calcePMV: Adjusted Predicted Mean Votes with Expectancy Factor

View source: R/calcePMV.R

calcePMVR Documentation

Adjusted Predicted Mean Votes with Expectancy Factor

Description

Function to calculate Predicted Mean Votes (PMV) adjusted by the expectancy factor.

Usage

calcePMV(ta, tr, vel, rh, clo = 0.5, met = 1, wme = 0, epCoeff)

ePMV(ta, tr, vel, rh, clo = 0.5, met = 1, wme = 0, epCoeff)

epmv(ta, tr, vel, rh, clo = 0.5, met = 1, wme = 0, epCoeff)

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]

epCoeff

expectancy factor e

Details

epCoeff can be derived using calcepCoeff.

calcePMV requires the actual sensation vote related to the physical data as it is required to alter the metabolic rate.

Value

calcePMV returns the predicted mean vote adjusted by the expectancy factor.

Note

In case one of epCoeff 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

epmv is based on Fanger & Toftum (2002) <doi:10.1016/S0378-7788(02)00003-8>

See Also

calcComfInd, calcepCoeff

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 epCoeff for data set
epCoeff <- calcepCoeff(lsCond)
## calculate epmv
epmv <- NULL
for (i in 1:length(ta)){
 epmv[i] <- calcePMV(ta[i], tr[i], vel[i], rh[i], clo[i], met[i], epCoeff = epCoeff)$epmv}
epmv

marcelschweiker/comfort_R documentation built on Feb. 22, 2024, 9:04 p.m.