Abstract
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.
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Foundation item: This research was financially supported by the National Natural Science Foundation of China (Grant Nos. 51875466 and 51805436), the China Postdoctoral Science Foundation (Grant No. 2019T120941) and the China Scholarships Council (Grant No. 201806290133).
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Li, Cs., Wang, P., Qiu, Zm. et al. A Double-Stage Surrogate-Based Shape Optimization Strategy for Blended-Wing-Body Underwater Gliders. China Ocean Eng 34, 400–410 (2020). https://doi.org/10.1007/s13344-020-0036-2
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DOI: https://doi.org/10.1007/s13344-020-0036-2