Single bead evaluation plot

This example shows how to use PyAdditive-Widgets to visualize the results of a parametric study containing single bead simulations. It uses the display package to visualize the results of the study.

Units are SI (m, kg, s, K) unless otherwise noted.

Perform required imports and create study

Perform the required imports and create a ParametricStudy instance.

from ansys.additive.core import Additive, SimulationStatus, SimulationType
from ansys.additive.core.parametric_study import ColumnNames, ParametricStudy

from ansys.additive.widgets import display

study = ParametricStudy("single-bead-study")

Saving parametric study to /home/runner/work/pyadditive-widgets/pyadditive-widgets/examples/single-bead-study.ps

Get name of study file

The current state of the parametric study is saved to a file on each update. The following code retrieves the name of the file. This file uses a binary format and is not human readable.

print(study.file_name)

/home/runner/work/pyadditive-widgets/pyadditive-widgets/examples/single-bead-study.ps

Select material for study

Select a material to use in the study. The material name must be known by the Additive service. You can connect to the Additive service and print a list of available materials prior to selecting one.

additive = Additive()
additive.materials_list()
material = "IN718"

2024-06-14 17:22:20 Connected to dns:///localhost:50052
user data path: /home/runner/.local/share/pyadditive

Create single bead evaluation

Generate single bead simulation permutations using the generate_single_bead_permutations() method. This method’s parameters allow you to specify a range of machine parameters and filter them by energy density. Not all the parameters shown are required. Optional parameters that are not specified use the default values defined in the MachineConstants class.

import numpy as np

# Specify a range of laser powers. Valid values are 50 to 700 W.
initial_powers = np.linspace(50, 700, 7)
# Specify a range of laser scan speeds. Valid values are 0.35 to 2.5 m/s.
initial_scan_speeds = np.linspace(0.35, 2.5, 5)
# Specify powder layer thicknesses. Valid values are 10e-6 to 100e-6 m.
initial_layer_thicknesses = [40e-6, 50e-6]
# Specify laser beam diameters. Valid values are 20e-6 to 140e-6 m.
initial_beam_diameters = [80e-6]
# Specify heater temperatures. Valid values are 20 - 500 C.
initial_heater_temps = [80]
# Restrict the permutations within a range of energy densities
# For a single bead, the energy density is laser power / (laser scan speed * layer thickness).
min_energy_density = 2e6
max_energy_density = 8e6
# Specify a bead length in meters.
bead_length = 0.001

study.generate_single_bead_permutations(
    material_name=material,
    bead_length=bead_length,
    laser_powers=initial_powers,
    scan_speeds=initial_scan_speeds,
    layer_thicknesses=initial_layer_thicknesses,
    beam_diameters=initial_beam_diameters,
    heater_temperatures=initial_heater_temps,
    min_area_energy_density=min_energy_density,
    max_area_energy_density=max_energy_density,
)

Show simulations as a table

Use the display package to list the simulations as a table.

display.show_table(study)

show_table

Skip some simulations

If you are working with a large parametric study, you might want to skip some simulations to reduce processing time. To do so, set the simulation status, which is defined in the SimulationStatus class, to SimulationStatus.SKIP. The following code obtains a DataFrame object, applies a filter to get a list of simulation IDs, and then updates the status on the simulations with those IDs.

df = study.data_frame()
# Get IDs for single bead simulations with laser power below 75 W.
ids = df.loc[
    (df[ColumnNames.LASER_POWER] < 75) & (df[ColumnNames.TYPE] == SimulationType.SINGLE_BEAD),
    ColumnNames.ID,
].tolist()
study.set_status(ids, SimulationStatus.SKIP)
display.show_table(study)

show_table

Run single bead simulations

Run the simulations using the run_simulations() method. All simulations with a SimulationStatus.PENDING status are executed.

study.run_simulations(additive)

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Plot single bead results

Plot the single bead results using the single_bead_eval_plot() function.

display.single_bead_eval_plot(study)

single_bead_eval_plot