LAUSR

The available amount of input data for uncertain parameters of composite laminated plates can vary, and the uncertain parameters can be decomposed into strong statistical variables, sparse variables and interval variables. Therefore, a new reliability optimization design methodology for composite laminated plate considering these uncertainty types simultaneously is proposed. The uncertainty types of elastic material parameters are identified, and the corresponding distribution parameters are calculated based on the Akaike information criterion. The reliability indices considering three uncertainty types are calculated based on linear approximation models of first-ply failure functions. A two-level reliability optimization algorithm is proposed to calculate the optimum stacking sequence for composite laminated plate, which can satisfy the lightweight requirement and reliability constraints. Comparisons with the optimization results of the Monte Carlo simulation method in two examples of composite laminated plates demonstrate the effectiveness of the proposed algorithm in conditions with multiple uncertain parameters due to insufficient input data.