Automated optimization system for aircraft wing design
Automated optimization system for aircraft wing design
The optimization of a transonic civil transport aircraft is a complex and difficult task, due to the complexity of the cost surfaces and the human expertise that is necessary in order to achieve high quality results. In this paper we describe an Automated Optimization System that provide recommendations to design engineers on the choice of optimization search technique to sue, especially when searching within familiar domains. The Automated optimization System uses Artificial Intelligence, specifically machine learning techniques to perform knowledge discovery from past optimization search and reuses this knowledge to facilitate intelligent recommendations for search routines selection. Results of a case study on the design of a transonic civil transport aircraft wing using the Automated Optimization System are presented in the paper. It is shown that the Automated Optimization System not only aids design engineers to make improved decisions when working on complex aircraft wing but also helps improve design search performance.
Centre for Computational Intelligence, University of Essex
Ong, Y.S.
62497a6f-823e-4663-b263-4a805a00f181
Keane, A.J.
26d7fa33-5415-4910-89d8-fb3620413def
2002
Ong, Y.S.
62497a6f-823e-4663-b263-4a805a00f181
Keane, A.J.
26d7fa33-5415-4910-89d8-fb3620413def
Ong, Y.S. and Keane, A.J.
(2002)
Automated optimization system for aircraft wing design.
In Proceedings of 7th International Conference on Artificial Intelligence in Design, Cambridge, UK, 13-17 Jul 2002.
Centre for Computational Intelligence, University of Essex.
4 pp
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
The optimization of a transonic civil transport aircraft is a complex and difficult task, due to the complexity of the cost surfaces and the human expertise that is necessary in order to achieve high quality results. In this paper we describe an Automated Optimization System that provide recommendations to design engineers on the choice of optimization search technique to sue, especially when searching within familiar domains. The Automated optimization System uses Artificial Intelligence, specifically machine learning techniques to perform knowledge discovery from past optimization search and reuses this knowledge to facilitate intelligent recommendations for search routines selection. Results of a case study on the design of a transonic civil transport aircraft wing using the Automated Optimization System are presented in the paper. It is shown that the Automated Optimization System not only aids design engineers to make improved decisions when working on complex aircraft wing but also helps improve design search performance.
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Published date: 2002
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conference; 2002-01-01, 2002-01-01
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Local EPrints ID: 22261
URI: http://eprints.soton.ac.uk/id/eprint/22261
PURE UUID: 71c93463-ef28-419b-b2ed-6fbaff32d7e9
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Date deposited: 11 Jul 2006
Last modified: 16 Mar 2024 02:53
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Author:
Y.S. Ong
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