Numerical study of 3-D finlets using Reynolds-averaged Navier–Stokes computational fluid dynamics for trailing edge noise reduction

Abstract

This paper uses Reynolds-averaged Navier–Stokes computational fluid dynamics to study trailing edge noise reduction with 3-D finlets. Reynolds-averaged Navier–Stokes computational fluid dynamics provides boundary layer parameters near a trailing edge for an empirical wall pressure spectrum model, and then an acoustic model predicts far-field noise based on pressure fluctuations obtained from the wall pressure spectrum model. First, this numerical approach is validated against experiments. Second, a comprehensive trend analysis is conducted to give insight into the design of 3-D finlets under different flow conditions. A data-driven turbulence spanwise length scale model is developed to tackle finlets with small spacing. Combined with acoustic results, detailed computational flow field results are analyzed to understand the physical mechanism of noise reduction. While the major part of the proposed mechanism is the same as prior work, several new observations are shown which better understand the physical mechanism of noise reduction with 3-D finlets. The goals of the current paper are to provide an efficient Reynolds-averaged Navier–Stokes-based approach to predict trailing edge noise of 3-D finlets, to give complete trend analysis results with various finlets under different flow conditions, and to advance an understanding of the underlying physics.