s <- suppressPackageStartupMessages
s(library(data.table))
s(library(lubridate))
s(library(knitr))
s(library(dygraphs))
s(library(ggplot2))

1 Introduction

This R Notebook utilizes the javascript functions from the CBE Comfort Tool, freely available on the website’s Github in order to estimate the thermal comfort of the students of FROG UHM.

2 Readings

The readings are a sample data from the frog-uhm project provided by Eileen Peppard to test the tool.

readings <- fread("~/Downloads/template_IP_dhhl_house8_aug_sept.csv")

2.1 Used Variables

Of the provided data, the following variables were used:

Air Temperature
Mean Radiant Temperature
Relative Air Velocity
Relative Humidity

In addition, the following artificially created variables were used:

Metabolic Rate = 1.1
Clothing Level = 0.5
External Work = 0 (According to the CBE Comfort Tool Documentation)

colnames(readings) <- c("ta","tr","vel","rh","met","clo") 
readings$wme <- 0

3 Conversions

For the CBE Comfort Tool, the following units must be respected for the variables:

Air Temperature, Mean Radiant Temperature = C
Relative Air Velocity = m/s
Relative Humidity = %

And were converted from the sample data to meet the expected units.

readings_si <- readings
#Convert F to C
readings_si$ta <- (readings$ta - 32)*(5/9)
readings_si$tr <- (readings$tr - 32)*(5/9)

# Convert fpm to m/s
readings_si$vel <- 0.00508 * readings$vel

4 Elevated Air Speed PMV Model

This notebook uses the javascript function from the CBE Comfort Tool by passing the sample data after preparation as input, and then retrieving the output of the function which contains the PMV and PPD.

5 Merge Results with Timestamps and Readings

After the model results is output, the data is combined with the original readings for comparison.

pmv_elevated_air <- cbind(readings,pmv_elevated_air)

6 PMV Results

In addition to PMV and PPD, the following columns are also output in the table (not shown below):

SET
TA_adj
TR_adj
cooling_effect

The first 3 columns relate to the Elevated Airspeed adjustmenet to the PMV model, which can’t handle high air speeds in the original proposal by Fanger.

6.1 Output Table

First few rows of the table for Frogs 1.

# Convert ta to tr 
pmv_elevated_air$ta_adj <- pmv_elevated_air$ta_adj*1.8 + 32
pmv_elevated_air$tr_adj <- pmv_elevated_air$tr_adj*1.8 + 32
kable(head(pmv_elevated_air))

ta	tr	vel	rh	met	clo	pmv	ppd	set	ta_adj	tr_adj	cooling_effect
84.900	84.900	32	58.548	1	1.1	1.771195	65.52252	32.58639	84.34185	84.34185	0.3100947
84.945	84.945	32	58.583	1	1.1	1.778521	65.90511	32.61514	84.38707	84.38707	0.3099731
84.722	84.722	32	55.662	1	1.1	1.711599	62.37170	32.23582	84.15227	84.15227	0.3165170
83.959	83.959	32	53.122	1	1.1	1.567876	54.59564	31.61651	83.38042	83.38042	0.3214231
83.332	83.332	32	50.514	1	1.1	1.445843	47.96911	31.09290	82.74630	82.74630	0.3254112
82.441	82.441	32	49.420	1	1.1	1.301822	40.36219	30.55440	81.85504	81.85504	0.3255535

7 Plot

pmv_elevated_air$is_acceptable <- NA_character_
pmv_elevated_air[ppd > 5]$is_acceptable <- ">5"


pmv_elevated_air[ppd < -5]$is_acceptable <- "Unacceptable Cold"
pmv_elevated_air[ppd >= -5 & ppd <= 5]$is_acceptable <- "Acceptable"

ggplot() +
  aes(pmv_elevated_air$pmv) +
  geom_histogram(binwidth = 0.5, fill="black", col="grey") +
  scale_x_continuous(breaks = seq(-5,5,0.5), lim = c(-5,5)) + theme_minimal() + 
  xlab("PMV") + 
  ylab("Number of Hours")

PMV PPD

Carlos V. Paradis

March 22, 2018