Skip to main navigation Skip to search Skip to main content

Improvement of airfoil turbulent trailing-edge noise semi-empirical prediction formulation

  • Baohong Bai
  • , Xiaodong Li*
  • *Corresponding author for this work
  • Beihang University

Research output: Contribution to journalArticlepeer-review

Abstract

The traditional BPM semi-empirical prediction airfoil turbulent boundary layer trailing edge noise was improved. The traditional BPM semi-empirical prediction formulation overpredicts the spectra in high frequency range at high angle of attack or for thick airfoil. It is found that it was mainly caused by the overestimation of the noise contribution from pressure side source through the analysis and comparison between the traditional BPM semi-empirical prediction formulation and Howe's trailing-edge noise theoretical model. Then the ratio of noise contribution from suction side and pressure side source is improved to the square power of boundary displacement thickness rather than the one power appeared in the traditional BPM semi-empirical prediction formulation. The improved BPM semi-empirical prediction formulation is employed in the airfoil turbulent boundary layer trailing-edge noise prediction, which shows that better results can be obtained from the improved BPM semi-empirical prediction formulation for NACA0012 airfoil at high angle of attack. The prediction for wind turbine airfoil DU-96-W-180 is improved significantly by improved BPM semi-empirical prediction formulation.

Original languageEnglish
Pages (from-to)86-92
Number of pages7
JournalBeijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics
Volume43
Issue number1
DOIs
StatePublished - 1 Jan 2017

Keywords

  • Airfoil trailing-edge noise
  • Noise prediction
  • Noise radiation
  • Semi-empirical formulation
  • Turbulent boundary layer

Fingerprint

Dive into the research topics of 'Improvement of airfoil turbulent trailing-edge noise semi-empirical prediction formulation'. Together they form a unique fingerprint.

Cite this