Validation of the ExaWind hybrid solver framework using field measurements of the NM-80 turbine under turbulent inflow

ORAL

Abstract

We present a hybrid solver framework for high-fidelity blade-resolved simulations of wind turbines in realistic atmospheric conditions. The challenge in this approach is to create a solver framework that can efficiently simulate both the flow around the complex blade geometry as well capture the wake formation and interaction with the atmosphere. We coupled the CFD solver Nalu-wind capable of resolving the turbine geometry with the block-structured background solver AMR-wind using overset technology from TIOGA to achieve this capability. The hybrid solver framework will allow us to simulate wind energy flows across a range of length scales that are eight orders of magnitude apart from 10 microns in the blade boundary layer to 1 km in the atmospheric boundary layer (ABL). The new hybrid solver was used to perform a comparison of the aerodynamic and structural loads under turbulent inflow conditions for the blade-resolved simulations of the NM80 rotor (IEA Wind Task 29 benchmark case), for which turbulence is generated in two different ways: 1. Synthetic turbulence from a Mann model introduced as source terms within the computational domain; 2. A full precursor Large-Eddy simulation of the ABL.

*This work was authored in part by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36- 08GO28308. M. Brazell was funded by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of two DOE organizations (Office of Science and the National Nuclear Security Administration). Funding provided by the U.S.\ Department of Energy Office of Energy Efficiency and Renewable Energy Wind Energy Technologies Office. A portion of the research was performed using computational resources sponsored by the DOE's Office of Energy Efficiency and Renewable Energy and located at the National Renewable Energy Laboratory.

Presenters

  • Ganesh Vijayakumar

    • National Renewable Energy Laboratory

Authors

  • Ganesh Vijayakumar

    • National Renewable Energy Laboratory
  • Shreyas Ananthan

    • Siemens Gamesa Renewable Energy Digital Ventures Lab
    • Siemens Gamesa Renewable Energy - Digital Ventures Lab
  • Lawrence Cheung

    • Sandia National Laboratory
    • Sandia National Laboratories
  • Michael J Brazell

    • National Renewable Energy Laboratory
    • National Renewable Energy Laboratory (NREL)
  • Luis Martinez-Tossas

    • National Renewable Energy Laboratory
    • National Renewable Energy Lab
  • Ashesh Sharma

    • National Renewable Energy Laboratory
  • Neil Matula

    • Sandia National Laboratories
  • Philip Sakievich

    • Sandia National Laboratories
  • Jayanarayanan Sitaraman

    • Parallel Geometric Algorithms LLC
  • Michael A Sprague

    • National Renewable Energy Laboratory