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]<mailto:[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
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