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Sergey Karabasov

Dr Sergey Karabasov

Dr Sergey Karabasov

Research Fellow

Interests and expertise (Subject groups)

Grants awarded

Next generation of hybrid numerical methods for engineering aeroacoustics

Scheme: University Research Fellowship

Organisation: Queen Mary, University of London

Dates: Oct 2010-Nov 2014

Value: £305,620.30

Summary: My research interests lie in the area of high-resolution and multiscale modelling in computational aero and hydrodynamics. Over the years, my research into sound generated by aerodynamic flows has been supported the leading UK industry such as Rolls-Royce, GKN Westland Helicopters and Thales Underwater Systems, Royal Society and EPSRC. My current research into modelling of sound generated by turbulence is supported by Aero Acoustics Research Consortium (AARC) in the framework of joint research effort with Ohio Aerospace Institute and NASA Glen for jet noise modeling and also by EPSRC/BAE Systems for broadband noise modellig in water systems. My research into high-resolution computational hydrodynamics for ocean modelling is supported by NERC in the project with Imperial College London. In collaboration with Dr Nerukh’s group in Aston University we have developed a new scheme for numerically coupling the continuum equations with the molecular dynamics based on an idea of Eulerian-Lagrangian unsteady flux coupling in the framework of a new multi-space-time method. The idea formed the basis for a new 1.2 M Euro multi-lateral G8 project which involves Queen Mary, Aston University and several other research institutions in Japan and Russia. The goal of the project was to develop a new non-local boundary condition for industry-standard open-source molecular dynamics codes to allow one to truncate the computational domain size and, thus, speed up the simulation. First results have been reported at the recent Lorenz Centre Workshop and Royal Society Kavli Seminar devoted to Multiscale Modelling. I am a guest editor of the Royal Society PhilTrans A special issue “Multiscale systems in fluids and soft matter: approaches, numerics, and applications” which will be published in Summer 2014.

Next generation of hybrid numerical methods for engineering aeroacoutics

Scheme: University Research Fellowship

Organisation: University of Cambridge

Dates: Oct 2005-Sep 2010

Value: £239,543.24

Summary: 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.

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