign consisting of tension tests, three- and four-point bending tests is carried out on a commercial Fibreglass composite. Then, the Primary Cumulative Distribution Function of Failure (PCDFF) is determined by employing both experimental and numerical results. In particular, the PCDFF is derived in two cases: (a) by considering the specimens subjected to the above three loading conditions separately (GPA single application); (b) by collecting both the specimens subjected to tension and those subjected to three-point bending in order to constitute a unique set (GPA joint application). Finally, a comparison between experimental failure probability values and PCDFF, being the latter obtained from both single and joint application of GPA, is provided for each loading condition.