Stochastic optimisation based control of boundary layer transition
MacCormack, W., Tutty, O.R., Rogers, E. and Nelson, P. (2002) Stochastic optimisation based control of boundary layer transition. Control Engineering Practice, 10, (3), 243-260. (doi:10.1016/S0967-0661(01)00140-X).
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Suction is one of the most promising techniques for delaying the transition from laminar to turbulent flow and hence reducing the drag force on aircraft. However, in order to achieve an overall reduction in energy consumption and thereby operating costs, it is necessary to apply the suction in an efficient if not optimal manner. Here an investigation is conducted into the use of distributed surface suction with multiple suction panels where the suction distribution is optimised to satisfy a desired objective Cost functions based on minimising the total energy consumption of the system are employed. Evolutionary methods, Genetic Algorithms and Simulated Annealing, are used to perform the optimisation. These methods were successful in cases where gradient based search techniques fail. Physically sensible suction distributions were produced. In general, better behaviour was found with the Genetic Algorithm than with Simulated Annealing, which was prone to premature convergence.
|Digital Object Identifier (DOI):||doi:10.1016/S0967-0661(01)00140-X|
|Keywords:||optimisation, genetic algorithms, simulated annealing, controller design, flow control, transition control|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QC Physics
T Technology > TL Motor vehicles. Aeronautics. Astronautics
|Divisions:||Faculty of Engineering and the Environment > Aeronautics, Astronautics and Computational Engineering > Computational Engineering & Design
Faculty of Engineering and the Environment > Institute of Sound and Vibration Research
Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Southampton Wireless Group
|Date Deposited:||05 Mar 2002|
|Last Modified:||27 Mar 2014 19:58|
|Further Information:||Google Scholar|
|ISI Citation Count:||5|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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