Global sensitivity analysis of model uncertainty in aeroelastic wind turbine models. Issue 4 (September 2020)
- Record Type:
- Journal Article
- Title:
- Global sensitivity analysis of model uncertainty in aeroelastic wind turbine models. Issue 4 (September 2020)
- Main Title:
- Global sensitivity analysis of model uncertainty in aeroelastic wind turbine models
- Authors:
- Kumar, P.
Sanderse, B.
Boorsma, K.
Caboni, M. - Abstract:
- Abstract: A framework is presented for performing global sensitivity analysis of model parameters associated with the Blade Element Momentum (BEM) models. Sobol indices based on adaptive sparse polynomial expansions are used as a measure of global sensitivities. The sensitivity analysis workflow is developed using the uncertainty quantification toolbox UQLab that is integrated with TNO's Aero-Module aeroelastic code. Uncertainties in chord, twist, and lift- and drag-coefficients have been parametrized through the use of NURBS curves. Sensitivity studies are performed on the NM80 wind turbine model from the DanAero project, for a case with 19 uncertainties in both model and geometry. The combination of parametrization and sparse adaptive polynomial chaos yields a new efficient framework for global sensitivity analysis of aeroelastic wind turbine models, paving the way to effective model calibration.
- Is Part Of:
- Journal of physics. Volume 1618:Issue 4(2020)
- Journal:
- Journal of physics
- Issue:
- Volume 1618:Issue 4(2020)
- Issue Display:
- Volume 1618, Issue 4 (2020)
- Year:
- 2020
- Volume:
- 1618
- Issue:
- 4
- Issue Sort Value:
- 2020-1618-0004-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-09
- Subjects:
- Physics -- Congresses
530.5 - Journal URLs:
- http://www.iop.org/EJ/journal/1742-6596 ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1742-6596/1618/4/042034 ↗
- Languages:
- English
- ISSNs:
- 1742-6588
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5036.223000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25658.xml