Study on Optimization Design of Airfoil Transonic Buffet with Reinforcement Learning Method
Problem
Transonic buffet, large self-excited shock oscillations on wings, is a flow instability that makes optimal airfoil design difficult.
Why it matters
Transonic buffet is a common flow instability problem in aeronautical engineering affecting aircraft performance and safety.
What the AI did
A reinforcement learning design framework using the DDPG algorithm optimized airfoil shapes, with aerodynamics computed via CFD, to suppress transonic buffet.
Results
Buffet onset angles of attack improved by 2° (NACA0012) and 1.2° (RAE2822); lift-drag ratios improved by 83.5% and 30% respectively.
Impact
The RL-optimized airfoils demonstrably delayed buffet onset and improved lift-drag ratio on two benchmark airfoils.
Record
| Venue | Aerospace |
|---|---|
| Published | 2023 |
| Work type | article |
| Authors | Hao Chen, Chuanqiang Gao, Jifei Wu, Kai Ren, Weiwei Zhang |
| Citations | 12 (OpenAlex, at import time) |
| References | 44 |
| Model or method | DDPG (deep deterministic policy gradient) |
| Organization | not stated in source |
| Primary source | https://doi.org/10.3390/aerospace10050486 |
| Open access | gold |
| Keywords | transonic buffet, reinforcement learning, DDPG, airfoil optimization, CFD |
Importance rating
real but narrower advance
Abstract calls transonic buffet a common flow instability affecting aircraft performance and safety; RL optimization delayed buffet onset on two benchmark airfoils.
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