Abstract
Fusing predictions from multiple simulators in the early stages of the conceptual design of a wind turbine results in reduction in model uncertainty and risk mitigation. Aero-servo-elastic is a term that refers to the coupling of wind inflow, aerodynamics, structural dynamics and controls. Fusing the response data from multiple aero-servo-elastic simulators could provide better predictive ability than using any single simulator. The co-Kriging approach to fuse information from multifidelity aero-servo-elastic simulators is presented. We illustrate the co-Kriging approach to fuse the extreme flapwise bending moment at the blade root of a large wind turbine as a function of wind speed, turbulence and shear exponent in the presence of model uncertainty and non-stationary noise in the output. The extreme responses are obtained by two widely accepted numerical aero-servo-elastic simulators, FAST and BLADED. With limited high-fidelity response samples, the co-Kriging model produced notably accurate prediction of validation data.
Original language | English |
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Title of host publication | Proceedings of 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12 |
Editors | Terje Haukaas |
Number of pages | 8 |
Publisher | Civil Engineering Risk and Reliability Association |
Publication date | 2015 |
Publication status | Published - 2015 |
Event | 12th International Conference on Applications of Statistics and Probability in Civil Engineering - Vancouver, Canada Duration: 12 Jul 2015 → 15 Jul 2015 Conference number: 12 |
Conference
Conference | 12th International Conference on Applications of Statistics and Probability in Civil Engineering |
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Number | 12 |
Country/Territory | Canada |
City | Vancouver |
Period | 12/07/2015 → 15/07/2015 |