A Double-Stage Surrogate-Based Shape Optimization Strategy for Blended-Wing-Body Underwater Gliders

In this paper, a Double-stage Surrogate-based Shape Optimization (DSSO) strategy for Blended-Wing-Body Underwater Gliders (BWBUGs) is proposed to reduce the computational cost. In this strategy, a double-stage surrogate model is developed to replace the high-dimensional objective in shape optimization. Specifically, several First-stage Surrogate Models (FSMs) are built for the sectional airfoils, and the second-stage surrogate model is constructed with respect to the outputs of FSMs. Besides, a Multi-start Space Reduction surrogate-based global optimization method is applied to search for the optimum. In order to validate the efficiency of the proposed method, DSSO is first compared with an ordinary One-stage Surrogate-based Optimization strategy by using the same optimization method. Then, the other three popular surrogate-based optimization methods and three heuristic algorithms are utilized to make comparisons. Results indicate that the lift-to-drag ratio of the BWBUG is improved by 9.35% with DSSO, which outperforms the comparison methods. Besides, DSSO reduces more than 50% of the time that other methods used when obtaining the same level of results. Furthermore, some considerations of the proposed strategy are further discussed and some characteristics of DSSO are identified.