CFL number
 

How much, in general, can the CFL number be increased for a steady (implicit) RANS simulation? From test cases, it appears to be around 5. I've used other, similar type solvers where the CFL number can be ramped up to a value on the order of 100.

Depending on the geometry and quality of the mesh, we have been able to ramp the CFL in SU2 to relatively large values. For example, with something simple like the viscous flat plate cases, we have been able to ramp the CFL up to hundreds or thousands. With that said, each application is different, so some experimenting is required.

Have you tried using the CFL ramp options in the configuration file? An example of the format is as follows:

% CFL ramp (factor, number of iterations, CFL limit)
CFL_RAMP= ( 1.05, 50, 2.0 )

where the first number is a factor, 1.05, that is multiplied by the initial CFL number every 50 iterations until is hits the maximum of 2.0.

Finally, an important thing to note is that the stability for implicit calculations is heavily affected by the type of linear solver used and its settings. With the second release of the code, we now have more linear solvers available, such as GMRES. Some the these solvers might offer more stability (i.e. higher CFL numbers) but may also be more computationally expensive. I would recommend trying the different solvers and also experimenting with their settings such as the error tolerance and number of smoothing iterations between each major iteration of the flow solver.

CFL number
 

Hi,

When performing steady state RANS simulations using SU2 5.0, the CFL number was set to 2.0 and the simulations were diverging. When I kept all the settings the same and just changed to CFL number to 1.0 the simulations stopped diverging. From my knowledge, CFL number is used in unsteady simulations where the time step is not equal to zero. Is there a reason why the CFL number matters for my steady state case where the time step is zero? :confused:

Thanks.

Regards,
Sou

Hi Sou,

for obtaining steady-state solutions SU2 makes use of the so-called 'pseudo-time method'.
It's comparable to finding the the (presumably steady) limit by an unsteady simulation, but it's not quite the same. Still it makes use of a CFL number which has a similar meaning as the one for 'real time' simulations. It can be set to the highest possible value for saving computational cost.
Unsteady simulations, if required, are then carried out by an outer loop of a sequence of such pseudo-time solutions.

Have a look into the reference papers on SU2 (https://github.com/su2code/Documentation) for further information.

Kind regards, Ole