Surrogate-based optimization method applied to multidisciplinary design optimziation architectures

During the past three decades, various multidisciplinary design optimization (MDO) architectures have been developed, using different ways of dealing with interactions between disciplines, which can be solved by optimization algorithms. In the field of aircraft design optimization, as the complexity of system increases, conventional optimization algorithms applied in MDO architecture exhibit many drawbacks, such as low efficiency, poor robustness or easily getting trapped in a local extra. In this paper, a newly developed surrogate-based optimization (SBO) method is applied to replace traditional optimization algorithms in the MDO architectures so that the efficiency of solving MDO problems can be dramatically improved. To demonstrate its effectiveness, a benchmark MDO test case and Speed Reducer MDO case are employed. It shows that the efficiency of SBO is two-order higher than that of genetic algorithm and the optimization results are better than that obtained by gradient-based algorithm. Besides, SBO is applied to the aerodynamic/structural integrated design of a transport wing in MDF architecture. The weight of the wing is reduced by 30.32% while its aerodynamic performance is retained at a cruise condition.