Hi Vincent, Thanks for your reply. I am really interested in this since for large meshes become unfeasible to subdivide into linear elements to do the post-processing. I think the best thing would be to include this functionality in "pyfr export" and export the polynomials information local to each cell to the VTU file with -d 1. This is desirable because working with the HDF5 format can be really slow to query for spatially dependent data, and in that respect , VTK provides space partitioners which are very useful to map coordinates to cells efficiently. I am willing to work on this and contribute to the project if you point me to the right place to look and if you provide me detailed information on how polynomial information is encoded in the HDF5 file and how can I reconstruct them. I think this is a valuable feature to have and I have seen at least another message in the mailing list related to this problem [1].
Thanks in advance, Eduardo [1] https://groups.google.com/forum/#!searchin/pyfrmailinglist/integration%7Csort:date/pyfrmailinglist/zNq4ooPSgDI/9hDxh88FCQAJ On Tuesday, November 13, 2018 at 8:22:18 AM UTC, Vincent, Peter E wrote: > > Thanks for the email. > > The polynomial information is stored inside the .pyfrs files. They can be > interrogated with e.g. h5py or any other HDF5 wrapper. > > Basically, we store the solution value at a set if nodal points within > each element, which when combined with an associated nodal basis can be > used to reconstruct the polynomials within each element. > > If you are interested we would need to provide some more info about the > exact file format, since it is not documented anywhere yet. Also, since > elements can be curved, it can be a challenge to work out which element a > given physical point is in. And when you have found the element the mapping > may need to be inverted numerically. > > Peter > > Dr Peter Vincent MSci ARCS DIC PhD FRAeS > Reader in Aeronautics and EPSRC Fellow > Department of Aeronautics > Imperial College London > South Kensington > London > SW7 2AZ > UK > > > > On 12 Nov 2018, at 15:45, Eduardo Ramos Fernandez <eduard...@gmail.com > <javascript:>> wrote: > > Hi all, > > I want to use the solution of a turbulent flow from PyFR as an input for a > Lagrangian simulation. The problem is computing the trajectories of the > particles advected by the flow are sensitive to local errors in the fluid > velocity field and can diverge. The trajectories can be computed one at a > time since they do not interact and they are not coupled to the solver > (flow not affected by the presence of particles). Because of that, I dump > my flow solution from PyFR and convert it to .VTU so I can after read it > with the Lagrangian software and use VTK libraries to extract velocities at > different positions. The problem is in the conversion from .pyfrs to .vtu > information is lost through the -d N linearisation stage and the > computational advantage of having a coarser mesh it is lost. Furthermore, > making N high, when resolving particle trajectories, makes the inverse > search from particle positions to fluid cells really expensive in an > unstructured mesh. Would it be possible to dump the internal PyFR > polynomial information local to each cell so it can be used in a > post-processing stage? This would be useful for any kind of post-processing > doing integration over the fields. > > Regards, > > Eduardo > > -- > You received this message because you are subscribed to the Google Groups > "PyFR Mailing List" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to pyfrmailingli...@googlegroups.com <javascript:>. > To post to this group, send email to pyfrmai...@googlegroups.com > <javascript:>. > Visit this group at https://groups.google.com/group/pyfrmailinglist. > For more options, visit https://groups.google.com/d/optout. > > > -- You received this message because you are subscribed to the Google Groups "PyFR Mailing List" group. To unsubscribe from this group and stop receiving emails from it, send an email to pyfrmailinglist+unsubscr...@googlegroups.com. To post to this group, send an email to pyfrmailinglist@googlegroups.com. Visit this group at https://groups.google.com/group/pyfrmailinglist. For more options, visit https://groups.google.com/d/optout.
