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Toward a GPU-Accelerated Immersed Boundary Method for Wind Forecasting Over Complex Terrain

[+] Author Affiliations
Rey DeLeon, Kyle Felzien, Inanc Senocak

Boise State University, Boise, ID

Paper No. FEDSM2012-72145, pp. 1385-1394; 10 pages
doi:10.1115/FEDSM2012-72145
From:
  • ASME 2012 Fluids Engineering Division Summer Meeting collocated with the ASME 2012 Heat Transfer Summer Conference and the ASME 2012 10th International Conference on Nanochannels, Microchannels, and Minichannels
  • Volume 1: Symposia, Parts A and B
  • Rio Grande, Puerto Rico, USA, July 8–12, 2012
  • Conference Sponsors: Fluids Engineering Division
  • ISBN: 978-0-7918-4475-5
  • Copyright © 2012 by ASME

abstract

A short-term wind power forecasting capability can be a valuable tool in the renewable energy industry to address load-balancing issues that arise from intermittent wind fields. Although numerical weather prediction models have been used to forecast winds, their applicability to micro-scale atmospheric boundary layer flows and ability to predict wind speeds at turbine hub height with a desired accuracy is not clear. To address this issue, we develop a multi-GPU parallel flow solver to forecast winds over complex terrain at the micro-scale, where computational domain size can range from meters to several kilometers. In the solver, we adopt the immersed boundary method and the Lagrangian dynamic large-eddy simulation model and extend them to atmospheric flows. The computations are accelerated on GPU clusters with a dual-level parallel implementation that interleaves MPI with CUDA. We evaluate the flow solver components against test problems and obtain preliminary results of flow over Bolund Hill, a coastal hill in Denmark.

Copyright © 2012 by ASME

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