On the potential of a multi-fidelity G-POD based approach for optimization & uncertainty quantification
On the potential of a multi-fidelity G-POD based approach for optimization & uncertainty quantification
Traditional multi-fidelity surrogate models require that the output of the low fidelity model be reasonably well correlated with the high fidelity model and will only predict scalar responses. The following paper explores the potential of a novel multi-fidelity surrogate modelling scheme employing Gappy Proper Orthogonal Decomposition (G-POD) which is demonstrated to accurately predict the response of the entire computational domain thus improving optimization and uncertainty quantification performance over both traditional single and multi-fidelity surrogate modelling schemes
Toal, David J.J.
dc67543d-69d2-4f27-a469-42195fa31a68
16 June 2014
Toal, David J.J.
dc67543d-69d2-4f27-a469-42195fa31a68
Toal, David J.J.
(2014)
On the potential of a multi-fidelity G-POD based approach for optimization & uncertainty quantification.
ASME Turbo Expo 2014: Turbine Technical Conference and Exposition, Dusseldorf, Germany.
16 - 20 Jun 2014.
Record type:
Conference or Workshop Item
(Paper)
Abstract
Traditional multi-fidelity surrogate models require that the output of the low fidelity model be reasonably well correlated with the high fidelity model and will only predict scalar responses. The following paper explores the potential of a novel multi-fidelity surrogate modelling scheme employing Gappy Proper Orthogonal Decomposition (G-POD) which is demonstrated to accurately predict the response of the entire computational domain thus improving optimization and uncertainty quantification performance over both traditional single and multi-fidelity surrogate modelling schemes
Text
GT2014-25184 (On the Potential of A Multi-Fidelity G-POD Based Approach for Optimization & Uncertainty Quantification).pdf
- Accepted Manuscript
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Published date: 16 June 2014
Venue - Dates:
ASME Turbo Expo 2014: Turbine Technical Conference and Exposition, Dusseldorf, Germany, 2014-06-16 - 2014-06-20
Organisations:
Computational Engineering & Design Group
Identifiers
Local EPrints ID: 363184
URI: http://eprints.soton.ac.uk/id/eprint/363184
PURE UUID: dda14a75-1b4a-4c88-a1de-2133c0dbc884
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Date deposited: 24 Mar 2014 09:18
Last modified: 15 Mar 2024 03:29
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