Tecplot for Barracuda – Calculating Spatial Average Axial Profiles

This video is part of the Tecplot for Barracuda Training Videos collection.

This training video shows how to calculate spatial average axial profiles from Tecplot for Barracuda using PyTecplot. It is necessary to have Python installed in order to perform this analysis.

Concepts covered in this video:

• Enabling PyTecplot connections
• Analyzing 3D visualization data to create a reduced-order xy plot

Related references of interest for the topics discussed in this video include:

• Tecplot for Barracuda – PyTecplot Examples and Snippets
• binned_statistic — SciPy Manual

Youtube

The contents of the Python script shown in the video are included below for easy copy-and-paste.

#!/usr/bin/env python

import tecplot as tp
import numpy as np
from scipy import stats

tp.session.connect()
with tp.session.suspend():
    dataset = tp.active_frame().dataset

    # Get cell-center values for z-position
    tp.data.operate.execute_equation(equation='{zCenter} = {z}', value_location=tp.constant.ValueLocation.CellCentered)
    z = dataset.zone('Cells').values('zCenter').as_numpy_array()

    # Get the time-average particle volume fraction
    aveParticleVolFrac = dataset.zone('Cells').values('Time-averaged particle volume fraction').as_numpy_array()

# Calculate the spatially averaged profile
bin_means, bin_edges, binnumber = stats.binned_statistic(z, aveParticleVolFrac, statistic='mean', bins=20)
bin_centers = (bin_edges[:-1] + bin_edges[1:]) / 2

# Export the calculated profile to an SFF file so it can be plotted with Tecplot
headerText  = "# Spatial average calculation results\n"
headerText += "#\n"
headerText += "#@ 1 \"Time-averaged particle volume fraction\" \"\"\n"
headerText += "#@ 2 \"Height\" \"m\""
np.savetxt('time_and_spatial_average_profile_particle_volume_fraction.sff', np.transpose([bin_means, bin_centers]),
           fmt='%3.6e', comments='', header=headerText)