An Efficient Surrogate-Based Optimization Method for BWBUG Based on Multifidelity Model and Geometric Constraint Gradients. (24th August 2021)

• Record Type: Journal Article
• Authors: Zhang, Daiyu; Zhang, Bei; Wang, Zhidong; Zhu, Xinyao
• Other Names: Cunkas Mehmet Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2021(2021)
• Publication Date: 2021-08-24
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2021/6939863
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : Performing shape optimization of blended-wing-body underwater glider (BWBUG) can significantly improve its gliding performance. However, high-fidelity CFD analysis and geometric constraint calculation in traditional surrogate-based optimization methods are expensive. An efficient surrogate-based optimization method based on the multifidelity model and geometric constraint gradient information is proposed. By establishing a shape parameterized model, deriving analytical expression of geometric constraint gradient, constructing multifidelity surrogate model, the calculation times of high-fidelity CFD model and geometric constraints are reduced during the shape optimization process of BWBUG, which greatly improve the optimization efficiency. Finally, the effectiveness and efficiency of the proposed method are verified by performing the shape optimization of a BWBUG and comparing with traditional surrogate-based optimization methods.