from __future__ import annotations
from dataclasses import asdict
import numpy as np
from pythermalcomfort.classes_input import UseFansHeatwavesInputs
from pythermalcomfort.classes_return import UseFansHeatwaves
from pythermalcomfort.models.two_nodes_gagge import two_nodes_gagge
from pythermalcomfort.shared_functions import valid_range
from pythermalcomfort.utilities import Postures
[docs]
def use_fans_heatwaves(
tdb: float | list[float],
tr: float | list[float],
v: float | list[float],
rh: float | list[float],
met: float | list[float],
clo: float | list[float],
wme: float | list[float] = 0,
body_surface_area: float | list[float] = 1.8258,
p_atm: float | list[float] = 101325,
position: str = Postures.standing.value,
max_skin_blood_flow: float = 80,
max_sweating: float = 500,
limit_inputs: bool = True,
round_output: bool = True,
) -> UseFansHeatwaves:
"""Estimate if the conditions you have selected would cause heat strain.
This occurs when either the following variables reaches its
maximum value:
* m_rsw Rate at which regulatory sweat is generated, [mL/h/m2]
* w : Skin wettedness, adimensional. Ranges from 0 and 1.
* m_bl : Skin blood flow [kg/h/m2]
Parameters
----------
tdb : float or list of floats
Dry bulb air temperature, [°C].
tr : float or list of floats
Mean radiant temperature, [°C].
v : float or list of floats
Air speed, [m/s].
rh : float or list of floats
Relative humidity, [%].
met : float or list of floats
Metabolic rate, [met].
clo : float or list of floats
Clothing insulation, [clo].
wme : float or list of floats, optional
External work, [met]. Defaults to 0.
body_surface_area : float or list of floats, optional
Body surface area, default value 1.8258 [m2]. Defaults to 1.8258.
.. note::
The body surface area can be calculated using the function
:py:meth:`pythermalcomfort.utilities.body_surface_area`.
p_atm : float or list of floats, optional
Atmospheric pressure, default value 101325 [Pa]. Defaults to 101325.
position : str, optional
Select either "sitting" or "standing". Defaults to "standing".
max_skin_blood_flow : float
Maximum blood flow from the core to the skin. Defaults to 80.
limit_inputs : bool, optional
By default, if the inputs are outside the standard applicability limits the
function returns nan. If False, returns values even if input values are
outside the applicability limits of the model. Defaults to True. The
applicability limits are 20 < tdb [°C] < 50, 20 < tr [°C] < 50,
0.1 < v [m/s] < 4.5, 0.7 < met [met] < 2, and 0 < clo [clo] < 1.
round_output : bool, optional
If True, rounds output value. If False, it does not round it. Defaults to True.
max_sweating : float or list of floats, optional
Maximum rate at which regulatory sweat is generated, [kg/h/m2]. Defaults to 500.
Returns
-------
UseFansHeatwaves
A dataclass containing the results of using fans during heatwaves.
See :py:class:`~pythermalcomfort.classes_return.UseFansHeatwaves` for more details.
To access the results, use the corresponding attributes of the returned `UseFansHeatwaves` instance, e.g., `result.e_skin`.
Examples
--------
.. code-block:: python
from pythermalcomfort.models import use_fans_heatwaves
result = use_fans_heatwaves(tdb=35, tr=35, v=1.0, rh=50, met=1.2, clo=0.5)
print(result.e_skin) # 63.0
"""
# Validate inputs using the UseFansHeatwavesInputs class
UseFansHeatwavesInputs(
tdb=tdb,
tr=tr,
v=v,
rh=rh,
met=met,
clo=clo,
wme=wme,
body_surface_area=body_surface_area,
p_atm=p_atm,
position=position,
max_skin_blood_flow=max_skin_blood_flow,
limit_inputs=limit_inputs,
)
tdb = np.asarray(tdb)
tr = np.asarray(tr)
v = np.asarray(v)
rh = np.asarray(rh)
met = np.asarray(met)
clo = np.asarray(clo)
wme = np.asarray(wme)
output = two_nodes_gagge(
tdb,
tr,
v,
rh,
met,
clo,
wme=wme,
body_surface_area=body_surface_area,
p_atm=p_atm,
position=position,
max_skin_blood_flow=max_skin_blood_flow,
round_output=False,
max_sweating=max_sweating,
)
output = asdict(output)
output_vars = [
"e_skin",
"e_rsw",
"e_max",
"q_sensible",
"q_skin",
"q_res",
"t_core",
"t_skin",
"m_bl",
"m_rsw",
"w",
"w_max",
"heat_strain_blood_flow",
"heat_strain_w",
"heat_strain_sweating",
"heat_strain",
]
output["heat_strain_blood_flow"] = np.where(
output["m_bl"] == max_skin_blood_flow,
True,
False,
)
output["heat_strain_w"] = np.where(output["w"] == output["w_max"], True, False)
output["heat_strain_sweating"] = np.where(
output["m_rsw"] == max_sweating,
True,
False,
)
output["heat_strain"] = np.any(
[
output["heat_strain_blood_flow"],
output["heat_strain_w"],
output["heat_strain_sweating"],
],
axis=0,
)
output = {key: output[key] for key in output_vars}
if limit_inputs:
# fan_heatwaves applicability limits (extended from ASHRAE 55 baseline).
tdb_valid = valid_range(tdb, (20.0, 50.0))
tr_valid = valid_range(tr, (20.0, 50.0))
v_valid = valid_range(v, (0.1, 4.5))
# rh is range-checked for its side-effect warning but is not included
# in all_valid (matches the function's prior behaviour).
valid_range(rh, (0, 100))
met_valid = valid_range(met, (0.7, 2.0))
clo_valid = valid_range(clo, (0.0, 1.0))
all_valid = ~(
np.isnan(tdb_valid)
| np.isnan(tr_valid)
| np.isnan(v_valid)
| np.isnan(met_valid)
| np.isnan(clo_valid)
)
output = {key: np.where(all_valid, output[key], np.nan) for key in output_vars}
if round_output:
output = {key: np.around(output[key], 1) for key in output_vars}
return UseFansHeatwaves(**output)