Time-averaging Streamline Output

Time-averaging Streamline Output#

Time-averaging Streamline Output in Flow360 allows you to visualize time-averaged streamlines during unsteady simulations. Streamtraces are computed upwind and downwind, and may originate from a single point, from a line, or from points evenly distributed across a parallelogram.

Note: Time-averaging outputs are only available when using unsteady time stepping methods.

Available Options#

Option

Description

Output fields

Flow variables to include along streamlines

Start step

Physical time step to start calculating averaging

Assigned points

Points indicating the locations of streamlines

See also

For the underlying physics and configuration of outputs, see the Output Configuration user guide.

Detailed Descriptions#

Output fields#

The flow variables that will be included along the time-averaged streamlines.

  • Default: None

  • Example: pressure, velocity, Mach

Notes:

  • Time-averaging streamline outputs only support custom variables (UserVariable), not predefined output fields. Create custom variables using the Variable Settings tool or Python API.

  • Vector-valued fields will be colored by their magnitude.

Start step#

The physical time step at which time-averaging begins.

  • Required: Yes

  • Default: None

  • Example: 100 (begin averaging from the 100th physical time step)

Notes:

  • Use positive integers to start averaging from a specific time step.

  • Set this to a time step after initial transients have settled for more meaningful statistics.

  • Important for child cases - this parameter refers to the global time step, which gets transferred from the parent case. See Global Time Stepping in Child Cases for more details.

Assigned points#

Points that define the placement of streamlines. Streamtraces are computed upwind and downwind, and may originate from a single point, from a line, or from points evenly distributed across a parallelogram.

  • Point Definition: The creation of points is described in detail here

Notes:

  • You can specify individual points or arrays of points to seed streamlines at multiple locations.

  • Points can be defined in the GUI or via the Python API.

🐍 Python Example Usage

See also

Python API reference: TimeAverageStreamlineOutput. See also Streamline Output.

# Example of setting up time-averaged streamline output in Python
time_avg_streamline_output = fl.TimeAverageStreamlineOutput(
    entities=[
        fl.Point(
            name="Point_1",
            location=(0.0, 1.5, 0.0) * fl.u.m,
        ),
        fl.Point(
            name="Point_2",
            location=(0.0, -1.5, 0.0) * fl.u.m,
        ),
        fl.PointArray(
            name="Line_streamline",
            start=(1.0, 0.0, 0.0) * fl.u.m,
            end=(1.0, 0.0, -10.0) * fl.u.m,
            number_of_points=11,
        ),
        fl.PointArray2D(
            name="Parallelogram_streamline",
            origin=(1.0, 0.0, 0.0) * fl.u.m,
            u_axis_vector=(0, 2.0, 2.0) * fl.u.m,
            v_axis_vector=(0, 1.0, 0) * fl.u.m,
            u_number_of_points=11,
            v_number_of_points=20
        )
    ],
    output_fields=[fl.solution.pressure, fl.solution.velocity],
    start_step=400,
)
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