Abstract

This paper describes an experimental study on a notched nozzle for jet noise reduction. The notch, a tiny tetrahedral dent formed at the edge of a nozzle, is expected to enhance mixing within a limited region downstream of the nozzle. The enhanced mixing leads to the suppression of broadband peak components of jet noise with little effect on the engine performance. To investigate the noise reduction performances of a six-notch nozzle, a series of experiments have been performed at an outdoor test site. Tests on the engine include acoustic measurement in the far field to evaluate the noise reduction level with and without the notched nozzle, and pressure measurement near the jet plume to obtain information on noise sources. The far-field measurement indicated the noise reduction by as much as 3 dB in terms of overall sound pressure level in the rear direction of the engine. The use of the six-notch nozzle though decreased the noise-benefit in the side direction. Experimental data indicate that the high-frequency components deteriorate the noise reduction performance at wider angles of radiation. Although the increase in noise is partly because of the increase in velocity, the penetration of the notches into the jet plume is attributed to the increase in sound pressure level in higher frequencies. The results of near-field measurement suggest that an additional sound source appears up to x/D = 4 due to the notches. In addition, the total pressure maps downstream of the nozzle edge, obtained using a pressure rake, show that the notched nozzle deforms the shape of the mixing layer, causing it to become wavy within a limited distance from the nozzle. This deformation of the mixing layer implies strong vortex shedding and thus additional noise sources. To improve the noise characteristics, we proposed a revised version of the nozzle on the basis of a computational prediction, which contained 18 notches that were smaller than those in the 6-notched nozzle. Ongoing tests indicate greater noise reduction in agreement with the computational prediction.

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