ConvectiveCooling

ConvectiveCooling

ConvectiveCooling(
    altitude: floatArrayLike,
    cable_azimuth: floatArrayLike,
    ambient_temperature: floatArrayLike,
    wind_speed: floatArrayLike,
    outer_diameter: floatArrayLike,
    wind_azimuth: floatArrayLike = None,
    wind_attack_angle: floatArrayLike = None,
    **kwargs: Any,
)

Bases: ConvectiveCoolingBase

Convective cooling term.

If more than one input are numpy arrays, they should have the same size.

Parameters:

Name	Type	Description	Default
altitude	float | ndarray	Altitude (m).	required
cable_azimuth	float | ndarray	Azimuth (deg).	required
ambient_temperature	float | ndarray	Ambient temperature (°C).	required
wind_speed	float | ndarray	Wind speed (m·s⁻¹).	required
wind_azimuth	float | ndarray	wind_azimuth regarding north (deg).	None
outer_diameter	float | ndarray	External diameter (m).	required

Source code in src/thermohl/power/ieee/convective_cooling.py

def __init__(
    self,
    altitude: floatArrayLike,
    cable_azimuth: floatArrayLike,
    ambient_temperature: floatArrayLike,
    wind_speed: floatArrayLike,
    outer_diameter: floatArrayLike,
    wind_azimuth: floatArrayLike = None,
    wind_attack_angle: floatArrayLike = None,
    **kwargs: Any,
):
    r"""Init with args.

    If more than one input are numpy arrays, they should have the same size.

    Args:
        altitude (float | numpy.ndarray): Altitude (m).
        cable_azimuth (float | numpy.ndarray): Azimuth (deg).
        ambient_temperature (float | numpy.ndarray): Ambient temperature (°C).
        wind_speed (float | numpy.ndarray): Wind speed (m·s⁻¹).
        wind_azimuth (float | numpy.ndarray): wind_azimuth regarding north (deg).
        outer_diameter (float | numpy.ndarray): External diameter (m).

    """
    super().__init__(
        altitude,
        cable_azimuth,
        ambient_temperature,
        wind_speed,
        outer_diameter,
        Air.volumic_mass,
        Air.dynamic_viscosity,
        Air.thermal_conductivity,
        wind_azimuth,
        wind_attack_angle,
    )

derivative

derivative(
    conductor_temperature: floatArrayLike,
    temperature_increment: float = _TEMP_INCREMENT,
) -> floatArrayLike

Compute power term derivative regarding temperature in function of temperature.

Usually this function should be overriden in children classes; if it is not the case it will evaluate the derivative from the value method with a second-order approximation.

Parameters:

Name	Type	Description	Default
conductor_temperature	float | ndarray	Conductor temperature (°C).	required
temperature_increment	float	Temperature increment. The default is 1.0E-03.	_TEMP_INCREMENT

Returns:

Type	Description
floatArrayLike	float | numpy.ndarray: Power term derivative (W·m⁻¹·K⁻¹).

Source code in src/thermohl/power/power_term.py

def derivative(
    self,
    conductor_temperature: floatArrayLike,
    temperature_increment: float = _TEMP_INCREMENT,
) -> floatArrayLike:
    r"""Compute power term derivative regarding temperature in function of temperature.

    Usually this function should be overriden in children classes; if it is
    not the case it will evaluate the derivative from the value method with
    a second-order approximation.

    Args:
        conductor_temperature (float | numpy.ndarray): Conductor temperature (°C).
        temperature_increment (float, optional): Temperature increment. The default is 1.0E-03.

    Returns:
        float | numpy.ndarray: Power term derivative (W·m⁻¹·K⁻¹).

    """
    return (
        self.value(conductor_temperature + temperature_increment)
        - self.value(conductor_temperature - temperature_increment)
    ) / (2.0 * temperature_increment)

value

value(
    conductor_temperature: floatArrayLike,
) -> floatArrayLike

Compute convective cooling.

Parameters:

Name	Type	Description	Default
conductor_temperature	float | ndarray	Conductor temperature (°C).	required

Returns:

Type	Description
floatArrayLike	float | numpy.ndarray: Power term value (W·m⁻¹).

Source code in src/thermohl/power/convective_cooling.py

def value(self, conductor_temperature: floatArrayLike) -> floatArrayLike:
    r"""Compute convective cooling.

    Args:
        conductor_temperature (float | numpy.ndarray): Conductor temperature (°C).

    Returns:
        float | numpy.ndarray: Power term value (W·m⁻¹).

    """
    film_temperature = 0.5 * (conductor_temperature + self.ambient_temp)
    temperature_delta = conductor_temperature - self.ambient_temp
    air_density = self.air_density(film_temperature, self.altitude)
    return np.maximum(
        self._value_forced(film_temperature, temperature_delta, air_density),
        self._value_natural(temperature_delta, air_density),
    )