Research Fellows Directory
Dr Sergey Karabasov
Queen Mary, University of London
In the past, most of the jet noise reduction for civil aircraft came from increasing the size of jet engines. This allowed engineers to reduce the jet speed for the same amount of thrust and, since jet noise scales as a high power of the jet exit velocity, this reduces the noise. However, any further decrease is only possible if detailed noise mechanisms are quantified. Meanwhile, noise reduction remains an important and pressing task: by 2020 the total number of flights is expected to double and, accordingly, each individual jet needs to be made at least twice as quiet.
At Cambridge University we developed a new jet noise model based on flow decomposition into the turbulent noise source and sound propagation through the jet flow. The decomposition of complex flows such as the turbulent jet into the source and propagation parts, referred to as an acoustic analogy, is a difficult task., which may have more than one solution. We choose our model so that we have an exact match between the propagation and the noise sources whose statistical representation can be obtained from a separate calculation. This leads to a new model which is completely free from any empirical input, is able to produce accurate noise predictions and allows one to identify effective sound sources in the jet. These effective sound sources indicate which areas of the jet need to be modified if the noise is to be reduced. The primary tool I am using in my research is computational modelling. Computational modelling in aeroacoustics requires a particular accuracy because of the vast range of length and time scales one has to resolve with a finite computing power. Hence, another part of the project is devoted to continued development and application of efficient computational methods which can be used in jet noise and more general turbulent flow research.