Hi Andy, Sorry for the very slow reply!
The full paper is now available open-access here: https://arc.aiaa.org/doi/abs/10.2514/1.J055304 Along with a full set of Electronic Supplementary Material, so you can reproduce the results if you like! Thanks Peter Dr Peter Vincent MSci ARCS DIC PhD Reader in Aeronautics and EPSRC Fellow Department of Aeronautics Imperial College London South Kensington London SW7 2AZ UK web: www.imperial.ac.uk/aeronautics/research/vincentlab<http://www.imperial.ac.uk/aeronautics/research/vincentlab> twitter: @Vincent_Lab On 7 Jun 2017, at 04:14, Andy Smith <[email protected]<mailto:[email protected]>> wrote: Peter, Sorry to bring up an old post but I was also wondering if you had any more guidance regarding recommended anti-aliasing options such as relative order of the over-integration vs. solution polynomial approximation, over-integration quadrature points vs solution quadrature points, etc. Perhaps some of these points have been addressed in your recently accepted publication to the AIAA Journal, "High-Order Accurate Implicit Large Eddy Simulations of Flow over a NACA0021 Aerofoil in Deep Stall". If so would it be possible to post a pre-print of this article? Thank you, Andy On Tuesday, August 30, 2016 at 8:28:32 AM UTC-4, Antonio Garcia-Uceda wrote: Hi Peter, Indeed, replacing the "|" by the comma solves the issues. Thanks a lot. There is a couple of points I think you didn't answer in your previous email: Which option for "Anti-Aliasing" do you normally use in PyFR? Is there any procedure for choosing the most appropriate one? I mean, you first attempt with one and if it doesn't improve enough the stability you try other options? Also, Have you done any tests on the performance (increase in both computational time and memory footprint) of each of the "Anti-Aliasing" options? Finally, out of curiosity, I've observed in the sources of PyFR that when applying the "surf-flux" option with the navier-stokes solver, the L2 projection is applied on both the fluxes on the interfaces, as well as the common solution for the correction of the gradients. In my understanding, this last wouldn't be needed since the common solution can be exactly integrated on the faces just with the flux points. Nevertheless, I presume that you do this in order to avoid to extrapolate the solution twice to the interfaces (to both flux and quad points), and most importantly to avoid having to transfer these two sets of data through MPI in a parallel computation. Could you please tell me whether I'm right with this? Thanks a lot once more. Best regards, Antonio On Tuesday, August 30, 2016 at 11:49:09 AM UTC+2, Vincent, Peter E wrote: Hi Antonio, I have a question about the "Anti-Aliasing" technique available in PyFR in order to improve the stability of the method. I see there are several options available, so as to apply over-integration of the fluxes in the cell (<<flux>>), interfaces (<<surf-flux>>), or div_flux (<<div-flux>>) in the cell, or coupling some of these together (<<flux | surf-flux>>, …). Yes, that is correct. Could you please let me know the difference in between these different options? flux: performs an approximate L2 projection of the flux in the volume of each element surf-flux: performs an approximate L2 projection of the Riemann solver flux on the surface of each element div-flux: performs an approximate L2 projection of \nabla\cdot f = \hat{\nabla}\cdot\hat{f}/|J| I mean, Are there particular cases where an option turns out to be more efficient than the others in enhancing the stability? Which option do you users of PyFR utilise most often? The most important two are flux and surf-flux, but div-flux can also be useful/required if the elements have non-constant Jacobians. Finally, I've seen that the combined options (<<flux | div-flux>>, ...) are broken in PyFR (I get the following error message when launching PyFR: "Invalid anti-alias option", which is an Exception raised in shapes.py). Is this normal, or perhaps I''m setting something wrong in the .ini file? I think they need to be a comma separated list e.g. flux, surf-flux and not flux | surf-flux as your snippet implies you were using. Let us know if this fixes the issue. Cheers Peter Dr Peter Vincent MSci ARCS DIC PhD Senior Lecturer and EPSRC Early Career Fellow Department of Aeronautics Imperial College London South Kensington London SW7 2AZ UK web: www.imperial.ac.uk/aeronautics/research/vincentlab<http://www.imperial.ac.uk/aeronautics/research/vincentlab> twitter: @Vincent_Lab<https://twitter.com/Vincent_Lab> On 30 Aug 2016, at 11:30, Antonio Garcia-Uceda <[email protected]> wrote: Dear all, My name is Antonio Garcia-Uceda, and I'm a researcher working on Flux Reconstruction Methods. I have a question about the "Anti-Aliasing" technique available in PyFR in order to improve the stability of the method. I see there are several options available, so as to apply over-integration of the fluxes in the cell (<<flux>>), interfaces (<<surf-flux>>), or div_flux (<<div-flux>>) in the cell, or coupling some of these together (<<flux | surf-flux>>, ...). Could you please let me know the difference in between these different options? I mean, Are there particular cases where an option turns out to be more efficient than the others in enhancing the stability? Which option do you users of PyFR utilise most often? Also, which option is more efficient in terms of computational time? Finally, I've seen that the combined options (<<flux | div-flux>>, ...) are broken in PyFR (I get the following error message when launching PyFR: "Invalid anti-alias option", which is an Exception raised in shapes.py). Is this normal, or perhaps I''m setting something wrong in the .ini file? Thanks a lot in advance for your help. Best regards, Amntonio -- 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 [email protected]. To post to this group, send email to [email protected]. 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 [email protected]. To post to this group, send an email to [email protected]. Visit this group at https://groups.google.com/group/pyfrmailinglist. For more options, visit https://groups.google.com/d/optout.
