Deep Reinforcement Learning (DRL) for aerodynamic shape optimization is highly sensitive to geometry parameterization. When coupled with global-support methods like Class-Shape Transformation (CST), DRL frequently generates self-intersecting, oscillatory profiles that cause flow-solver...
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