Black-box calibration for complex systems simulation
Black-box calibration for complex systems simulation
Predicting or measuring the output of complex systems is an important and challenging part of many areas of science. If multiple observations are required for parameter studies and optimization, accurate, computationally intensive predictions or expensive experiments are intractable. This paper looks at the use of Gaussian process based correlations to correct simple computer models with sparse data from physical experiments or more complex computer models. In essence, physics based computer codes and experiments are replaced by fast problem specific statistics based codes. Two aerodynamic design examples are presented. First a cheap two dimensional potential flow solver is calibrated to represent the flow over the wing of an unmanned air vehicle. The rear wing of a racing car is then optimized using rear wing simulations calibrated to include the effects of the flow over the whole car.
3567-3579
Forrester, Alexander I. J.
176bf191-3fc2-46b4-80e0-9d9a0cd7a572
April 2010
Forrester, Alexander I. J.
176bf191-3fc2-46b4-80e0-9d9a0cd7a572
Forrester, Alexander I. J.
(2010)
Black-box calibration for complex systems simulation.
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 368 (1924), .
(doi:10.1098/rsta.2010.0051).
Abstract
Predicting or measuring the output of complex systems is an important and challenging part of many areas of science. If multiple observations are required for parameter studies and optimization, accurate, computationally intensive predictions or expensive experiments are intractable. This paper looks at the use of Gaussian process based correlations to correct simple computer models with sparse data from physical experiments or more complex computer models. In essence, physics based computer codes and experiments are replaced by fast problem specific statistics based codes. Two aerodynamic design examples are presented. First a cheap two dimensional potential flow solver is calibrated to represent the flow over the wing of an unmanned air vehicle. The rear wing of a racing car is then optimized using rear wing simulations calibrated to include the effects of the flow over the whole car.
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Published date: April 2010
Organisations:
Faculty of Engineering and the Environment
Identifiers
Local EPrints ID: 146605
URI: http://eprints.soton.ac.uk/id/eprint/146605
ISSN: 1364-5021
PURE UUID: 01cf55c2-b2b6-48ad-bf6a-98d641bee1f9
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Date deposited: 22 Apr 2010 08:08
Last modified: 14 Mar 2024 00:56
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