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
> twitter: @Vincent_Lab <https://twitter.com/Vincent_Lab>
>
>
>
>
>
> On 30 Aug 2016, at 11:30, Antonio Garcia-Uceda <[email protected]
> <javascript:>> 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
>
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