A workaround for computing spanwise average per iteration is to use the dynamic filter "HistoryPoints" and set WaveSpace = "true".
You will have to provide the coordinates of the "plane" you wish to sample from (note that z = 0 for spanwise averaged field).
After which, you can post-process the .csv file using any platform you wish (python/matlab/jupyter/etc..).
Moshen,
Thank you for the helpful response! "meanmodes" performed exactly what I needed. I'm curious
if there's a method to perform the spanwise average dynamically during computation time, meaning that the spanwise average is calculated per iteration, and this 2D plane is then averaged over time.
From: Mohsen Lahooti <Mohsen.Lahooti@newcastle.ac.uk>
Sent: Monday, November 27, 2023 4:39 PM
To: Ma, Ting-Hsuan <TIM48@pitt.edu>; nektar-users@imperial.ac.uk <nektar-users@imperial.ac.uk>
Subject: Re: Homogenous Spanwise Averaging
Hi Dustin,
You can use the “meanmode” module of FieldConvert which compute the data on the zero Fourier plane. You can use it on the flow fld files, or even on Reynolds
stresses fld files.
Hope this helps
Cheers,
Moshen
From: nektar-users-bounces@imperial.ac.uk <nektar-users-bounces@imperial.ac.uk> on behalf of Ma, Ting-Hsuan <TIM48@pitt.edu>
Date: Monday, 27 November 2023 at 20:10
To: nektar-users@imperial.ac.uk <nektar-users@imperial.ac.uk>
Subject: [Nektar-users] Homogenous Spanwise Averaging
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Hi all,
I am currently working on obtaining DNS data and have successfully provided Nektar with a 2D mesh (XY) for streamwise and wall-normal directions. Utilizing Nektar's homogeneous expansion in the spanwise direction, I've managed to acquire my 3D turbulence data.
However, I'm looking for a function that can return a 2D XY plane of all averaged components by averaging in the spanwise, homogeneous direction. While the Filter "ReynoldsStresses" can provide the 3D time-averaged fields, I was wondering if there's a function
specifically designed performing the averaging/output that I have specified. I've checked the user guide without finding relevant information. Any guidance or pointers would be greatly appreciated.
Thanks,
Dustin