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Simulating Flows Passing a Wind Turbine with a Fully Implicit Domain Decomposition Method

  • Rongliang Chen
  • Zhengzheng Yan
  • Yubo Zhao
  • Xiao-Chuan Cai
Part of the Lecture Notes in Computational Science and Engineering book series (LNCSE, volume 104)

Abstract

Wind power is an increasingly popular renewable energy. In the design process of the wind turbine blade, the accurate aerodynamic simulation is important. In the past, most of the wind turbine simulations were carried out with some low fidelity methods, such as the blade element momentum method [9]. Recently, with the rapid development of the supercomputers, high fidelity simulations based on 3D unsteady Navier-Stokes (N-S) equations become more popular. For example, Sorensen et al. studied the 3D wind turbine rotor using the Reynolds-Averaged Navier-Stokes (RANS) framework where a finite volume method and a semi-implicit method are used for the spatial and temporal discretization, respectively [17]. Bazilevs et al. investigated the aerodynamic of the NREL 5 MW offshore baseline wind turbine rotor using large eddy simulation built with a deforming-spatial-domain/stabilized space-time formulation [3, 11] and later extended the simulation to the full wind turbine including both the rotor and the tower [10]. Li et al. conducted dynamic overset CFD simulations for the NREL phase VI wind turbine using RANS and detached eddy models [15].

Keywords

Wind Turbine Large Eddy Simulation Wind Turbine Blade High Fidelity Simulation Inexact Newton Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The research was supported in part by the NSF of China under 11401564, the Chinese National 863 Plan Program under 2015AA01A302, the Knowledge Innovation Program of the Chinese Academy of Sciences under KJCX2-EW-L01 and the Shenzhen Peacock Plan (China) under KQCX20130628112914303.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Rongliang Chen
    • 1
  • Zhengzheng Yan
    • 1
  • Yubo Zhao
    • 1
  • Xiao-Chuan Cai
    • 2
  1. 1.Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhenP.R. China
  2. 2.Department of Computer ScienceUniversity of Colorado BoulderBoulderUSA

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