pyrc.validation.conduction.analytic#

get_k(resistance_terms: list)#

Calculates k.

Parameters:

resistance_terms (list) – The resistance terms. E.g.: thickness/thermal_conductivity or 1/alpha.

Returns:

k in W/K/m/m

Return type:

float

line_heat_conduction(range_x: list | ndarray | tuple, thickness: float | int, delta_temperature: float | int, lower_temperature: float | int = 0) → ndarray#
Parameters:

  • range_x (list | np.ndarray | tuple) – The x values to calculate the temperature for.

  • thickness (float | int) – The thickness of the material in m.

  • delta_temperature (float | int) – The temperature difference in K.

  • lower_temperature (float | int, optional) – The lower temperature in K or °C.

Returns:

The temperature values for the given range_x through the material.

Return type:

np.ndarray

major_temperatures(walls: list, lower_temperature: float | int, upper_temperature: float | int)#
Parameters:

  • walls (list) –

    Tuples defining the walls in ascending temperature order. Each tuple consists of:

    1. thickness in m

    2. thermal conductivity coefficient in W/m/K

  • lower_temperature (float | int) – The lower temperature in K

  • upper_temperature (float | int) – The upper temperature in K

Returns:

The temperatures between and at start/beginning of the walls.

Return type:

list

make_temp_data(walls: list, lower_temperature: float | int, upper_temperature: float | int, number_points: int) → tuple[ndarray, ndarray]#
run_conduction_analytic(plot_data=True)#