Improving variable-fidelity surrogate modeling via gradient-enhanced kriging and a generalized hybrid bridge function
Variable-fidelity surrogate modeling offers an efficient way to generate aerodynamic data for aero-loads prediction based on a set of CFD methods with varying degree of fidelity and computational expense. In this paper, direct Gradient-Enhanced Kriging (GEK) and a newly developed Generalized Hybrid...
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| Published in: | Aerospace science and technology Vol. 25; no. 1; pp. 177 - 189 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Issy-les-Moulineaux
Elsevier SAS
01.03.2013
Elsevier |
| Subjects: | |
| ISSN: | 1270-9638, 1626-3219 |
| Online Access: | Get full text |
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