calcepCoeff | R Documentation |
The functions calcCOEFF
calculate the coefficients necessary for apmv, epmv, apts, and epts based on a given dataset with actual comfort votes. calcapCoeff
calculates lambda the adaptive coefficients for apmv, calcepCoeff
calculates e the expectancy factor for epmv, calcasCoeff
calculates lambda the adaptive coefficients for apts, calcesCoeff
calculates e the expectancy factor for epts.
calcapCoeff(lsCond)
calcepCoeff(lsCond)
calcasCoeff(lsCond)
calcesCoeff(lsCond)
lsCond |
a list with vectors for the necessary variables (see details) . |
calcCOEFF
returns the adaptive coefficient lambda or expectancy factor depending on its call.
For calcapCoeff
and calcepCoeff
, lsCond should contain the following variables: ta, tr, vel, rh, clo, met, wme, asv (see createCond
for details). In case one or more of these variables are not included in the list, standard values will be used.
For calcasCoeff
and calcesCoeff
, lsCond should contain the following variables: ta, tr, vel, rh, clo, met, wme, pb, ltime, ht, wt, asv (see createCond
for details). In case one or more of these variables are not included in the list, standard values will be used.
Marcel Schweiker.
Coefficients are calculated based on Gao, J.; Wang, Y. and Wargocki, P. Comparative analysis of modified PMV models and set models to predict human thermal sensation in naturally ventilated buildings Building and Environment, 2015, 92, 200-208.
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 calcaPMV
, calcePMV
, calcPtsa
, calcPtse
## Note. Due to random generated asv values. The values for the coefficients will not be meaningful.
## Create sample data
ta <- 20:24 # vector with air temperature values
tr <- ta # vector with radiant temperature values
vel <- rep(.1,5) # vector with air velocities
rh <- rep(50,5) # vector with relative humidity values
clo <- rep(1.0,5) # vector with clo values
met <- rep(1.1,5) # vector with metabolic rates
asv <- rnorm(5) # vector with actual sensation votes
lsCond <- as.list(data.frame(ta,tr,vel,rh,clo,met,asv))
## Calculate coefficients
calcapCoeff(lsCond)
calcepCoeff(lsCond)
calcasCoeff(lsCond)
calcesCoeff(lsCond)
## use coefficients to calculate apmv
lsCond$apCoeff[1] <- calcapCoeff(lsCond)$apCoeff
calcComfInd(lsCond, request="apmv")
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