A Collaboratively Iterative Sequential Approximate Optimization Method for Aerodynamic Optimization
Publication: Journal of Aerospace Engineering
Volume 37, Issue 2
Abstract
The sequential approximate optimization (SAO) method is widely adopted in aircraft optimization design, whose further improvement in efficacy and efficiency has encountered bottlenecks. In this paper, a collaboratively iterative sequential approximate optimization (CISAO) method with field metamodel (FM) accelerating computational fluid dynamics (CFD) is proposed for aerodynamic optimization problems to enhance the coupling between metamodels and CFD high-fidelity models (HFMs). In this method, the field metamodel is used to predict the flow field distributions with respect to the design variables to accelerate the numerical solution of CFD HFMs. Two benchmark aerodynamic optimization cases are performed to validate the proposed method. The time costs for single CFD HFMs in the two test cases are shortened by 37.76% and 12.11%, respectively, and the total time costs of the two test cases are shrunk by 64.11% and 44.47% compared with the conventional SAO method. The optimization results indicate that the proposed method significantly reduces the time costs and improves the optimization efficiency. The proposed method shows a promising prospect in aircraft optimization design.
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Data Availability Statement
Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research was sponsored by National Natural Science Foundation of China (Grant No. 52005502), the science and technology innovation Program of Hunan Province (Grant No. 2020RC2035), and the Research Project of National University of Defense Technology (Grant No. ZK19-11).
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© 2024 American Society of Civil Engineers.
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Received: Mar 23, 2022
Accepted: Oct 20, 2023
Published online: Jan 3, 2024
Published in print: Mar 1, 2024
Discussion open until: Jun 3, 2024
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