Structural optimization design of typical adhesive bonded sandwich T-joints based on progressive damage analysis and multi-island genetic algorithm

This paper deals with the optimization of multi-laminate structures by Multi-Island Genetic Algorithm (MIGA) coupled with CAE solver. The optimization problem is a compound problem which relates to size optimization for object structure and stacking sequence optimization for variable-thickness composite laminates. Taking a typical adhesive bonded sandwich T-joint under a reference pull-off load as an instance object and establishing strength conditions on the basis of progressive damage analysis, optimum design is carried out with the total weight of joint as the target function. Progressive damage model (PDM) methodology and cohesive zone model (CZM) methodology are employed to develop an exact finite element model of the object structure. Classified failure criteria are chosen to investigate the capability of the joint in bearing the applied load. The optimization procedure on the typical adhesive bonded sandwich T-joint showed 34.24% weight reduction compared to the initial laminated structure. On the basis of history data, the study further brings out the influence of design variables on some main constraint variables.

Automated summary

This paper discusses the optimization of multi-laminate structures using MIGA algorithm and CAE solver, with a focus on a typical adhesive bonded sandwich T-joint. By establishing a finite element model based on progressive damage analysis and cohesive zone model, the optimization procedure successfully achieved a weight reduction of 34.24% compared to the initial structure. The study also highlights the influence of design variables on main constraint variables based on historical data.