NASA Airfoil Self-Noise Dataset

Context

NASA dataset obtained from a series of aerodynamic and acoustic tests of two and three-dimensional airfoil blade sections conducted in an anechoic wind tunnel. The data was obtained from UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/datasets/airfoil+self-noise

Content

The NASA data set comprises different size NACA 0012 airfoils (n0012-il) (see LINK) at various wind tunnel speeds and angles of attack. The span of the airfoil and the observer position were the same in all of the experiments.

Source

• Donor:
  Dr. Roberto Lopez
  robertolopez '@' intelnics.com
  Intelnics

• Creators:
  Thomas F. Brooks, D. Stuart Pope and Michael A. Marcolini
  NASA

Attribute Information:

Input features:

1. f: Frequency in Hertzs [Hz].
2. alpha: Angle of attack (AoA, α), in degrees [°].
3. c: Chord length, in meters [m].
4. U_infinity: Free-stream velocity, in meters per second [m/s].
5. delta: Suction side displacement thickness (𝛿), in meters [m].

Output:

1. SSPL: Scaled sound pressure level, in decibels [dB].

Relevant Papers

T.F. Brooks, D.S. Pope, and A.M. Marcolini.
Airfoil self-noise and prediction.
Technical report, NASA RP-1218, July 1989.

K. Lau.
A neural networks approach for aerofoil noise prediction.
Master’s thesis, Department of Aeronautics.
Imperial College of Science, Technology and Medicine (London, United Kingdom), 2006.

R. Lopez.
Neural Networks for Variational Problems in Engineering.
PhD Thesis, Technical University of Catalonia, 2008.

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