Inverse parameter identification framework for cohesive zone models based on multi-island genetic algorithm

Abstract

Composite interfaces are commonly simulated by cohesive zone models with the key challenge being the calibration of interfacial parameters. A novel inverse identification framework is presented in this paper to determine the interface parameters of cohesive zone models. This approach employs the multi-island genetic algorithm to obtain the key parameters of cohesive zone model which can reproduce the experimental observations. Utilizing two independent metrics, namely the load-displacement response and the debonding length history, an objective function is formulated to give the framework inherent robustness. The interface debonding length is used to uniquely determine the debonding properties of the specimen. To demonstrate the feasibility of the proposed framework, the strength-based cohesive zone model is taken as an example. The inverse algorithm is adopted to identify the interface parameters of both the double cantilever beam (DCB) experiments and the fixed-ratio mixed-mode (FRMM) tests. The robustness, accuracy and sensitivity of the framework are validated through the double cantilever beam test. The findings indicate that the numerical results align closely with the experimental data, confirming that the interface parameters identified by the proposed framework can reproduce the experimental results.