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.
Highlights
Aeroelastic models such as the Blade Element Momentum (BEM) models [1] play a critical role in the design, development, and optimization of modern wind turbines
Choice of uncertain inputs The data for lift (Cl) and drag (Cd) polars are available at four locations along the blade radius: at 11.87 m, 17.82 m, 28.97 m, and 35.53 m
Twist, lift- and drag-polars are obtained by perturbing the control points with a uniformly distributed random variable based on Latin Hypercube Sampling
Summary
Aeroelastic models such as the Blade Element Momentum (BEM) models [1] play a critical role in the design, development, and optimization of modern wind turbines. A large number of BEM models have been developed to predict turbine responses such as structural loads and power output [2]. As a consequence of the relatively strong model assumptions at the basis of BEM theory, the results from BEM codes can be subject to significant uncertainties. The effect of sheared inflow [3] is not naturally accounted for in the theory and needs to be incorporated via correction terms. Other major model uncertainties in BEM models are the time constant in dynamic stall models, the wake correction factor, the tip loss model parameter, and the lift- and drag-polars used to compute local aerodynamic forces. For increasing turbine sizes, these model parameters are likely not sufficiently accurate [4]
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