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
>> 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
>>
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