Virtual model-aided reliability analysis considering material and geometrical uncertainties for elastic metamaterials

Abstract

Elastic metamaterials (EMMs) have enormous potential to be employed in real-world engineering, including transport, aerospace, civil engineering, due to their exceptional wave-manipulating capabilities. The system uncertainties raised by various factors in EMMs would lead to fluctuations in wave attenuation performance. Without thoroughly considering the system uncertainties, severe structural failure may occur. Thus, to provide possible access to quantifying the structural reliability involving material and geometrical uncertainties separately and simultaneously, a virtual model-aided framework is proposed. A recently developed virtual modelling technique, namely the Extended Support Vector Regression (X-SVR), has been adopted to generate virtual models, as alternatives to the original physical relationships between the system parameters and the concerned bandgap characteristics for EMMs. By implementing the sampling-based method on the established virtual models, sufficient statistical information and the structural reliability of concerned structural responses are estimated effectively and efficiently. In addition, the sensitivity analysis and information update can be easily executed on the established virtual models. Furthermore, the computational efficiency, accuracy, and robustness of the proposed virtual model-aided framework are demonstrated by numerical investigation. Convincingly, this advanced framework would significantly benefit the reliability-based analysis, design, and fabrication of EMMs in multi-disciplinary engineering applications.