Enhanced single-loop method for efficient reliability-based design optimization with complex constraints

Abstract

Reliability-based design optimization (RBDO) has been widely implemented for engineering design optimization when considering the uncertainty. The single loop approaches (SLA) are highly efficient but is prone to converge with inappropriate results for highly nonlinear probabilistic constraints. In this paper, a novel RBDO algorithm is proposed based on single loop approach and the enhanced chaos control method, named as enhanced single-loop method (ESM). The performance of SLA is enhanced using an adaptive inverse reliability method with limited number of iterations. The adaptive step size is computed based on a merit function which is computed using the results of the new and previous iterations. The iterations of the probabilistic constraints of RBDO models are manually controlled in the range from 1 to 10 in ESM. The efficiency and accuracy of the ESM are compared through four nonlinear RBDO problems with complex constraints, including a nonlinear mathematical problem, two engineering problems and a practical complex stiffened panel example with complex buckling constraint for aircraft design. Results illustrate that the proposed ESM is more efficient and robust than the performance measure approach and reliability index approach for RBDO problems.