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This paper presents the results of an experimental investigation exploring the noise reduction potential of sawtooth trailing edge serrations on a flat plate at low-to-moderate Reynolds number (1.6 × 10 5 < Re c < 4.2 × 10 5). Acoustic measurements have been taken using a flat plate with both sharp and serrated trailing edges in an anechoic wind tunnel. Trailing edge serrations are found to achieve reductions of up to 13 dB in the narrowband noise levels and this is mainly due to attenuation of vortex shedding at the trailing edge. Velocity data have also been measured in the very near trailing edge wake using hot-wire anemometry and these data are related to the far-field noise measurements to give insight into the trailing edge serration noise reduction mechanism. The results show that for this particular configuration, the noise reduction mechanism of trailing edge serrations is dominated by their influence on the hydrodynamic field at the source location. Therefore the assumption that the turbulent field is unaffected by the serrations is not valid and explains why theory is not able to explain experimental observations.

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Traditional local active noise control systems minimise the measured acoustic pressure to generate a zone of quiet at the physical error sensor location. The resulting zone of quiet is generally limited in size and this requires the physical error sensor be placed at the desired location of attenuation, which is often inconvenient. To overcome this, a number of virtual sensing algorithms have been developed for active noise control. Using the physical error signal, the control signal and knowledge of the system, these virtual sensing algorithms estimate the error signal at a location that is remote from the physical error sensor, referred to as the virtual location. Instead of minimising the physical error signal, the estimated error signal is minimised with the active noise control system to generate a zone of quiet at the virtual location. This paper will review a number of virtual sensing algorithms developed for active noise control. Additionally, the performance of these virtual sensing algorithms in numerical simulations and in experiments is discussed and compared

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