Compute and plot 2D streamlines#

This example shows you how to compute and plot streamlines of fluid simulation results, for 2D models.

Note

This example requires DPF 7.0 (ansys-dpf-server-2024-1-pre0) or above. For more information, see Compatibility.

Plot surface streamlines#

Import modules, create the data sources and the model#

Import modules:

from ansys.dpf import core as dpf
from ansys.dpf.core import examples
from ansys.dpf.core.helpers.streamlines import compute_streamlines
from ansys.dpf.core.plotter import DpfPlotter

Create data sources for fluids simulation result:

fluent_files = examples.download_fluent_multi_species()
ds_fluent = dpf.DataSources()
ds_fluent.set_result_file_path(fluent_files["cas"], "cas")
ds_fluent.add_file_path(fluent_files["dat"], "dat")

Create model from fluid simulation result data sources:

m_fluent = dpf.Model(ds_fluent)

Get meshed region and velocity data#

Meshed region is used as the geometric base to compute the streamlines. Velocity data is used to compute the streamlines. The velocity data must be nodal.

Get the meshed region:

meshed_region = m_fluent.metadata.meshed_region

Get the velocity result at nodes:

velocity_op = m_fluent.results.velocity()
fc = velocity_op.outputs.fields_container()
field = dpf.operators.averaging.to_nodal_fc(fields_container=fc).outputs.fields_container()[0]

Compute single streamline#

single_2d_streamline, single_2d_source = compute_streamlines(
    meshed_region=meshed_region,
    field=field,
    start_position=(0.005, 0.0005, 0.0),
    surface_streamlines=True,
    return_source=True,
)

Plot single streamline#

pl_single = DpfPlotter()
pl_single.add_field(field, meshed_region, opacity=0.2)
pl_single.add_streamlines(
    streamlines=single_2d_streamline,
    source=single_2d_source,
    radius=0.00002,
)
# Use the PyVista 'cpos' optional argument to control the camera position.
# To easily save a camera position, plot the figure a first time with the argument
# 'return_cpos=True'. This will make the ``DpfPlotter.show_figure`` function return
# the camera position at the time the PyVista interactive plotting window is closed.
# You can also define a plane to use for the camera with 'cpos="xy"'.
# In this case the camera will fit the entire model in the window.
# Starting from a returned 'cpos', you can build a custom camera position, such as:
cpos = [
    (0.005, 0.0004, 0.015),  # Camera position (X, Y, Z)
    (0.005, 0.0004, 0.0),  # Target point (X, Y, Z)
    (0.0, 1.0, 0.0),  # Upward direction (+y)
]
return_cpos = pl_single.show_figure(return_cpos=True, cpos=cpos, show_axes=True)
print(return_cpos)
01 plot surface streamlines
[(0.005, 0.0004, 0.015),
 (0.005, 0.0004, 0.0),
 (0.0, 1.0, 0.0)]

Compute multiple streamlines#

multiple_2d_streamlines, multiple_2d_source = compute_streamlines(
    meshed_region=meshed_region,
    field=field,
    pointa=(0.005, 0.0001, 0.0),
    pointb=(0.005, 0.001, 0.0),
    n_points=10,
    surface_streamlines=True,
    return_source=True,
)

Plot multiple streamlines#

pl_multiple = DpfPlotter()
pl_multiple.add_field(field, meshed_region, opacity=0.2)
pl_multiple.add_streamlines(
    streamlines=multiple_2d_streamlines,
    source=multiple_2d_source,
    radius=0.000015,
)
pl_multiple.show_figure(cpos=cpos, show_axes=True)
01 plot surface streamlines

Total running time of the script: (0 minutes 4.283 seconds)

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