Revision as of 12:09, 15 February 2021

Statistical data

Volume data

Volumetric data on the statistics computed is provided in HDF5 files. This can be easily read through the HDF5 library or python's h5py. The tree scheme of the dataset is the following:

Statistics.h5
- 01_Info
  - Dimensions
- 02_Entries
  - Inputs
  - 01_Output
    - AdditionalQuantities
    - Convection
    - Production
    - TurbulentDiffusion01
    - TurbulentDiffusion02
    - PressureStrain
    - Dissipation
    - TripleCorrelation
    - PressureVelocity
- 03_Nodes
  - Nodes

The available files are:

Statistics (9.1 kB) Is the h5 masterfile that contains the data tree and relates with the other files.

Inputs (26.0 GB) Contains the averaged pressure and velocity along with their gradients, the shear stress and the Reynolds stress tensor in the following order:

${\overline {P}}$
${\overline {U}}$
${\overline {V}}$
${\overline {W}}$
${{\overline {\tau }}_{11}}$
${{\overline {\tau }}_{12}}$
${{\overline {\tau }}_{22}}$
${{\overline {\tau }}_{13}}$
${{\overline {\tau }}_{23}}$
${{\overline {\tau }}_{33}}$
${R_{11}}$
${R_{12}}$
${R_{22}}$
${R_{13}}$
${R_{23}}$
${R_{33}}$
${{\overline {P}},1}$
${{\overline {U}},1}$
${{\overline {V}},1}$
${{\overline {W}},1}$
${{\overline {P}},2}$
${{\overline {U}},2}$
${{\overline {V}},2}$
${{\overline {W}},2}$
${{\overline {P}},3}$
${{\overline {U}},3}$
${{\overline {V}},3}$
${{\overline {W}},3}$

An example to read this file with python's h5 library would be:

import h5py

f = h5py.File('Statistics.h5','r')

inp = np.array( f.get('02_Entries').get('Inputs') )

f.close()

Recover gradients and Reynolds stress tensor (indices are these of the list above:

grad_velocity = inp[:,[17,21,25,18,22,26,19,23,27]].astype(np.double)

Rij = inp[:,[10,11,13,11,12,14,13,14,15]].astype(np.double)

Additional data

Here additional statistical data should be provided such as data on solid surfaces and integral time scales as specified respectively in sections 4 and 5 of [1]. Further global quantities of interest ( e.g. drag/lift coefficients, mass flow rates, efficiencies, . . . ) should be given here and if need be the procedure should be described in detail. Indicate how the data were non-dimensionalised.

Contributed by: ' — '

Front Page

Description

Computational Details

Quantification of Resolution

Statistical Data

Instantaneous Data

Storage Format

@@ Line 10: / Line 10: @@
 * Statistics.h5
 ** 01_Info
+*** Dimensions
 ** 02_Entries
 *** Inputs
@@ Line 22: / Line 23: @@
 **** TripleCorrelation
 **** PressureVelocity
+** 03_Nodes
+*** Nodes
-[http://kbwiki-data.s3-eu-west-2.amazonaws.com/DNS-1/3/Statistics.h5 Statistics (9.1 kB)]
+The available files are:
+[http://kbwiki-data.s3-eu-west-2.amazonaws.com/DNS-1/3/Statistics.h5 Statistics (9.1 kB)] Is the h5 masterfile that contains the data tree and relates with the other files.
+[http://kbwiki-data.s3-eu-west-2.amazonaws.com/DNS-1/3/Inputs.h5 Inputs (26.0 GB)] Contains the averaged pressure and velocity along with their gradients, the shear stress and the Reynolds stress tensor in the following order:
+<div style="column-count:4;-moz-column-count:4;-webkit-column-count:4">
+# <math>{\overline{P}}</math>
+# <math>{\overline{U}}</math>
+# <math>{\overline{V}}</math>
+# <math>{\overline{W}}</math>
+# <math>{\overline{\tau}_{11}}</math>
+# <math>{\overline{\tau}_{12}}</math>
+# <math>{\overline{\tau}_{22}}</math>
+# <math>{\overline{\tau}_{13}}</math>
+# <math>{\overline{\tau}_{23}}</math>
+# <math>{\overline{\tau}_{33}}</math>
+# <math>{R_{11}}</math>
+# <math>{R_{12}}</math>
+# <math>{R_{22}}</math>
+# <math>{R_{13}}</math>
+# <math>{R_{23}}</math>
+# <math>{R_{33}}</math>
+# <math>{\overline{P},1}</math>
+# <math>{\overline{U},1}</math>
+# <math>{\overline{V},1}</math>
+# <math>{\overline{W},1}</math>
+# <math>{\overline{P},2}</math>
+# <math>{\overline{U},2}</math>
+# <math>{\overline{V},2}</math>
+# <math>{\overline{W},2}</math>
+# <math>{\overline{P},3}</math>
+# <math>{\overline{U},3}</math>
+# <math>{\overline{V},3}</math>
+# <math>{\overline{W},3}</math>
+</div>
+An example to read this file with python's h5 library would be:
+import h5py
+f   = h5py.File('Statistics.h5','r')
+inp = np.array( f.get('02_Entries').get('Inputs') )
+f.close()
+Recover gradients and Reynolds stress tensor (indices are these of the list above:
+grad_velocity = inp[:,[17,21,25,18,22,26,19,23,27]].astype(np.double)
+Rij = inp[:,[10,11,13,11,12,14,13,14,15]].astype(np.double)
 ==Additional data==

DNS 1-3 Statistical Data: Difference between revisions

Revision as of 12:09, 15 February 2021

Contents

Statistical data

Volume data

Additional data

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DNS 1-3 Statistical Data: Difference between revisions

Revision as of 12:09, 15 February 2021

Statistical data

Volume data

Additional data

Navigation menu

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