calcaPMV {comf}R Documentation

Adaptive Predicted Mean Votes

Description

Function to calculate adaptive Predicted Mean Vote (aPMV) adjusted through the adaptive coefficient.

Usage

calcaPMV(ta, tr, vel, rh, clo = 0.5, met = 1, wme = 0, apCoeff)

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]

apCoeff

adaptive coefficient lambda

Details

apCoeff can be derived using calcapCoeff.

Value

calcaPMV returns the predicted mean vote adjusted through the adaptive coefficients.

Note

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

Author(s)

Code implemented in to R by Marcel Schweiker. Further contribution by Sophia Mueller and Shoaib Sarwar.

References

aPMV is based on Yao, Li and Liu (2009) <doi:10.1016/j.buildenv.2009.02.014>

See Also

calcComfInd, calcapCoeff

Examples

## 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 coefficient apCoeff for data set
apCoeff <- calcapCoeff(lsCond)
## calculate apmv
apmv <- NULL
for (i in 1:length(ta)){
 apmv[i] <- calcaPMV(ta[i], tr[i], vel[i], rh[i], clo[i], met[i], apCoeff = apCoeff)$apmv}
apmv

[Package comf version 0.1.12 Index]