calcPtsa {comf}

Predicted Thermal Sensation based on 2-Node Model adjusted for Adaptation

Description

calcPtsa calculates Predicted Thermal Sensation based on the 2-Node-Model by Gagge et al. and adjusts its output according to adaptive coefficient

Usage

calcPtsa(ta, tr, vel, rh, clo = .5, met = 1, wme = 0, pb = 760, 
                     ltime = 60, ht = 171, wt = 70, tu = 40, asCoeff)

Arguments

ta

a numeric value presenting air temperature in [degree C]

tr

a numeric value presenting mean radiant temperature in [degree C]

vel

a numeric value presenting air velocity in [m/s]

rh

a numeric value presenting relative humidity [%]

clo

a numeric value presenting clothing insulation level in [clo]

met

a numeric value presenting metabolic rate in [met]

wme

a numeric value presenting external work in [met]

pb

a numeric value presenting barometric pressure in [torr] or [mmHg]

ltime

a numeric value presenting exposure time in [minutes]

ht

a numeric value presenting body height in [cm]

wt

a numeric value presenting body weight in [kg]

tu

a numeric value presenting turbulence intensity in [%]

asCoeff

a numeric values presenting adaptive coefficient [-]

Details

All variables must have the same length 1. For the calculation of several values use function calcComfInd. The value of obj defines whether the function will use the version presented in ASHRAE 55-2013 for adjustment of pmv (obj = "pmvadj"), or the original code by Gagge to calculate set (obj = "set"). In the version presented in ASHRAE 55-2013, the lines of code related to self-generated convection is deleted. Therefore, a difference can only be seen at higher values of met.

Value

calcPtsa returns a dataframe containing the Predicted Thermal Sensation value

Note

In case one of the variables is not given, a standard value will be taken from a list (see createCond for details).

Author(s)

The code for calc2Node is based on the code in BASIC and C++ presented by Fountain and Huizenga (1995). The translation into R-language and comparison with ASHRAE 55-2013 conducted by Marcel Schweiker.

References

ASHRAE Standard 55-2013. Thermal environmental conditions for human occupancy. American society of heating, Refrigerating and Air-Conditioning Engineering, Atlanta, USA, 2013. Fountain & Huizenga (1995) A thermal sensation model for use by the engineering profession ASHRAE RP-781 Final report.

Gagge, Fobelets & Berglund (1986) A standard predictive index of human response to the thermal environment, ASHRAE transactions, 92 (2B), 709-731. Coefficients are calculated based on Gao, Wang & Wargocki (2015) <doi:10.1016/j.buildenv.2015.04.030> The aPMV concept was introduced by Yao, Li & Liu (2009) <doi:10.1016/j.buildenv.2009.02.014> The ePMV concept was introudced by Fanger & Toftum (2002) <doi:10.1016/S0378-7788(02)00003-8>

See Also

see also calcComfInd and calc2Node

Examples

## Using several rows of data:
ta <- c(20,22,24)
tr <- ta
vel <- rep(.15,3)
rh <- rep(50,3)
asCoeff <- 0.5

maxLength <- max(sapply(list(ta, tr, vel, rh,asCoeff), length))
ptsa <- sapply(seq(maxLength), function(x) { calcPtsa(ta[x], tr[x], vel[x],
rh[x], asCoeff=asCoeff) } )