)
egp@vt.edu
Eric Paterson is Professor and Department Head of Aerospace and Ocean Engineering. For Fall 2013, he is teaching AOE 5984, Intro to Parallel Computing Applications with faculty from Virginia Tech's Advanced Research Computing.
AOE 5984: Introduction to Parallel Computing Applications
OpenFOAM for CFD Applications
Lecture 3: Data Analysis and Visualization
Professor Eric Paterson
Aerospace and Ocean Engineering, Virginia Tech
19 November 2013
Topics briefly discussed in Lecture 2
- Introduction to OpenFOAM data analysis tools
- Showed dictionary entries used by the sample utility for extracting sets and surfaces data from 4D fields
- Showed example of plotting X-Y data (sets) with python+matplotlib
- Showed example of visualizing surfaces rather than loading entire datasets
- Emphasized that data reconstruction should be avoided
Lecture 3: Data Analysis & Visualization
- Highlight the difference between data analysis and visualization of OpenFOAM data
- Discuss utilities and post-processing software for data analysis and visualization
- Students will:
- appreciate the importance of working with decomposed and remote data
- understand that there are numerous OpenFOAM utilities for operating on data and computing derived data
- learn about the power of using python and pyFoam
- understand that client-server visualization is important for reducing data transfer and duplication
Data Analysis vs. Visualization
- Data Analysis
- Quantitative
- Primary and derived variables
- Integral variables, e.g., lift, drag, mass-flow rate
- X-Y plots
- Extraction of comparison metrics for verification and validation
- Visualization
- Qualitative
- Primary and derived variables
- Contour maps, streamlines, iso-surfaces, etc.
- Animations
OpenFOAM utilities
- OpenFOAM has numerous pre-compiled post-processing utilities, which can be found in $FOAM_UTILITIES/postProcessing
- Description of each can be found online at: http://www.openfoam.org/docs/user/standard-utilities.php
- Many of the utilities perform vector and tensor operations to compute derived variables, e.g., vorticity, Q, lambda2, shearStress, etc.
velocityField postProcessing tools
Post-processing velocity fields | |
Calculates and writes the Courant number obtained from field phi as avolScalarField. |
|
Calculates and writes the enstrophy of the velocity field U |
|
Calculates and writes the flowType of velocity field U |
|
Calculates and writes the second largest eigenvalue of the sum of the square of the symmetrical and anti-symmetrical parts of the velocity gradient tensor |
|
Calculates and optionally writes the local Mach number from the velocity field U at each time |
|
Calculates and writes the Pe number as a surfaceScalarField obtained from field phi |
|
Calculates and writes the second invariant of the velocity gradient tensor |
|
Calculates and writes the stream function of velocity field U at each time |
|
Calculates and writes the scalar field of uprime ( |
|
Calculates and writes the vorticity of velocity field U |
|
Example: Calculation of vorticity
postProcessing/velocityField/vorticity/vorticity.C
IOobject Uheader
(
"U",
runTime.timeName(),
mesh,
IOobject::MUST_READ
);
if (Uheader.headerOk())
{
Info<< " Reading U" << endl;
volVectorField U(Uheader, mesh);
Info<< " Calculating vorticity" << endl;
volVectorField vorticity
(
IOobject
(
"vorticity",
runTime.timeName(),
mesh,
IOobject::NO_READ
),
fvc::curl(U)
);
volScalarField magVorticity
(
IOobject
(
"magVorticity",
runTime.timeName(),
mesh,
IOobject::NO_READ
),
mag(vorticity)
);
Info<< "vorticity max/min : "
<< max(magVorticity).value() << " "
<< min(magVorticity).value() << endl;
if (writeResults)
{
vorticity.write();
magVorticity.write();
}
}
else
{
Info<< " No U" << endl;
} wall postProcessing tools
Example: calculation of
wallShearStress
void calcIncompressible
(
const fvMesh& mesh,
const Time& runTime,
const volVectorField& U,
volVectorField& wallShearStress
)
{
#include "createPhi.H"
singlePhaseTransportModel laminarTransport(U, phi);
autoPtr<:rasmodel> model
(
incompressible::RASModel::New(U, phi, laminarTransport)
);
const volSymmTensorField Reff(model->devReff());
forAll(wallShearStress.boundaryField(), patchI)
{
wallShearStress.boundaryField()[patchI] =
(
-mesh.Sf().boundaryField()[patchI]
/mesh.magSf().boundaryField()[patchI]
) & Reff.boundaryField()[patchI];
}
} where is the function devReff?
Example: kEpsilon.C
tmp kEpsilon::devReff() const
{
return tmp
(
new volSymmTensorField
(
IOobject
(
"devRhoReff",
runTime_.timeName(),
mesh_,
IOobject::NO_READ,
IOobject::NO_WRITE
),
-nuEff()*dev(twoSymm(fvc::grad(U_)))
)
);
} 
python
- How to plot X-Y data for quantitative analysis?
- Tecplot
- Matlab
- python + matplotlib + numpy + scipy
- interactive python ipython provides a shell interface, http://ipython.org
- Visualization tools use python scripting for data manipulation and automation, http://paraview.org/Wiki/ParaView/Python_Scripting
pyFoam
pyFoam
-
This Python-library can be used to
- analyze the logs produced by OpenFoam-solvers
- execute OpenFoam-solvers and utilities and analyze their output simultaneously
- manipulate the parameter files and the initial-conditions of a run in a non-destructive manner
- plots the residuals of OpenFOAM solvers
-
Written by Bernhard Gschaider
pyFoam example
Visualization
- There are many very good visualization software packages
- Paraview - free
- Tecplot - Virginia Tech site license
- Fieldview
- Ensight
- All of these packages natively read OpenFOAM data, plus numerous other formats
- Making useful images requires experience and an eye for esthetics and art: beware of chartjunk and colorful fluid dynamics
Wind-turbine interaction: Fieldview
client-server visualization walkthrough
How-to notes posted on Scholar
next lecture: meshing
Captain Nemo's submarine, The Nautilus
AOE 5984: OPENFOAM Data Analysis and Visualization
By egp@vt.edu
AOE 5984: OPENFOAM Data Analysis and Visualization
OpenFOAM for AOE 5984, Fall 2013. This lectures will cover data analysis and visualization for OpenFOAM CFD simulations.
