Stochastic optimisation based control of boundary layer transition
Stochastic optimisation based control of boundary layer transition
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.
optimisation, genetic algorithms, simulated annealing, controller design, flow control, transition control
243-260
MacCormack, W.
95a16974-694b-4726-bfba-03472bc8c866
Tutty, O.R.
c9ba0b98-4790-4a72-b5b7-09c1c6e20375
Rogers, E.
611b1de0-c505-472e-a03f-c5294c63bb72
Nelson, P.
5c6f5cc9-ea52-4fe2-9edf-05d696b0c1a9
2002
MacCormack, W.
95a16974-694b-4726-bfba-03472bc8c866
Tutty, O.R.
c9ba0b98-4790-4a72-b5b7-09c1c6e20375
Rogers, E.
611b1de0-c505-472e-a03f-c5294c63bb72
Nelson, P.
5c6f5cc9-ea52-4fe2-9edf-05d696b0c1a9
MacCormack, W., Tutty, O.R., Rogers, E. and Nelson, P.
(2002)
Stochastic optimisation based control of boundary layer transition.
Control Engineering Practice, 10 (3), .
(doi:10.1016/S0967-0661(01)00140-X).
Abstract
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.
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More information
Published date: 2002
Keywords:
optimisation, genetic algorithms, simulated annealing, controller design, flow control, transition control
Organisations:
Inst. Sound & Vibration Research, Computational Engineering & Design Group, Southampton Wireless Group
Identifiers
Local EPrints ID: 256027
URI: http://eprints.soton.ac.uk/id/eprint/256027
ISSN: 0967-0661
PURE UUID: 7e0a56ca-26c0-4c8f-a5b4-a89d71153627
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Date deposited: 05 Mar 2002
Last modified: 15 Mar 2024 02:42
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Contributors
Author:
W. MacCormack
Author:
O.R. Tutty
Author:
E. Rogers
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