Large-scale Dataset of 100,000 Airfoil Pressure Distributions via Potential Flow Theory

This dataset contains the aerodynamic pressure coefficients for 100,000 unique airfoil geometries. The data was generated using potential flow theory (Panel Method) across various angles of attack. This collection is ideal for training machine learning models in aerodynamic shape optimization or surrogate modeling. Data Structure: Each sample is stored as a single row with 242 columns, organized as follows: Columns 1-121: Y-coordinates of the airfoil surface. Column 122: Angle of Attack in degrees. Columns 123-242: Pressure Coefficient values corresponding to the surface points. Spatial Discretization: The X-coordinates are not included as they are constant for all samples, following a standard cosine spacing distribution over a unit chord.