# Solution filtering

**URL:** <https://pyfr.discourse.group/t/solution-filtering/1012>\
**Category:** Cases\
**Tags:** config\
**Created:** [10 January 2024 08:18 UTC](https://pyfr.discourse.group/t/solution-filtering/1012 "2024-01-10T08:18:30Z")\
**Posts on this page:** 4\
**Page:** 1

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**Author:** ![Frankx9](https://avatars.discourse-cdn.com/v4/letter/f/3e96dc/32.png) [@Frankx9](https://pyfr.discourse.group/u/Frankx9)\
**Post date:** [10 January 2024 08:18 UTC](https://pyfr.discourse.group/t/solution-filtering/1012/1 "2024-01-10T08:18:30Z")

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Hello,

I’m currently running a case where if I use p=1 I can run the solution with a sporadic filtering (e.g 1000 steps) and it is stable while as soon as I increase to p=4 it can only progress in time if I start filtering every step. It is the first time I face such a condition.

Do you have any recommendation in what to look at? Diffusion is playing a key role in stabilising it but I need to avoid such a frequent filtering to reduce computational time.

Best regards

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**Author:** ![fdw](https://avatars.discourse-cdn.com/v4/letter/f/a587f6/32.png) [@fdw](https://pyfr.discourse.group/u/fdw)\
**Post date:** [10 January 2024 13:19 UTC](https://pyfr.discourse.group/t/solution-filtering/1012/2 "2024-01-10T13:19:02Z")

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It is hard to say without knowing more about your case and how it diverges. Things such as mesh spacing, if anti-aliasing is enabled, time stepping scheme, etc.

Solution filtering is known to interact poorly with adaptive time stepping so you may want to revert to a fixed time step in such cases.

Regards, Freddie.

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**Author:** ![Frankx9](https://avatars.discourse-cdn.com/v4/letter/f/3e96dc/32.png) [@Frankx9](https://pyfr.discourse.group/u/Frankx9)\
**Post date:** [11 January 2024 10:05 UTC](https://pyfr.discourse.group/t/solution-filtering/1012/3 "2024-01-11T10:05:24Z")

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Could you provide some theoretical references for the flux, surf-flux procedure implemented in pyFR?

Best regards

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**Author:** ![fdw](https://avatars.discourse-cdn.com/v4/letter/f/a587f6/32.png) [@fdw](https://pyfr.discourse.group/u/fdw)\
**Post date:** [11 January 2024 13:13 UTC](https://pyfr.discourse.group/t/solution-filtering/1012/4 "2024-01-11T13:13:06Z")

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Yes, see:

[https://arc.aiaa.org/doi/full/10.2514/1.J055304](https://arc.aiaa.org/doi/full/10.2514/1.J055304)

Regards, Freddie.