Postprocessing
Simulation results are good and nice. However, you will have to visualize to data you get out of a simulation in OpenFOAM. These tutorials will explain, how to evaluate simulation results in OpenFOAM.
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Post-processing
- Post- processing with five example cases - Ferras et al. provide 5 cases and guide through the postrpocessing with gnuplot and ParaView.
- Detailed information on Paraview - In this tutorial you will get a deep understanding on the scientific postprocessing and visualization of results in Paraview.
- Sampling - Simulate the flow along a shock tube for 0.007 s and use OpenFOAM sampling utility for extracting the data along a line during the simulation and after the simulation.
- Session B: Using OpenFOAM - Here you will find information about sampling and probing (see sub-section Sampling and Probing), as well as get a basic introduction to visualization (see sub-section Visualization 0.1).
- Training material of the NanoSim project - For Lagrangian Data Visualization using ParaView checkout this tutorial. Note, this page also contains instructions to load data from the popular particle dynamics code LAMMPS/LIGGGHTS. Also, the PVReader Plugin, the LIGGGHTS reader plugin, as well as how to use math-text in Paraview annotations is provided.
- swak4Foam and pyFoam - This tutorial provides material on how to use swak4Foam and pyFoam to postprocess data.
Further reading
- The ParaView Public Wiki gives you all details related to the functionality of ParaView. Tutorias, books, etc. are linked here
- Gnuplot is a lightweight and widespread tool for preparing plots (mainly useful for x-y plots of samples/probed data from OpenFOAM output.
- Octave is an often recommended alternative to Gnuplot. It is the open-source alternative to Matlab.
- You may also want to use Python-based plotting: checkout the matplotlib, or work with Spyder