Scale-Adaptive Simulation (SAS) of Dynamic Stall on a Wind Turbine

Abdolrahim Rezaeiha*, Hamid Montazeri, Bert Blocken

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Scale-adaptive simulation (SAS) approach is employed to investigate the complex dynamic stall phenomena occurring on a wind turbine blade. The results are compared with the more popular less computationally-expensive unsteady Reynolds-averaged Navier-Stokes (URANS) approach where the latter is validated using three sets of experimental data. The comparison reveals that the two approaches have similar predictions of the instant of the formation/bursting/shedding of the laminar separation bubble (LSB) and dynamic stall vortex (DSV), the size of the LSB and aerodynamic loads during the upstroke. This is while the two approaches exhibit dissimilar predictions of the trailing-edge vortex characteristics, its interaction with the DSV, number of secondary vortices and aerodynamic loads during the downstroke.

Original languageEnglish
Title of host publicationProgress in Hybrid RANS-LES Modelling
PublisherSpringer
Pages323-333
Number of pages11
ISBN (Electronic)9783030276072
ISBN (Print)9783030276065
DOIs
Publication statusPublished - 2020
Event7th Symposium on Hybrid RANS-LES Methods 2018 - Berlin, Germany
Duration: 17 Sept 201819 Sept 2018

Publication series

NameNotes on Numerical Fluid Mechanics and Multidisciplinary Design
Volume143
ISSN (Print)1612-2909
ISSN (Electronic)1860-0824

Conference

Conference7th Symposium on Hybrid RANS-LES Methods 2018
Country/TerritoryGermany
CityBerlin
Period17/09/1819/09/18

Keywords

  • Blade-wake interaction
  • Hybrid RANS/LES
  • Turbulence modeling
  • Vertical axis wind turbine (VAWT)
  • Wind energy

ASJC Scopus subject areas

  • Fluid Flow and Transfer Processes

Fingerprint

Dive into the research topics of 'Scale-Adaptive Simulation (SAS) of Dynamic Stall on a Wind Turbine'. Together they form a unique fingerprint.

Cite this