Hi all,
I’m working with unsteady flow data stored as time series for several spanwise slices (e.g., “s0001”, “s0002”, etc.), each located at a different z-position. My goal is to compute a single 2D field that is both time-averaged and spanwise-averaged — essentially ⟨w⟩(x, y), averaged over time and span.
I’ve computed the temporal average for each slice using “Temporal Statistics” and saved the outputs. Then I load these averaged slices and tried combining them using “Append Attributes”, followed by a “Python Calculator” to average the “w_average” fields spatially. However, the final result seems incorrect.
Do I need to apply “Transform” filter to align all slices to the same z-plane before appending? Is “Append Attributes” the right filter here, or should I be using “Append Datasets” or something else when the data is spatially separated?
Any advice on best practices for this type of averaging would be much appreciated!
Thanks