1. Performance evaluation of an airfoil under ice accretion using CFD simulations
- Author
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Daniel Bodenlle-Toral, Pedro García-Regodeseves, and Adrián Pandal-Blanco
- Subjects
History ,Computer Science Applications ,Education - Abstract
The profiles used in wind turbine blades have a great effect on aerodynamic behavior. The incorporation in engineering methods of the three-dimensional and rotation effects obtained through numerical simulations has allowed to substantially improve the design of the blades. A further advance in the improvement of the models is the modification of the surface state of the profile due to environmental effects. The presence of erosion, dirt, or snow on the leading edge reduces the aerodynamic behavior of the profiles. Therefore, incorporating its effects would improve predictions. However, the implementation of these effects in numerical models is complex. In this work, only the effect of the ice/snow accretion will be taken into account. The study is made using the NREL PHASE VI experimental horizontal-axis turbine with the S809 profile. The BEM theory is applied to conduct accurate 2D numerical simulations firstly, of a clean profile (unmodified) and afterwards of accreted profile. The latter is constructed by the modification of the profile in advance, following indications of the Icing ANSYS Fluent tool. Simulations are conducted under a RANS numerical approach through an SST k-ω model, which properly predicts boundary layer behavior. CFD results are evaluated at different sections of the profile and compared against predictions from other authors in terms of aerodynamic coefficients. The simulations consistently predict an increase in the drag coefficient (CD +33%), and a decrease in the lift coefficient (CL -9%). The presence of ice accretion affects the airfoil performance along the whole blade span, being slightly more pronounced towards the root of the blade. This work presents a new engineering methodology able to accurately predict airfoil performance under ice accretion at a reduced computational cost.
- Published
- 2022
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