Articles | Volume 10, issue 12
https://doi.org/10.5194/wes-10-2821-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-10-2821-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
01 Dec 2025
Data description article |
| 01 Dec 2025
| 01 Dec 2025
JHTDB-wind: a web-accessible large-eddy simulation database of a wind farm with virtual sensor querying
Xiaowei Zhu
Department of Mechanical and Materials Engineering, Portland State University, Portland, OR 97201, USA
Shuolin Xiao
Ralph O’Connor Sustainable Energy Institute, Johns Hopkins University, Baltimore, MD 21218, USA
Ghanesh Narasimhan
Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
St. Anthony Falls Lab, University of Minnesota, Minneapolis, MN 55455, USA
Luis A. Martinez-Tossas
National Renewable Energy Laboratory, Golden, CO 80401, USA
Michael Schnaubelt
Institute for Data Intensive Engineering and Science, Johns Hopkins University, Baltimore, MD 21218, USA
Gerard Lemson
Institute for Data Intensive Engineering and Science, Johns Hopkins University, Baltimore, MD 21218, USA
Hanxun Yao
Institute for Data Intensive Engineering and Science, Johns Hopkins University, Baltimore, MD 21218, USA
Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
Alexander S. Szalay
Institute for Data Intensive Engineering and Science, Johns Hopkins University, Baltimore, MD 21218, USA
Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218, USA
Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA
Dennice F. Gayme
Ralph O’Connor Sustainable Energy Institute, Johns Hopkins University, Baltimore, MD 21218, USA
Institute for Data Intensive Engineering and Science, Johns Hopkins University, Baltimore, MD 21218, USA
Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
Ralph O’Connor Sustainable Energy Institute, Johns Hopkins University, Baltimore, MD 21218, USA
Institute for Data Intensive Engineering and Science, Johns Hopkins University, Baltimore, MD 21218, USA
Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
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Short summary
The paper describes a new approach to democratize access to results from expensive high-performance computer simulations of atmospheric boundary layer flow interacting with wind turbines, in large wind farms. Users interact with the data using a virtual sensor array methodology and essentially stream the data on demand to their analysis or visualization programs rather than having to download files and worrying about data formats, etc.
The paper describes a new approach to democratize access to results from expensive...
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