Analysis of Impact-Induced Fracture of Laminated Glass Using Multi-Objective Genetic Algorithm

The complexity of impact energy dissipation in laminated glass structures and the required model sophistication increases the computational demand of traditional computation (e.g., finite element analysis). Unlike hard computing, soft computing bypass these difficulties to offer a robust low-demand alternative. Therefore, in this study, the behavior of various laminated glass systems/configurations were investigated to anticipate the fracture patterns upon impact using genetic algorithms. Herein, recent laminated glass systems were examined, along with various laminated glass fracture models, all incorporated to develop the genes’ objective (fitness) function for evolution in a localized “near crack-tip” domain. Moreover, the influence of various interlayer materials was considered, including polyvinyl butyral (PVB), ethyl vinyl acetate (EVA), and thermoplastic polyurethane (TPU). Subsequently, a model was proposed allowing for an efficient crack path and critical impact scenario identification. Finally, the accuracy of the proposed fracture analysis and optimization scheme for laminated glass impact were evaluated against available results in the literature. Additionally, the adequacy of this approach in predicting laminated glazing responses to impact and blast loads for the various assemblies and parameters is discussed.