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DOE OSTI · 3014935

JHTDB-wind: a web-accessible large-eddy simulation database of a wind farm with virtual sensor querying

Zhu, Xiaowei [Portland State Univ., OR (United States)]·Xiao, Shuolin [Johns Hopkins Univ., Baltimore, MD (United States)] (ORCID:0000000263646365)·Narasimhan, Ghanesh [Univ. of Minnesota, Minneapolis, MN (United States)]·Martinez-Tossas, Luis A. [National Renewable Energy Laboratory (NREL), Golden, CO (United States)] (ORCID:0000000323534999)·Schnaubelt, Michael [Johns Hopkins Univ., Baltimore, MD (United States)]·Lemson, Gerard [Johns Hopkins Univ., Baltimore, MD (United States)]·Yao, Hanxun [Johns Hopkins Univ., Baltimore, MD (United States)]·Szalay, Alexander S. [Johns Hopkins Univ., Baltimore, MD (United States)]·Gayme, Dennice F. [Johns Hopkins Univ., Baltimore, MD (United States)]·Meneveau, Charles [Johns Hopkins Univ., Baltimore, MD (United States)] (ORCID:0000000169473605)
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Abstract

This paper introduces JHTDB-wind (https://turbulence.idies.jhu.edu/datasets/windfarms, last access: 11 November 2025), a publicly accessible database containing large-eddy simulation (LES) data from wind farms. Building on the framework of the Johns Hopkins Turbulence Database (JHTDB), which hosts direct numerical simulation (DNS) and some LES datasets of canonical turbulent flows, JHTDB-wind stores the 4D space–time history of the flow and provides users the ability to access and query the data via a web-based virtual sensor interface. The initial dataset comprises LES results from a large wind farm with 10×6 turbines, modeled using a filtered actuator line method, under conventionally neutral atmospheric conditions. These data comprise 1 h (hour) of flow field data (velocity, pressure, potential temperature deviation, subgrid-scale (SGS) eddy viscosity, and turbine forces, approximately 15 TB (terabytes) and wind turbine data – including both turbine-level operational quantities and blade-level aerodynamic quantities (approximately 1.3 TB) – stored in Zarr and Parquet formats, respectively. Data retrieval is facilitated by the giverny Python package, allowing remote users to query the database in Python or MATLAB (C and Fortran support are available for flow field data). This paper details the simulation setup and demonstrates data access through examples that analyze wind farm flow structures and turbine performance. The framework is extensible to future datasets, including the JHTDB-wind diurnal cycle simulation analyzed in Xiao et al. (2025).

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Zhu, Xiaowei [Portland State Univ., OR (United States)], Xiao, Shuolin [Johns Hopkins Univ., Baltimore, MD (United States)] (ORCID:0000000263646365), Narasimhan, Ghanesh [Univ. of Minnesota, Minneapolis, MN (United States)], Martinez-Tossas, Luis A. [National Renewable Energy Laboratory (NREL), Golden, CO (United States)] (ORCID:0000000323534999), Schnaubelt, Michael [Johns Hopkins Univ., Baltimore, MD (United States)], Lemson, Gerard [Johns Hopkins Univ., Baltimore, MD (United States)], Yao, Hanxun [Johns Hopkins Univ., Baltimore, MD (United States)], Szalay, Alexander S. [Johns Hopkins Univ., Baltimore, MD (United States)], Gayme, Dennice F. [Johns Hopkins Univ., Baltimore, MD (United States)], Meneveau, Charles [Johns Hopkins Univ., Baltimore, MD (United States)] (ORCID:0000000169473605). 2025-12-01. JHTDB-wind: a web-accessible large-eddy simulation database of a wind farm with virtual sensor querying. https://doi.org/10.5194/wes-10-2821-2025

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