Towards an intelligent non-stationary performance prediction of engineering systems
Towards an intelligent non-stationary performance prediction of engineering systems
The analysis of complex engineering systems can often be expensive thereby necessitating the use of surrogate models within any design optimization. However, the time variant response of quantities of interest can be non-stationary in nature and therefore difficult to represent effectively with traditional surrogate modelling techniques. The following paper presents the application of partial non-stationary kriging to the prediction of time variant responses where the definition of the non-linear mapping scheme is based upon prior knowledge of either the inputs to, or the nature of, the engineering system considered.
Toal, David J.J.
dc67543d-69d2-4f27-a469-42195fa31a68
Keane, A.J.
26d7fa33-5415-4910-89d8-fb3620413def
25 May 2011
Toal, David J.J.
dc67543d-69d2-4f27-a469-42195fa31a68
Keane, A.J.
26d7fa33-5415-4910-89d8-fb3620413def
Toal, David J.J. and Keane, A.J.
(2011)
Towards an intelligent non-stationary performance prediction of engineering systems.
Learning and Intelligent OptimizatioN (LION 5), Rome, Italy.
4 pp
.
(doi:10.1007/978-3-642-25566-3).
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Conference or Workshop Item
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Abstract
The analysis of complex engineering systems can often be expensive thereby necessitating the use of surrogate models within any design optimization. However, the time variant response of quantities of interest can be non-stationary in nature and therefore difficult to represent effectively with traditional surrogate modelling techniques. The following paper presents the application of partial non-stationary kriging to the prediction of time variant responses where the definition of the non-linear mapping scheme is based upon prior knowledge of either the inputs to, or the nature of, the engineering system considered.
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Published date: 25 May 2011
Venue - Dates:
Learning and Intelligent OptimizatioN (LION 5), Rome, Italy, 2011-05-25
Organisations:
Computational Engineering & Design Group
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Local EPrints ID: 188459
URI: http://eprints.soton.ac.uk/id/eprint/188459
PURE UUID: 3e4b644e-4209-4f32-aec7-2c1d1b9e4823
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Date deposited: 25 May 2011 10:43
Last modified: 15 Mar 2024 03:29
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