meaning of a "integ" boundary condition in dedalus examples

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Upasana Das

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Apr 19, 2018, 8:34:47 PM4/19/18
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Hello Everyone,

In the 1d Rayleigh-Benard example script under EVP in Dedalus examples, can you tell me what the following boundary condition means physically, and when can 
I use a such a boundary condition?

problem.add_bc("integ(p, 'z') = 0")

I am attaching the script here for everyone's reference.

Thanks & Regards,
Upasana

rayleigh_benard.py

Daniel Lecoanet

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Apr 19, 2018, 8:51:39 PM4/19/18
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integral of p over z direction is zero

Daniel

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Upasana Das

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Apr 19, 2018, 11:21:34 PM4/19/18
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Thanks Daniel. I wanted to clarify that this condition has nothing to do with incompressibility right?

Upasana


On Thursday, 19 April 2018 18:51:39 UTC-6, Daniel Lecoanet wrote:
integral of p over z direction is zero

Daniel
On Fri, Apr 20, 2018 at 2:34 AM, Upasana Das <upasa...@gmail.com> wrote:
Hello Everyone,

In the 1d Rayleigh-Benard example script under EVP in Dedalus examples, can you tell me what the following boundary condition means physically, and when can 
I use a such a boundary condition?

problem.add_bc("integ(p, 'z') = 0")

I am attaching the script here for everyone's reference.

Thanks & Regards,
Upasana

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Keaton Burns

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Apr 20, 2018, 10:45:16 AM4/20/18
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Hi Upasana,

It’s actually a little complicated here.  In some simulations, you’ll see this BC applied to the horizontal-mean Fourier mode (kx=0).  In that case, it’s setting the pressure gauge — the overall constant pressure, which is dynamically insignificant in incompressible simulations.

This case is different — for the eigenvalue problem, each variable takes the form f(x)e^{ikx}, where the x-dependence is implied by the substitution defining the x-derivative.  So this condition isn’t setting the pressure gauge, it’s actually a boundary condition that you can show is equivalent to setting w=0 on the other wall for the linear problem.

I think this is an outdated version of the example script though — the current version should include Dirichlet preconditioning and utilize the sparse eigenvalue solver, which is much faster when you’re only interested in finding a subset of the eigenmodes.

Best,
-Keaton
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