How to map extracted power losses in Icepack using Script to reduce the manual effort.

Mahesh_G

I am extracting power losses for a applied current profile (maximum and minimum) from Maxwell and mapping the corresponding power loss curve in Icepak for a Joule heating problem. This is manual method and taking 30min of time.

lorenzov

Hi,

This script processes power loss data from Maxwell simulations and prepares datasets for
transient analysis in Icepak. The losses are extracted using the AEDT Field Calculator and used to
generate square-wave power loss profiles, which are then applied as transient boundary conditions.

Before running this script, ensure that:

• The Maxwell3D and Icepak projects are properly set up.
• Object names in obj_list match those in your Maxwell project.
• Simulation settings are adapted to your specific project requirements.

from ansys.aedt.core import Icepak
from ansys.aedt.core.maxwell import Maxwell3d


def get_obj_losses(obj_list: list[str], app: Maxwell3d) -> dict:
    """
    Extract power losses from Maxwell3D using the AEDT Field Calculator.

    Parameters:
        obj_list (list[str]): List of object names to extract losses from.
        app (Maxwell3d): Maxwell3D application instance.

    Returns:
        dict: A dictionary with object names as keys and their corresponding power losses as values.
    """
    losses = {}
    for obj in obj_list:
        my_expression = {
            "name": "OhmicLossCalc",
            "description": "Compute ohmic losses",
            "design_type": ["Maxwell3D"],
            "fields_type": ["Fields"],
            "primary_sweep": "Freq",
            "assignment_type": ["Volume"],
            "operations": [
                "NameOfExpression('Ohmic-Loss')",
                f"EnterVolume('{obj}')",
                "Operation('VolumeValue')",
                "Operation('Integrate')"
            ],
            "report": ["Data Table"]
        }
        xpr = app.post.fields_calculator.add_expression(my_expression, obj)
        losses[obj] = app.post.fields_calculator.evaluate(xpr)
    return losses


def generate_dataset(y1: float, y2: float, t1: float, t2: float, n_cycles: int) -> tuple[list[float], list[float]]:
    """
    Generate a time-dependent square wave dataset for transient analysis.

    The generated wave alternates between two power loss values (y1 and y2) over specified time intervals.

    Parameters:
        y1 (float): Power loss during the high state (W).
        y2 (float): Power loss during the low state (W).
        t1 (float): Duration of the high state (s).
        t2 (float): Duration of the low state (s).
        n_cycles (int): Number of cycles to generate.

    Returns:
        tuple[list[float], list[float]]: Two lists representing time (x-values) and corresponding power loss (y-values).
    """
    x_values, y_values = [], []
    period = t1 + t2
    for i in range(n_cycles):
        t_start = i * period
        x_values += [t_start, t_start + t1, t_start + t1, t_start + period]
        y_values += [y1, y1, y2, y2]
    return x_values, y_values


# List of objects for which losses will be computed
obj_list = ["HVA", "HVB", "HVC"]

# Initialize Maxwell3D application
m3d = Maxwell3d()

# Simulate for minimum current condition and extract losses
min_current = "220A"
# Set min_current and run simulation in Maxwell (custom setup needed)
# ...
min_losses = get_obj_losses(obj_list, m3d)

# Simulate for maximum current condition and extract losses
max_current = "340A"
# Set max_current and run simulation in Maxwell (custom setup needed)
# ...
max_losses = get_obj_losses(obj_list, m3d)

# Initialize Icepak application
ipk = Icepak()

# Generate datasets and apply transient boundary conditions in Icepak
for obj in obj_list:
    x, y = generate_dataset(max_losses[obj], min_losses[obj], 10, 30, 5)
    dataset_name = f"{obj}_power"
    ds = ipk.create_dataset(name=dataset_name, x=x, y=y, x_unit="s", y_unit="W", is_project_dataset=False)
    ipk.assign_solid_block(obj, ipk.create_dataset_transient_assignment(ds.name), f"{obj}_block")