An efficient Bi-level hybrid multi-objective reliability-based design optimization of composite structures

Abstract

This paper presents computationally an efficient multi-objective reliability-based design optimization (RBDO) method for composite structures with uncertain design parameters. The approach adopted is based on a novel hybrid decomposing-based multi-objective particle swarm optimization and sequential quadratic programming algorithms, which is coupled with bi-level modelling and optimization strategy of composite structures and RBDO using Cross entropy method. The reliability analysis considers the rare-event corresponding to the limit states, which is based on Tsai-Wu failure index. In addition, the growing requirements for composite structural design with a minimum weight, introduces significant research challenges in the RBDO approach as the weight and reliability are the two important opposing design requirements. To address this research challenges, the proposed approach involves both reliability and weight as objective functions. A laminated composite plate and benchmark problems were used to demonstrate the efficiency and accuracy of the proposed method. Results show that the proposed method provides computationally efficient and accurate evaluations of the performance of the design of composite structures in comparison to the conventional Monte Carlo simulation method and can provide a potential for solving large-scale multi-objective RBDO of composite structures design problems.