PyTecplot has a lot of great capability: bringing in the Python multiprocessing toolkit allows you to accelerate your work and get it done even faster. This webinar shows how to use the Python Multiprocessing Library in conjunction with PyTecplot to accelerate the generation of movies and images. This technique can go beyond just the generation of images: you can extract information from your simulation data as well. If you’re new to MPI, it’s also well worth your time reviewing both how to get it running on your OS, and some other niceties.

The approach outlined in these tutorials is applicable to any solver, so the fact that we’re using SU2 is without prejudice to any other solver! SU2, as faithful users will attest, has some AMR capabilities of it’s own – see this article for some interesting comments by developers that can help you figure out your own approach as we work forwards. Further, it’s an easy solver to install on both Linux and Windows, and is easily used with MPI. So download it, install it, and you’re all set!

If the flow-solver wants to adapt the mesh to the flow physics, it will necessarily need to move, insert, remove or otherwise modify mesh points that adhere to the geometry model. And how can it do so if it doesn’t know what the geometry is? See this article to read how Pointwise addresses this critical requirement, and go here to review the schema and library. You can use this library with any of C++, C, Fortran and Python.