# Predicted Thermal Sensation based on 2-Node Model adjusted for Expectancy `calcPtse` calculates Predicted Thermal Sensation based on the 2-Node-Model by Gagge et al. and adjusts its output according to expectancy factor ```r calcPtse(ta, tr, vel, rh, clo = .5, met = 1, wme = 0, pb = 760, ltime = 60, ht = 171, wt = 70, tu = 40, esCoeff) ``` ## 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 [%] - `esCoeff`: a numeric values presenting expectancy factor [-] ## Returns `calcPtse` returns a dataframe containing the Predicted Thermal Sensation value ## 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. ## Note In case one of the variables is not given, a standard value will be taken from a list (see `createCond` for details). ## Examples ```r ## Using several rows of data: ta <- c(20,22,24) tr <- ta vel <- rep(.15,3) rh <- rep(50,3) esCoeff <- 0.5 maxLength <- max(sapply(list(ta, tr, vel, rh), length)) ptse <- sapply(seq(maxLength), function(x) { calcPtse(ta[x], tr[x], vel[x], rh[x], esCoeff=esCoeff) } ) ``` ## 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) The aPMV concept was introduced by Yao, Li & Liu (2009) The ePMV concept was introudced by Fanger & Toftum (2002) ## See Also see also `calcComfInd` and `calc2Node` ## 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.

calcPtse function