JHU Turbulence Database

The JHU Turbulence Database Cluster turbulence.pha.jhu.edu
Dataset descriptions Access via web-browser Access via Web services interface (using Fortran, C or Matlab running on client computer) Download data cutout Matlab analysis tools Analysis tools documentation (interpolation algorithms, differentiation, etc..) Publications People and credits Citing the database in your work Related group webpages Links to other turbulence and fluid dynamics datasets Home		NOTICE: On Monday April 22th updates will be performed on the Database cluster nodes. There will be a brief downtime for the Turbulence Database Cluster for the duration of the updates. Welcome to the JHU Turbulence Database Cluster (TDC) site This website is a portal that enables access to multi-Terabyte turbulence databases. The data reside on several nodes and disks on our database cluster computer and are stored in small 3D subcubes. Positions are indexed using a Z-curve for efficient access. Access to the data is facilitated by a Web services interface that permits numerical experiments to be run across the Internet. We offer C, Fortran and Matlab interfaces layered above Web services so that scientists can use familiar programming tools on their client platforms. Calls to fetch subsets of the data can be made directly from within a program being executed on the client's platform. Manual queries for data at individual points and times via web-browser are also supported. Evaluation of velocity and pressure at arbitrary points and time is supported using interpolations executed on the database nodes. Spatial differentiation using various order approximations (up to 8th order) and filtering are also supported (for details, see documentation page). Particle tracking can be performed both forward and backward in time using a second order accurate Runge-Kutta integration scheme. Subsets of the data can be downloaded in hdf5 file format using the data cutout service. So far the database contains a 1024⁴ space-time history of a direct numerical simulation (DNS) of isotropic turbulent flow, in incompressible fluid in 3D, and a DNS of the incompressible magneto-hydrodynamic (MHD) equations. The simulations were performed using 1024 grid points in each direction using a pseudo-spectral method, and forcing at large scales. The database allows access to 1024 time steps covering about one integral turn-over time-scale of the turbulence. The datasets comprise 27 Terabytes for the isotropic turbulence data and 56 Terabytes for the MHD data. Basic characteristics of the data sets can be found in the datasets description page. Technical details about the database techniques used for this project are described in the publications. The Turbulence Database Cluster project is funded by the US National Science Foundation . Questions and comments? turbulence@pha.jhu.edu 1078741002072 points queried Please excuse our dust as we continue to develop this site. The Turbulence Database is on-line but may periodcally be unavailable as we continue to add functionalities.

The JHU Turbulence Database Cluster

turbulence.pha.jhu.edu

Dataset descriptions

Access via web-browser

Access via Web services interface (using Fortran, C or Matlab running on client computer)

Download data cutout

Matlab analysis tools

Analysis tools documentation (interpolation algorithms, differentiation, etc..)

Publications

People and credits

Citing the database in your work

Related group webpages

Links to other turbulence and fluid dynamics datasets

Home

NOTICE: On Monday April 22th updates will be performed on the Database cluster nodes. There will be a brief downtime for the Turbulence Database Cluster for the duration of the updates.

Welcome to the JHU Turbulence Database Cluster (TDC) site

This website is a portal that enables access to multi-Terabyte turbulence databases. The data reside on several nodes and disks on our database cluster computer and are stored in small 3D subcubes. Positions are indexed using a Z-curve for efficient access.

Access to the data is facilitated by a Web services interface that permits numerical experiments to be run across the Internet. We offer C, Fortran and Matlab interfaces layered above Web services so that scientists can use familiar programming tools on their client platforms. Calls to fetch subsets of the data can be made directly from within a program being executed on the client's platform. Manual queries for data at individual points and times via web-browser are also supported. Evaluation of velocity and pressure at arbitrary points and time is supported using interpolations executed on the database nodes. Spatial differentiation using various order approximations (up to 8th order) and filtering are also supported (for details, see documentation page). Particle tracking can be performed both forward and backward in time using a second order accurate Runge-Kutta integration scheme. Subsets of the data can be downloaded in hdf5 file format using the data cutout service.

So far the database contains a 1024⁴ space-time history of a direct numerical simulation (DNS) of isotropic turbulent flow, in incompressible fluid in 3D, and a DNS of the incompressible magneto-hydrodynamic (MHD) equations. The simulations were performed using 1024 grid points in each direction using a pseudo-spectral method, and forcing at large scales. The database allows access to 1024 time steps covering about one integral turn-over time-scale of the turbulence. The datasets comprise 27 Terabytes for the isotropic turbulence data and 56 Terabytes for the MHD data. Basic characteristics of the data sets can be found in the datasets description page. Technical details about the database techniques used for this project are described in the publications.

The Turbulence Database Cluster project is funded by the US National Science Foundation .

Questions and comments? turbulence@pha.jhu.edu

1078741002072 points queried

Please excuse our dust as we continue to develop this site. The Turbulence Database is on-line but may periodcally be unavailable as we continue to add functionalities.