NREL - Neutral - TTU

Kosovic, Branko

doi:10.21947/1959744

Title: NREL - Neutral - TTU

Dataset
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Abstract

This dataset includes large-eddy simulation (LES) output from a neutrally stratified atmospheric boundary layer (ABL) simulation of observations at the SWIFT tower near Lubbock, Texas on Aug. 17, 2012. The dataset was used to assess LES models for simulation of canonical neutral ABL. The dataset can be used for comparison with other LES and computational fluid dynamics model outputs.

Authors:

Kosovic, Branko

University Corporation for Atmospheric Research; Pacific Northwest National Laboratory

Publication Date:: Fri Mar 03 23:00:00 EST 2023

Research Org.:: Atmosphere to Electrons (A2e) Data Archive and Portal, Pacific Northwest National Laboratory; PNNL

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)

Subject:: 17 WIND ENERGY

OSTI Identifier:: 1959744

DOI:: https://doi.org/10.21947/1959744

Citation Formats


                    Kosovic, Branko. NREL - Neutral - TTU.  United States: N. p., 2023. 
        Web.  doi:10.21947/1959744.

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                    Kosovic, Branko. NREL - Neutral - TTU.  United States.  doi:https://doi.org/10.21947/1959744

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                    Kosovic, Branko. 2023.  
"NREL - Neutral - TTU".  United States.  doi:https://doi.org/10.21947/1959744.  https://www.osti.gov/servlets/purl/1959744. Pub date:Fri Mar 03 23:00:00 EST 2023

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@article{osti_1959744,

  title        = {NREL - Neutral - TTU},

  author       = {Kosovic, Branko},

  abstractNote = {This dataset includes large-eddy simulation (LES) output from a neutrally stratified atmospheric boundary layer (ABL) simulation of observations at the SWIFT tower near Lubbock, Texas on Aug. 17, 2012. The dataset was used to assess LES models for simulation of canonical neutral ABL. The dataset can be used for comparison with other LES and computational fluid dynamics model outputs.},

  doi          = {10.21947/1959744},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Fri Mar 03 23:00:00 EST 2023},

  month        = {Fri Mar 03 23:00:00 EST 2023}

}

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DOI: https://doi.org/10.21947/1959744

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