Source code for pythermalcomfort.models.e_pmv

import numpy as np

from pythermalcomfort.models import pmv


[docs]def e_pmv(tdb, tr, vr, rh, met, clo, e_coefficient, wme=0, **kwargs): """Returns Adjusted Predicted Mean Votes with Expectancy Factor (ePMV). This index was developed by Fanger, P. O. et al. (2002). In non-air- conditioned buildings in warm climates, occupants may sense the warmth as being less severe than the PMV predicts. The main reason is low expectations, but a metabolic rate that is estimated too high can also contribute to explaining the difference. An extension of the PMV model that includes an expectancy factor is introduced for use in non-air-conditioned buildings in warm climates [26]_. Parameters ---------- tdb : float, int, or array-like dry bulb air temperature, default in [°C] in [°F] if `units` = 'IP' tr : float, int, or array-like mean radiant temperature, default in [°C] in [°F] if `units` = 'IP' vr : float, int, or array-like relative air speed, default in [m/s] in [fps] if `units` = 'IP' Note: vr is the relative air speed caused by body movement and not the air speed measured by the air speed sensor. The relative air speed is the sum of the average air speed measured by the sensor plus the activity-generated air speed (Vag). Where Vag is the activity-generated air speed caused by motion of individual body parts. vr can be calculated using the function :py:meth:`pythermalcomfort.utilities.v_relative`. rh : float, int, or array-like relative humidity, [%] met : float, int, or array-like metabolic rate, [met] clo : float, int, or array-like clothing insulation, [clo] Note: The activity as well as the air speed modify the insulation characteristics of the clothing and the adjacent air layer. Consequently, the ISO 7730 states that the clothing insulation shall be corrected [2]_. The ASHRAE 55 Standard corrects for the effect of the body movement for met equal or higher than 1.2 met using the equation clo = Icl × (0.6 + 0.4/met) The dynamic clothing insulation, clo, can be calculated using the function :py:meth:`pythermalcomfort.utilities.clo_dynamic`. e_coefficient : float expectacy factor wme : float, int, or array-like external work, [met] default 0 Other Parameters ---------------- units : {'SI', 'IP'} select the SI (International System of Units) or the IP (Imperial Units) system. limit_inputs : boolean default True By default, if the inputs are outsude the standard applicability limits the function returns nan. If False returns pmv and ppd values even if input values are outside the applicability limits of the model. The ISO 7730 2005 limits are 10 < tdb [°C] < 30, 10 < tr [°C] < 40, 0 < vr [m/s] < 1, 0.8 < met [met] < 4, 0 < clo [clo] < 2, and -2 < PMV < 2. Returns ------- pmv : float, int, or array-like Predicted Mean Vote Examples -------- .. code-block:: python >>> from pythermalcomfort.models import a_pmv >>> from pythermalcomfort.utilities import v_relative, clo_dynamic >>> tdb = 28 >>> tr = 28 >>> rh = 50 >>> v = 0.1 >>> met = 1.4 >>> clo = 0.5 >>> # calculate relative air speed >>> v_r = v_relative(v=v, met=met) >>> # calculate dynamic clothing >>> clo_d = clo_dynamic(clo=clo, met=met) >>> results = e_pmv(tdb, tr, v_r, rh, met, clo_d, e_coefficient=0.6) >>> print(results) 0.51 """ default_kwargs = {"units": "SI", "limit_inputs": True} kwargs = {**default_kwargs, **kwargs} met = np.array(met) _pmv = pmv(tdb, tr, vr, rh, met, clo, wme, "ISO", **kwargs) met = np.where(_pmv > 0, met * (1 + _pmv * (-0.067)), met) _pmv = pmv(tdb, tr, vr, rh, met, clo, wme, "ISO", **kwargs) return np.around(_pmv * e_coefficient, 2)