An XFEM/CZM based inverse method for identification of composite failure parameters. (June 2015)

• Record Type: Journal Article
• Authors: Bouhala, Lyazid; Makradi, Ahmed; Belouettar, Salim; Younes, Anis; Natarajan, Sundararajan
• Is Part Of: Computers & structures. Volume 153(2015)
• Page Start: 91
• Page End: 97
• Publication Date: 2015-06
• Subjects: Carbon fibre -- Mechanical properties -- Computational modelling -- Mechanical testing; Structural engineering -- Data processing -- Periodicals; Electronic data processing -- Structures, Theory of -- Periodicals; 624.171
• DOI: 10.1016/j.compstruc.2015.02.035
• Languages: English
• ISSNs: 0045-7949

Abstract

Highlights: Inverse numerical model to identify unidirectional composites failure parameters. Robust and accurate scheme validated by experimental results. Flexible to use non-standardized experiments data or other optimisation techniques. Reduced computation time thanks to the XFEM. Abstract: An experimental–numerical methodology for identification of mode I failure parameters, namely the critical strain energy release rate ( G Ic ) and the strength ( σ c ) of unidirectional carbon/epoxy composite is proposed. Using an inverse procedure, the experimental results of a double cantilever beam (DCB) test are used in conjunction with a counterpart extended finite element method (XFEM) cohesive zone model (CZM). In the developed numerical model, the notch and the crack path are located and enriched implicitly by a level set function and the crack propagation is controlled by a bi-linear cohesive law. The cost function accounts for the error between the numerical and the experimental results, and it is minimised in a least squares sense by updating the values of the two independent parameters. The determined critical strain energy release rate is then compared with the one obtained using the corrected beam theory (CBT), and the identified strength is compared with the one estimated experimentally. Globally, the results are very well in agreement and the proposed methodology seems to be efficient to determine accurately the composite failure parameters.