General: optimetrics setup#

This example shows how you can use PyAEDT to create a project in HFSS and create all optimetrics setups.

Perform required imports#

Perform required imports.

import pyaedt

import os

Set AEDT version#

Set AEDT version.

aedt_version = "2024.1"

Set non-graphical mode#

Set non-graphical mode. You can set non_graphical either to True or False.

non_graphical = False

Initialize object and create variables#

Initialize the Hfss object and create two needed design variables, w1 and w2.

hfss = pyaedt.Hfss(specified_version=aedt_version, new_desktop_session=True, non_graphical=non_graphical)
hfss["w1"] = "1mm"
hfss["w2"] = "100mm"

Create waveguide with sheets on it#

Create one of the standard waveguide structures and parametrize it. You can also create rectangles of waveguide openings and assign ports later.

wg1, p1, p2 = hfss.modeler.create_waveguide(
    [0, 0, 0],
    hfss.AXIS.Y,
    "WG17",
    wg_thickness="w1",
    wg_length="w2",
    create_sheets_on_openings=True,
)

model = hfss.plot(show=False)

model.show_grid = False
model.plot(os.path.join(hfss.working_directory, "Image.jpg"))
Optimetrics
True

Create wave ports on sheets#

Create two wave ports on the sheets.

hfss.wave_port(p1, integration_line=hfss.AxisDir.ZPos, name="1")
hfss.wave_port(p2, integration_line=hfss.AxisDir.ZPos, name="2")
<pyaedt.modules.Boundary.BoundaryObject object at 0x000001A7FFA94100>

Create setup and frequency sweep#

Create a setup and a frequency sweep to use as the base for optimetrics setups.

setup = hfss.create_setup()
hfss.create_linear_step_sweep(
    setupname=setup.name, unit="GHz", freqstart=1, freqstop=5, step_size=0.1, sweepname="Sweep1", save_fields=True
)
<pyaedt.modules.SolveSweeps.SweepHFSS object at 0x000001A7FFC1A9B0>

Optimetrics analysis#

Create parametrics analysis#

Create a simple optimetrics parametrics analysis with output calculations.

sweep = hfss.parametrics.add("w2", 90, 200, 5)
sweep.add_variation("w1", 0.1, 2, 10)
sweep.add_calculation(calculation="dB(S(1,1))", ranges={"Freq": "2.5GHz"})
sweep.add_calculation(calculation="dB(S(1,1))", ranges={"Freq": "2.6GHz"})
True

Create sensitivity analysis#

Create an optimetrics sensitivity analysis with output calculations.

sweep2 = hfss.optimizations.add(calculation="dB(S(1,1))", ranges={"Freq": "2.5GHz"}, optim_type="Sensitivity")
sweep2.add_variation("w1", 0.1, 3, 0.5)
sweep2.add_calculation(calculation="dB(S(1,1))", ranges={"Freq": "2.6GHz"})
True

Create optimization based on goals and calculations#

Create an optimization analysis based on goals and calculations.

sweep3 = hfss.optimizations.add(calculation="dB(S(1,1))", ranges={"Freq": "2.5GHz"})
sweep3.add_variation("w1", 0.1, 3, 0.5)
sweep3.add_goal(calculation="dB(S(1,1))", ranges={"Freq": "2.6GHz"})
sweep3.add_goal(calculation="dB(S(1,1))", ranges={"Freq": ("2.6GHz", "5GHz")})
sweep3.add_goal(
    calculation="dB(S(1,1))",
    ranges={"Freq": ("2.6GHz", "5GHz")},
    condition="Maximize",
)
True

Create DX optimization based on a goal and calculation#

Create a DX (DesignXplorer) optimization based on a goal and a calculation.

sweep4 = hfss.optimizations.add(calculation="dB(S(1,1))", ranges={"Freq": "2.5GHz"}, optim_type="DesignExplorer")
sweep4.add_goal(calculation="dB(S(1,1))", ranges={"Freq": "2.6GHz"})
True

Create DOE based on a goal and calculation#

Create a DOE (Design of Experiments) based on a goal and a calculation.

sweep5 = hfss.optimizations.add(calculation="dB(S(1,1))", ranges={"Freq": "2.5GHz"}, optim_type="DXDOE")

Create DOE based on a goal and calculation#

Create a DOE based on a goal and a calculation.

region = hfss.modeler.create_region()
hfss.assign_radiation_boundary_to_objects(region)
hfss.insert_infinite_sphere(name="Infinite_1")
sweep6 = hfss.optimizations.add(
    calculation="RealizedGainTotal",
    solution=hfss.nominal_adaptive,
    ranges={"Freq": "5GHz", "Theta": ["0deg", "10deg", "20deg"], "Phi": "0deg"},
    context="Infinite_1",
)

Close AEDT#

After the simulaton completes, you can close AEDT or release it using the pyaedt.Desktop.release_desktop() method. All methods provide for saving the project before closing.

hfss.release_desktop()
True

Total running time of the script: (0 minutes 55.610 seconds)

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