Study on Optimization Design of Airfoil Transonic Buffet with Reinforcement Learning Method Article Swipe
Hao Chen
,
Chuanqiang Gao
,
Jifei Wu
,
Kai Ren
,
Weiwei Zhang
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/aerospace10050486
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/aerospace10050486
Transonic buffet is a phenomenon of large self-excited shock oscillations caused by shock wave-boundary layer interaction, which is one of the common flow instability problems in aeronautical engineering. This phenomenon involves unsteady flow, which makes optimal design more difficult. In this paper, aerodynamic shape optimization design is combined with reinforcement learning to address the problem of transonic buffet. Using the deep deterministic policy gradient (DDPG) algorithm, a reinforcement learning-based design framework for airfoil shape optimization was constructed to achieve effective suppression of transonic buffet. The aerodynamic characteristics of the airfoil were calculated by the computational fluid dynamics (CFD) method. After optimization, the buffet onset angles of attack of the airfoils NACA0012 and RAE2822 were improved by 2° and 1.2° respectively, and the lift-drag ratios improved by 83.5% and 30% respectively. Summarizing and verifying the optimization results, three general conclusions can be drawn to improve the buffet performance: (1) narrowing of the leading edge of the airfoil; (2) situating the maximum thickness position at approximately 0.4 times the chord length; (3) increasing the thickness of the trailing edge within a certain range. This paper established a reinforcement learning-based unsteady optimal design method that enables the optimization of unsteady problems, including buffet.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/aerospace10050486
- https://www.mdpi.com/2226-4310/10/5/486/pdf?version=1684590276
- OA Status
- gold
- Cited By
- 8
- References
- 43
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4377289601
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4377289601Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/aerospace10050486Digital Object Identifier
- Title
-
Study on Optimization Design of Airfoil Transonic Buffet with Reinforcement Learning MethodWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-05-20Full publication date if available
- Authors
-
Hao Chen, Chuanqiang Gao, Jifei Wu, Kai Ren, Weiwei ZhangList of authors in order
- Landing page
-
https://doi.org/10.3390/aerospace10050486Publisher landing page
- PDF URL
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https://www.mdpi.com/2226-4310/10/5/486/pdf?version=1684590276Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2226-4310/10/5/486/pdf?version=1684590276Direct OA link when available
- Concepts
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Airfoil, Transonic, Aerodynamics, Trailing edge, Leading edge, Computational fluid dynamics, Computer science, Angle of attack, Aerospace engineering, Reinforcement learning, Structural engineering, Engineering, Artificial intelligenceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
8Total citation count in OpenAlex
- Citations by year (recent)
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2025: 4, 2024: 4Per-year citation counts (last 5 years)
- References (count)
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43Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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