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Nisr United States Department of Commerce

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National Institute of Standards and Technology

NIST BUILDING SCIENCE SERIES 173

Heat and Moisture Transfer in Wood-Based

Wall Construction: Measured Versus Predicted

R. R. Zarr, D. M. Burch and A. H. Fanney

.U58

NO. 173

1995
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NIST BUILDING SCIENCE SERIES 173

Heat and Moisture Transfer in Wood-Based

Wall Construction: Measured Versus Predicted

R. R. Zarr, D. M. Burch and A. H. Fanney

Building and Fire Research Laboratory

National Institute of Standards and Technology

Gaithersburg, MD 20899-0001

February 1995

U.S. Department of Commerce

Ronald H. Brown, Secretary

Technology Administration

Mary L. Good, Under Secretary for Technology

National Institute of Standards and Teciinology

Arati Prabhakar, Director
National Institute of Standards and Technology Building Science Series 173

Natl. Inst. Stand. Technol. BIdg. Sci. Ser. 173, 83 pages (Feb. 1995)

CODEN: NBSSES

U.S. GOVERNMENT PRINTING OFFICE

WASHINGTON: 1995

For sale by the Superintendent of Documents, U.S. Government Printing Office, Washington, DC 20402-9325
ABSTRACT

The National Institute of Standards and Technology has developed a personal computer program,

MOIST, that predicts the transient one-dimensional heat and moisture transfer in building

envelopes. MOIST allows the user to vary building materials, their relative placement within the

building envelope, and the geographic location of the building. For a given geometry and

location, it predicts the resulting moisture accumulation and transfer across each construction

layer as a function of time.

This report describes a comprehensive laboratory study to verify the accuracy of MOIST for 12

different wall specimens. The rate of heat transfer through each of the 12 wall specimens was

measured. The moisture content of the exterior construction materials were measured for eight

of the twelve wall specimens. For the remaining four walls, the relative humidity level was

measured at the interior side of the exterior sheathing. The measured heat transfer rates,

moisture content levels and relative humidities were compared to the predictions of MOIST.

In general, the agreement between MOIST and the experimental measurements was good. The

moisture content predicted by MOIST was within one percent of the measured values for seven

of the eight walls that contained moisture content sensors. The measured relative humidities for

two of the remaining four walls agreed well with the MOIST predictions. The relative humidity

measurements from the other two walls could not be compared to MOIST since the walls were

constructed with vapor retarder defects that introduced two-dimensional effects. The heat flux

predicted by MOIST was within ten percent of the values measured under steady-state

conditions. When the walls were subjected to a series of diurnal ambient temperature cycles, the

root-mean-square difference between the measured and predicted heat flux values ranged from

four to fifteen percent. MOIST heat flux predictions were also in close agreement with the

values predicted by the Thermal Analysis Research Program (TARP).

A comparison was made between measured steady-state thermal resistances and corresponding

calculated values using procedures recommended by The American Society of Heating,

Refrigerating, and Air Conditioning Engineers (ASHRAE). The ASHRAE calculations agreed

with the measured values within thirteen percent.

Keywords

apparatus; building science; building technology; calibrated hot box; computer models;

experiment; heat transfer; mass transfer; MOIST; moisture transfer; relative humidity;

temperature; thermal resistance; validation; wall

iii

TABLE OF CONTENTS

Page

ABSTRACT iii INTRODUCTION 1 EXPERIMENT 2

Overview 2

Wall Specimens 2

Calibrated Hot Box 8

Data Acquisition 10

Boundary Conditions 10

Measurements 12

Temperature 12

Heat flux 12

Moisture Content 16

Relative Humidity 21

SPECIMEN MATERIALS PROPERTIES 23

Sorption Isotherms 23

Permeability Measurements 25

Thermal Conductivity Measurements 28

COMPARISON OF EXPERIMENTAL RESULTS TO MOIST 34

Moisture Content Comparisons 34

Base Case - Wall Specimen 1 34

Effect of Vapor Retarder - Wall Specimen 2 36

Effect of Paint Coatings - Wall Specimens 3 and 4 36

Effect of Sheathing - Wall Specimens 5 and 6 39

Effect of Cavity Insulation - Wall Specimens 7 and 8 39

Modeling Insulation as a Storage Layer 43

Typical Wall Construction and Vapor Retarder Defects - Wall Specimens 9 to 12 43

Summary of Moisture Content Comparisons 46

Heat Flux Comparisons 46

COMPARISONS OF MOIST AND TARP 51

v
TABLE OF CONTENTS (continued)

Page

COMPARISON OF STEADY-STATE HEAT FLUX MEASUREMENTS TO

ASHRAE PREDICTIONS 53

EFFECT OF MOISTURE ON HEAT TRANSFER 58

SUMMARY AND CONCLUSIONS 61

ACKNOWLEDGMENTS 63

REFERENCES 64

APPENDIX A - BUILDING MATERIALS 66

APPENDIX B - PERMEANCE MEASUREMENTS 67

Thermal Insulation Materials 67

Gypsum Wallboard 69

Paint Layers 72

Latex Paint Applied to Gypsum Wallboard 72

Oil & Latex Paint Applied to Sugar Pine 72

Convective Airspace 72

vi
LIST OF FIGURES

Page

Figure 1 Wall Specimen Location Within Calibrated Hot Box (Exterior View) .... 3

Figure 2 Meter Section Construction Details 4

Figure 3 Wall Specimen Construction Details 6

Figure 4 Schematic of the NIST Calibrated Hot Box 9

Figure 5 Climatic Chamber Boundary Conditions 11

Figure 6 Wall Specimen Sensor Locations 13

Figure 7 Typical Heat Flux Transducer Calibration Curve 15

Figure 8 Construction and Location of Moisture Content Sensors 17

Figure 9 Sugar Pine Moisture Content Time Response 19

Figure 10 Typical Moisture Content Sensor Calibration Curves for Sugar Pine .... 19

Figure 1 1 Variability in Moisture Content Sensors 20

Figure 12 Sensor-to-Sensor Variability of Sugar Pine Moisture Content Sensors ... 20

Figure 13 Relative Humidity Sensor Calibration Curves 22

Figure 14 Sugar Pine Sorption Measurements 24

Figure 15 Sugar Pine Permeability Measurements 27

Figure 16 Guarded Hot Plate Apparatus 29

Figure 17 Thermal Conductivity of Glass-Fiber Insulation as a Function of

Specimen Density 32

Figure 18 Distribution of Moisture Content on Interior Surface of Sugar Pine .... 35

Figure 19 Measured and Predicted Moisture Content - Wall Specimen 1 35

Figure 20 Measured and Predicted Moisture Content - Wall Specimen 2 37

vii
LIST OF FIGURES (continued)

Page

Figure 21 Measured and Predicted Moisture Content - Wall Specimen 3 37

Figure 22 Measured and Predicted Moisture Content - Wall Specimen 4 38

Figure 23 Measured and Predicted Moisture Content - Wall Specimen 5 40

Figure 24 Measured and Predicted Moisture Content - Wall Specimen 6 41

Figure 25 Measured and Predicted Moisture Content - Wall Specimen 7 42

Figure 26 Measured Surface Relative Humidities - Wall Specimens

9, 10, and 12 44

Figure 27 Measured and Predicted Surface Relative Humidity - Wall Specimen 9 . . 45

Figure 28 Measured and Predicted Surface Relative Humidity - Wall Specimen 12 . 45

Figure 29 Measured and Predicted Heat Flux - Wall Specimen 1 48

Figure 30 Comparison Between Measured and Predicted Steady-State Heat Fluxes . 48

Figure 31 Measured and Predicted Heat Fluxes 50

Figure 32 MOIST and TARP Predicted Heat Fluxes - Wall Specimen 1 52

Figure 33 Measured Versus Predicted Thermal Resistance 57

Figure 34 Comparison of Ambient Outdoor Temperatures (First Versus Second

Series Sinewaves) 59

Figure 35 Comparison of Heat Fluxes (First Versus Second Series Sinewaves) .... 60

Figure B-1 Permeability Test Method for Stagnant Air 68

Figure B-2 Water Vapor Permeability of a Stagnant Air Layer 70

Figure B-3 Permeability Test Method for Gypsum Wallboard 71

Figure B-4 Water Vapor Transfer Resistance Versus Thickness for Gypsum

Wallboard 71

viii
LIST OF TABLES

Page

Table 1 Wall Specimen Constructions 7

Table 2 Climatic Chamber Conditions 10

Table 3 Heat Flux Transducer Regression Coefficients 16

Table 4 Standard Deviation of Sugar Pine Moisture Content Sensors (%MC) ... 21

Table 5 Sorption Isotherm Regression Coefficients 25

Table 6 Permeability Regression Coefficients 26

Table 7 Permeance of Paint Layers and Convective Airspace 26

Table 8 Guarded Hot Plate Measurements 30

Table 9 Local Thermal Conductivities for Cylindrical Core Samples of

Glass-Fiber Batt Insulation 33

Table 10 Summary of Root-Mean-Square Differences Between Measured and

Predicted Moisture Contents 46

Table 1 1 Comparison of Steady Heat Fluxes (W/m^) 47

Table 12 Summary of Root-Mean-Square Differences Between Measured and

Predicted Heat Fluxes 49

Table 13 Steady-State Thermal Transmission Properties and Predicted

Heat Fluxes 55

Table 14 R-Value Comparison for Days 10 through 14 56

Table B-1 Relative Humidities above Salt Solutions 67

ix
NOMENCLATURE

a constant in Equation (9), W/(m2-K^^'^^)

A cross-sectional area,

Ao constant coefficient for heat flux transducer function, W/m^

Ai linear coefficient for heat flux transducer function, W/(m'^'mV)

b constant in Equation (9), W-s/(m^-K)

Bj 2,3 coefficients for sorption-isotherm function

Cp specific heat of air at constant pressure, J/(kg-K)

Cj 2,3 coefficients for permeability function

Do coefficient for thermal-conductivity function, W/(m-K)

Dj coefficient for thermal-conductivity function, W-m^/(kg-K)

D2 coefficient for thermal-conductivity function, W•kg/(m'* -K)

emf electromotive force, mV

exp exponential function

Gt total water vapor transfer resistance, Pa-m^-s/kg

he convective conductance of vertical airspace W/(m^-K)

hj inside air film coefficient, W/(m^-K)

ho outside air film coefficient, W/(m^-K)

h^ water vapor permeance of vertical airspace kg/(s'm^-Pa)

j index

J number of layers of building materials

X
NOMENCLATURE (continued)

In natural logarithm function

L thickness of specimen, m

Le Lewis number

m slope of best-fit of water vapor resistance data, s-m -Pa/kg

MC moisture content, percent

n index

N number of points

p^ atm atmospheric pressure, Pa

saturation water vapor pressure. Pa

PA gv water vapor pressure inside glass vessel. Pa

Pv water vapor pressure inside glass vial. Pa

q heat flux, W/m^

Q power, W

thermal resistance of layer j

, m^ -K/W

Rhft measured thermal resistance of wall, m^-K/W

R-j- overall calculated thermal resistance of wall, m^-K/W

RH relative humidity, percent

RMS root-mean-square

RSD residual standard deviation of fit, W/m^

s standard deviation

t elapsed time, s

xi
NOMENCLATURE (continued)

Tn, mean temperature between surface and surrounding radiant environment, K

Tj measured inside air temperature, °C

To measured outside air temperature, °C

U calculated themial transmittance of wall, W/(m^-K)

Vair velocity of air film, m/s

V output voltage of heat flux transducer, mV

w water vapor transfer rate, kg/s

6rms root-mean-square difference, percent moisture content

An difference between measured and predicted moisture content, percent moisture content

A(/) relative humidity difference, percent

AT temperature difference between hot and cold plates, °C

ATair temperature difference across air film, °C

ATj temperature difference across wall specimen at time t, K

e surface emittance

X (apparent) thermal conductivity, W/(m-K)

fi permeability, kg/(s-m -Pa)

</) relative humidity

p density, kg/m^

u Stefan-Boltzmann constant, W/(m^-K'*)

L summation operator /

xii
INTRODUCTION

Guidelines are needed for controlling moisture in building envelopes. Current moisture control

practices are based upon the geographic location of the building, the construction materials used,

field study results, and local experience. The existing guidelines and practices are often debated

by experts in the building community and, for the most part, unsupported by analysis. For

example, most practitioners recommend that an interior vapor retarder be installed in building

envelopes. In a cold climate, an interior vapor retarder impedes the ingress of moisture from

the indoor environment, thereby minimizing potentially damaging moisture accumulation in the

sheathing and siding of walls. However, this same practice is counterproductive in a wall of an

air conditioned house located in a hot and humid climate. In this situation, moisture from the

outdoor environment permeates through the wall construction and accumulates at the interior

vapor retarder. Failure to properly control moisture within a building envelope may lead to increased energy usage, degradation of building materials, and the growth of biological agents

such as fungal spores (Bales and Rose 1991).

Field studies have provided valuable information for documenting specific moisture problems

for a given type of building construction in a specific climate. Field studies have also provided an understanding of the underlying physics involved in the transfer of heat and moismre through

building components. However, despite the valuable information that field studies provide, it

is difficult to generalize the results of a given field study to different building materials,

climates, and indoor environmental conditions. Moreover, it is impractical to implement the

number of field studies which would be required to address all possible combinations of

construction types and climatic conditions.

The National Institute of Standards and Technology (NIST) has developed a personal computer

program, MOIST (Burch and Thomas 1993) which provides the means for developing

appropriate moisture control guidelines. MOIST predicts the transient heat and moisture transfer

in building envelopes having multi-layer construction under nonisothermal conditions. MOIST

solves the one-dimensional conservation of energy and conservation of mass equations using the

finite-difference method. MOIST allows the user to vary building materials, their relative

placement within the building envelope, and the geographic location of the building. It includes

transfer of moisture in the diffusion and the capillary flow regimes. The vapor-transfer

resistance of paint layers and vapor retarders is readily included. Outdoor weather conditions

are available for 51 cities (Crow 1981). The program calculates and plots the average moisture

content of the layers of construction versus time of year for a given set of indoor and outdoor

conditions.

As is the case with any model, MOIST requires verification by comparison to laboratory

experiments as well as field studies. This report describes a comprehensive laboratory study

conducted by NIST to verify the accuracy of MOIST.

1
I

I EXPERIMENT

Overview

Twelve wall specimens were built and tested collectively in the NIST calibrated hot box. The

calibrated hot box was operated continuously for 104 days providing nominal conditions of

21 °C and 50 percent relative humidity at the interior surfaces of the wall specimens and a range j of ambient temperatures and relative humidities at the exterior surfaces. For the first 42 days,

the interior and exterior surfaces were preconditioned at roughly the same conditions of 21 °C

and 50 percent relative humidity. After preconditioning, the exterior temperature was decreased

suddenly to 7.2 °C for one day. For the next 6 days, a series of diurnal sinewaves were imposed on the exterior surfaces in which the amplitude of the air temperature varied from 1 .

to 15.6 °C. The exterior temperature was then maintained at a nominal air temperature of

7.2 °C for 34 days. For seven days, the exterior surfaces were exposed again to a second series

of diurnal sinewaves having nearly the same boundary conditions as the first series. Finally, the

exterior temperature was elevated to a nominal temperature of 32 °C for the last 14 days.

During the experiment, the moisture content and temperature of selected exterior materials, the

heat flux through each wall specimen, and the ambient air temperatures and relative humidities were measured. The measured moismre contents were subsequently compared to values

predicted by MOIST simulations of the experiment. These simulations used the experimental

boundary conditions and independently measured material properties, such as the water vapor

sorption isotherm and permeance, as input data. The measured heat flux through each wall

specimen was compared to the values predicted by MOIST simulations and also values calculated

from procedures in the ASHRAE Handbook of Fundamentals (ASHRAE 1993). The calculated

values of heat flux were determined using the measured thermal conductivity for the materials

within the wall specimens.

Wall Specimens

Twelve wall specimens were constructed within the 300-mm thick frame of the NIST calibrated

hot box. Figure 1. Each specimen had overall dimensions of 1.0 by 1.1 m and was designed

with a centrally located meter section, 305 mm in diameter. In designing each wall specimen,

finite-element calculations were conducted to insure that the heat transfer through each specimen

was one-dimensional. To minimize lateral transport of moisture between the meter section and

surrounding materials, the meter section was circumscribed by a thin 0.03-mm sleeve of

polycarbonate-plastic film as shown in Figure 2 . The specimens consisted of either three or four

layers of building materials typical of residential wood-frame construction, namely: gypsum

wallboard; cavity insulation of glass fiber or loose-fill cellulose; sheathing of either fiberboard,

fir plywood, or foil-faced polyisocyanurate; and siding of sugar pine or vinyl. The building

materials were obtained locally and are described in Appendix A.

2
X

3
METER SECTION CONSTRUCTION DETAILS

Plastic

sleeve Siding

Cavity

insulation

Interior

sheathing

3 2 1

3-layer wall construction

Plastic

sleeve

2'*"9 chf=1hPn. insula^on sheathing

Interior

sheathing

4 3 2 1

4-layer wall construction

Figure 2
Construction details and a material list for each wall specimen are illustrated in Figure 3 . The

first eight wall specimens were designed specifically for verification of MOIST. These

specimens utilized a design strategy that varied a single parameter of construction from

specimen-to-specimen. For example, specimen 1 was constructed with three layers of materials:

gypsum wallboard, glass-fiber insulation, and sugar pine siding. Specimens 2 through 8 varied one item of construction; 2, added a vapor retarder; 3, interior latex paint and exterior oil paint;

4, interior and exterior latex paint; 5, fiberboard sheathing; 6, plywood sheathing; 7, cavity

airspace; and, 8, cellulose insulation. This strategy examined the relative effects of each of

these parameters on the movement of moisture through the specimens.

The four other specimens, 9 to 12, were more representative of current building practices and were designed to explore the effectiveness of a vapor retarder on moisture movement. Again,

a single parameter of construction was varied. Specimens 10 and 1 1 were the same construction

as 9, except both were constructed purposely with a defect. The defect consisted of a 1 1 .5-mmdiameter hole in specimen 10 and a 7.9-mm-diameter hole in specimen 11. The diameter of

each hole was determined from design data compiled on effective leakage areas for electric

outlets in the ASHRAE Handbook of Fundamentals (ASHRAE 1993). Note that specimen 12 was the same as specimen 9 except the vapor retarder was excluded. A summary of the wall

specimen constructions is presented in Table 1

5
WALL SPECIMEN CONSTRUCTION DETAILS

Gypsum board

Glass-fiber insulation Sugar pine

Gypsum board

Glass-fiber insulation w/asphalt -kraft paper Sugar pine

Latex paint

Gypsum board

Glass-fiber insulation Sugar pine

Oil paint

Latex paint

Gypsum board

Glass-fiber insulation Sugar pine Latex paint

Gypsum board

Glass-fiber insulation Fiberboard sheathing

Sugar pine

Gypsum board

Glass-fiber insulation Plywood sheathing

Sugar pine

Gypsum board

Air - space Sugar pine

8. Gypsum board

Cellulose insulation Sugar pine

1 1 .5-mm

hole —

7.9-mm

hole —

9. Latex paint

Gypsum board

Glass-fiber insulation w/ asphalt - kraft paper

Foil-faced polyisocyanurate

Vinyl

10. Latex paint

Gypsum board

Glass-fiber insulation w/ asphalt - kraft paper

Foil-faced polyisocyanurate

Vinyl

11. Latex paint

Gypsum board

Glass-fiber insulation w/ asphalt - kraft paper

Foil-faced polyisocyanurate

Vinyl

12. Latex paint

Gypsum board

Glass-fiber insulation Foil-faced polyisocyanurate

Vinyl

Figure 3

6
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7
Calibrated Hot Box

A schematic of NIST's calibrated hot box is given in Figure 4. The NIST calibrated hot box

complies with the American Society for Testing and Materials Test Method C 976 (ASTM

1994). The apparatus consists of three principal components: a metering chamber, a climatic

chamber, and a specimen support frame. These components were designed to provide controlled

conditions of temperature, air flow, and radiation on each side of the wall specimen and to measure the resulting heat flow through the wall specimen. In this study, the calibrated hot box

was operated in a manner which provided controlled temperature and relative humidity

conditions at the interior and exterior surfaces of the wall specimens. A detailed description of

the facility is available in the literature (Achenbach, P.R. 1979, Zarr et al. 1987) and a brief

review of the components is given below.

The metering chamber consists of a five-sided, highly-insulated, enclosure. Its exterior walls

are comprised of rigid polyurethane insulation, 381 mm thick, providing a thermal resistance

of R-16 m^-K/W. Surrounding the exterior surface of the rigid polyurethane insulation is a chilled-water guard maintained at the same temperature as the air in the metering chamber. The

chamber walls are finished with a thin (1.7 mm) sheet of reinforced fiber-glass plastic. Due to the large thermal resistance of the walls and the small temperature gradient, the rate of heat

transfer through the chamber walls is quite small i.e., less than 0.5 W (Zarr et al. 1987).

Air within the metering chamber was circulated at a constant rate by a propeller-type fan and

conditioned by an electric heater and a cooling coil. The cooling coil was operated at a constant

chilled-water flow rate and was operated at a temperature above 10 °C. A platinum-resistance

thermometer measured the dry-bulb temperature within the metering chamber. The relative

humidity of the air was controlled by humidifying the supply air with a vaporizer and measured

using a thin-film capacitance humidity sensor. Conditioned air was delivered to the top of the

specimen through air diffusers designed to deliver a uniform distribution of air across the

specimen. The baffle wall was coated with flat-black paint to provide a total hemispherical

emittance greater than 0.8.

The climatic chamber consists of a five-sided enclosure, the same size and configuration as the

metering chamber, except its walls are constructed without an external chilled-water guard. The

thickness of the rigid polyurethane insulation is 457 mm, providing a thermal resistance of

R — 19 m^-K/W. The chamber walls are also finished with a thin sheet of reinforced fiber-glass

plastic.

Conditioned air for the climatic chamber was provided by one of two external systems as shown

in Figure 4. For dry conditions, air was conditioned by an electric heater and a refrigeration

system. A portion of the air was diverted to a two-stage rotating-drum desiccant dryer that

removed water vapor from the air. The dryer maintained a low dew point, preventing frost from

diminishing the capacity of the refrigeration coil. For humid conditions, the refrigeration system

and desiccant dryer were not used and air was instead conditioned by a heated vaporizer and a

chilled-water cooling coil. The dry-bulb temperature and relative humidity within the climatic

8
9
chamber were measured using a platinum-resistance thermometer and thin-film capacitance

humidity sensor, respectively. The humidity level within the climatic chamber was controlled

manually. Conditioned air was circulated to the climatic chamber by a vane-axial fan and

delivered to the bottom of the specimen through air diffusers. The baffle wall was coated with

flat-black paint to provide a total hemispherical emittance greater than 0.8.

The 300-mm-wide specimen frame can support wall specimens having a thickness of 250 mm

and an overall area of 3.0 by 4.6 m. The frame is comprised of 457-mm-thick rigid

polyurethane insulation finished with a thin 1.7-mm sheet of plastic reinforced fiber-glass plastic

to provide a vapor barrier. The design was engineered to minimize the heat transfer through

the specimen frame and provide structural support for the specimen.

Data Acquisition

The data-acquisition system consists of a portable computer interfaced to a data acquisition

system. The computer controls the data acquisition system, converts the sensor signals into

engineering quantities, corrects the measurements using calibration data, averages the data over

appropriate time intervals, displays the current measurements on a video monitor, and records

the data on a disk.

Boundary Conditions

During the experiment, the metering chamber maintained a steady indoor condition of 21.2 ±

0.1 °C and 50 + 3 percent relative humidity at the interior surfaces of the wall specimens. The

airspeed moving past the interior surfaces was maintained at 0.4 m/s in a downward direction.

During this same period, the climatic chamber provided the ambient conditions shown in

Figure 5 at the exterior surfaces of the wall specimens. At the exterior surfaces, the air speed

was maintained at 1.0 m/s in an upward direction. The sequence of ambient conditions in the

clunatic chamber is summarized in Table 2.

Table 2

Climatic Chamber Conditions

Condition Days

Pre-Conditioning 42

Winter - Steady 1

Winter - Diurnal Sinewave 6

Winter - Steady 34

Winter - Diurnal Sinewave 7

Summer - Steady 14

10
CLIMATIC CHAMBER BOUNDARY CONDITIONS

Figure 5

11
The wall specimens were initially pre-conditioned in order to establish initial moisture contents

within the construction materials. The test period was partitioned into four winter periods and

one summer period. At the end of the pre-conditioning period, the ambient temperamre within

the climatic chamber was reduced quickly to 7.2 °C for one day in preparation for the first series of diurnal sinewaves. The purpose of the first series of diurnal sinewaves was to investigate the time-dependent transfer of heat and moisture when the wall specimens were

comparatively dry. During the second steady winter period, moisture migrated through the wall

specimens and accumulated in the hygroscopic sheathing and siding materials. The purpose of

the second series of diurnal sinewaves was to investigate the time-dependent transfer of heat and

moisture when the wall specimens were comparatively moist. During the final summer period,

the accumulated moisture migrated towards the interior surface thereby drying the exterior layers

of construction.

Measurements

Each wall specimen was instrumented with sensors for the measurement of temperature, heat

flux and moisture content. Sensor locations are shown in Figure 6 for a typical wall

construction having a layer of exterior sheathing.

Temperature

Surface and air temperatures were measured with copper-constantan (type-T), bead

thermocouples. The thermocouples were fabricated from 30 gauge duplex wire (0.25 mm

diameter). The thermocouple wire was calibrated by NIST's Thermometry Group (Semerjian

1991) in accordance with the International Temperamre Scale of 1990 (ITS-90).

Heat flux

The rate of heat flux through the meter section of each wall specimen was measured with a

single heat-flux transducer. As shown in Figure 6, the transducer was placed at the geometric

center of the interior surface of the gypsum wallboard for specimens 1 through 9 and 12. For

specimens 10 and 11, however, the transducer was located at the same height but 30 mm offcenter from the air-leakage holes described above. The heat flux transducers were attached to the gypsum wallboard with a silicone-rubber adhesive. The transducers on wall specimens 3,

4, and 9 to 12 were painted with white latex paint.

The heat flux transducers consisted of a small disk of silicone rubber, 23 mm in diameter and

3 mm thick, containing a series of thermocouple junctions (e.g., thermopile) embedded on

opposite faces of the sensor. The junctions were wound in a helical spiral within a sensing

region about 20 mm in diameter. The thermopile generated an emf directly proportional to the

temperature difference across the sensing region, which was, for practical purposes, proportional

to the heat flux through the transducer.

12
13
The heat flux transducers were cahbrated by placing them between an assembly of thermal

insulation and subjecting them to a steady heat flux in NIST's 1-m guarded hot plate (Rennex

1983). The assembly consisted of a 25-mm thick glass-fiber board, a layer of 3-mm thick

silicone rubber, and a second 25-mm thick glass-fiber board. Twelve circular openings were

cut in the layer of silicone rubber to accommodate the transducers. In order to simulate test conditions within the calibrated hot box, the transducers were initially calibrated at a mean

temperature of 21 °C and temperature differences of 5, 10, 20, and 30 °C, providing heat fluxes

from approximately 3 W/m^ to 18 W/m^ The test conditions were repeated with the orientation

of the transducers inverted to study the effect of heat reversal through the transducer.

After obtaining a steady-state heat flux, data were collected at 5 minute intervals over a one-hour

period. The data were fit to an equation of the form:

q = Ao + V .

A typical curve-fit is shown in Figure 7. The functional form of eq (1) was selected to account

for the small (artificial) offset when the heat flux was zero. A summary of the regression curvefits for the heat flux transducers and the residual standard deviation for the fit is provided in

Table 3.

14
15
Table 3

Heat Flux Transducer Regression Coefficients

Transducer

Ao

(W/m^)

A,

(W/m'-mV)

Residual Standard

Deviation of Fit

(W/m')

1 0 114 1 1 967 0 021

0yj . IfiQ LKJZ/ 12 41

X , *T X X 0 042

12X ^ . X1 54 0 034

4 0 146 12 3S9 0 031

5 0 102 12X ^ . 147 X ~ / 0 030

6 0 175 12 239 0 048

7 0.102 11.244 0.024

8 0.093 10.983 0.026

9 0.062 11.226 0.045

10 0.195 10.805 0.068

11 0.156 10.502 0.044

12 0.160 11.547 0.039

Moisture Content

The moisture content of the wood-based materials was measured using the electrical-resistance

method (Duff 1968). This method is based on the principle that, below fiber-saturation, there

exists a unique relationship between moisture content and electrical resistance for a particular

species of wood. For this experiment, a commercial moisture meter based on this principle and

having a display resolution of 0. 1 percent moisture content was adapted in the following manner. The two-pin metal electrodes provided with the moisture meter were replaced with a pair of

electrodes comprised of electrically conductive epoxy. The epoxy was applied to the surface of

the wood-based materials in strips normal to the grain as illustrated in Figure 8a. The sensors were fabricated by mixing together equal parts of a two-component silver epoxy. Using a template, the mixture was applied to the surface of the material as two strips, each

approximately 4 mm wide with a centerline to centerline spacing of 23 mm. Before curing,

bare-wire leads were placed in the mixture (one lead per strip). The mixture was allowed to cure at room temperature for a minimum of 24 hours.

16
CONSTRUCTION AND LOCATION OF

MOISTURE CONTENT SENSORS

Electrically-

(a) Moisture content sensor normal (b) General configuration

to direction of wood grain

(c) Wall 1 configuration (d) Moisture content sensor

Interior surface of sugar pine on sugar pine substrate

Figure 8

17
Moisture content sensors were applied to the interior and exterior surfaces of the sugar pine and

to the interior surfaces of the plywood and fiberboard. With the exception of the interior surface

of the sugar pine sheathing of wall specimen 1 , the sensors were located at the geometric center

of each wall specimen as illustrated in Figures 6 and 8b. A special array of five sensors was

applied to the interior surface of the sugar pine of wall specimen 1 to investigate the lateral

distribution of moisture (fig. 8c). For wall specimens 9 to 12, a substrate of sugar pine with

epoxy electrodes was attached to the foil-faced polyisocyanurate sheathing with a silicone rubber

(fig. 8d).

At the completion of the calibrated hot box experiment, all 24 of the moismre content sensors were calibrated collectively in a small environmental chamber. Since the sensors had been

attached permanently to the wood-based materials, a 100 by 100 mm section of material (with

the attached sensor) was cut from the wall specimen and placed in a two-pressure humidity

generator (Hasegawa and Little 1977). The sensors were exposed to fixed relative humidities

of 50, 65, 80 and 92 percent at 4.4 °C, and 50, 65, 80, 90 and 95 percent at 32.2 °C.

Readings were taken from each sensor at daily intervals using the commercial moisture meter.

The meter readings for one sensor attached to sugar pine are plotted versus elapsed time in

Figure 9. Note that at 65 percent relative humidity and 4.4 °C, it required nearly 50 days for

the sugar pine substrate to obtain moisture equilibrium.

The calibration for each sensor was determined by comparing the equilibrium moisture-meter

readings to the actual moisture content of the wood-based substrate material. The calibration

data for one sensor attached to sugar pine is given in Figure 10. Here, the actual moisture

content of the wood-based material was determined from a previously established relationship

between moisture content and relative humidity, known as the sorption isotherm.^ Linear

regression curves were fit to the data at 4.4 °C and 32.2 °C for each sensor. The calibration curves were subsequently used to correct the data collected from wall specimens during the

calibrated hot box experiment. The moisture content at temperatures between 4.4 °C and

32.2 °C was determined by linear interpolation.

The analysis of the calibration data revealed considerable variability between the sensors attached

to sugar pine. An example is given in Figure 11 for data from 23 moisture content sensors conditioned at 4.4 °C. Note that the variability between sensors increased at higher moisture

contents. The data point for the sensor in contact with cellulose was excluded from the graph

since the presence of fire retardants in the cellulose caused the sensor to give erroneous readings

(Laurenzi 1994). The variability in the data for the 23 sensors was further examined by plotting

the meter readings at 32.2 °C and 95 percent relative humidity versus the sensor number as

illustrated in Figure 12. The middle line corresponds to the mean of the data and the dashed

lines are one standard deviation from the mean. The standard deviations for the sugar pine

^During the calibration tests, the sensors and substrates were exposed to a sequence of increasing

relative humidity conditions, so the "adsorption" isotherm, as opposed to the "desorption"

isotherm, was used.

18
SUGAR PINE MOISTURE CONTENT TIME RESPONSE

10

O

Q

<

LU

CC

DC

LJJ ILU

8

65% RH, 4.4°C

6 1

I

I I I I 0 10 20 30 40 50 60

ELAPSED TIME (Days)

Figure 9

TYPICAL MOISTURE CONTENT SENSOR

CALIBRATION CURVES FOR SUGAR PINE

< 0 I \ I \ I 0 10 20 30 40

METER READING (% MC)

Figure 10

19
VARIABILITY IN MOISTURE CONTENT SENSORS

Sugar pine at 4.4°C

5 10 15 20

MOISTURE CONTENT BY MASS (%)

Figure 11

25

SENSOR - TO - SENSOR VARIABILITY OF

SUGAR PINE MOISTURE CONTENT SENSORS

34

32

30

1—I—

1—

28

I 261-

n I I I I I I I 1 r 95% RH, 32.2° C

Standard deviation = 2.62% MC

Mean + s

iVlean

24 -

22 - Mean

20 I \ \ \ \ \ \ L J L J \ \ \ I L

3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

SENSOR NUMBER

Figure 12

20
moisture content sensors at the other calibration conditions are given in Table 4. The results

indicate that significant errors, particularly at high relative humidities, would result if a single

calibration were used to represent all the sugar pine substrates.

Table 4

Standard Deviation of Sugar Pine Moisture Content Sensors (%MC)

Relative Humidity

(%)

Ambient Temperature

4.4 °C 32.2 °C

50 0.43 0.39

65 0.48 0.66

80 1.13 0.85

90 1.80

92 2.21

95 2.62

Relative Humidity

The relative humidities of the metering and climatic chambers were measured using commercial

thin-film capacitance humidity sensors. The sensors were calibrated using a chilled-mirror dew

point hygrometer and a precision dry-bulb thermometer. The relative-humidity sensor for the

metering chamber was calibrated at 21 °C from 30 to 70 percent relative humidity whereas, the

climatic chamber sensor was calibrated from 20 to 80 percent relative humidity at various

temperatures. Figure 13.

21
RELATIVE HUMIDITY SENSOR CALIBRATION CURVES

Metering Chamber

100

>

I

60

X

^ 40

P

Ly 20

0

1 1 T=2rc

i 1

1

1

= 2.64 + 19.36 V

1 1 0

100

80

>

Q 60

LU 40

>

m 20

0

0

12 3 4

OUTPUT VOLTAGE (Volts)

Climatic Chamber

12 3 4

OUTPUT VOLTAGE (Volts)

Figure 13

- OJ =

1 1 0°C1 1

AT = 7.6°C

oT = 15.7°C

- vT = 32.5 °C

1

1

1.87 + 19.22 V

1

1

22
SPECIMEN MATERIALS PROPERTIES

MOIST requires that moisture and heat transfer properties for each material layer within a wall

specimen be provided as input data. Currently, the program has a database of "representative"

properties for 28 building materials commonly used in residential construction. In order to minimize the uncertainties associated with material variability, the following properties - sorption

isotherm, permeability, and thermal conductivity - were measured for each of the materials used

in the wall specimens. The experimental procedures and resulting data for these properties are summarized in this section.

Sorption Isotherms

The sorption isotherms were determined by placing eight small specimens of each hygroscopic

material in vessels above saturated salt-in-water solutions. For a given temperature, each

saturated salt-in-water solution provided a fixed relative humidity (Greenspan 1977). In this case, the vessels were maintained at a temperature of 24 ± 0.2 °C until the specimens reached

steady-state equilibrium. The equilibrium moisture content was plotted versus relative humidity

to give the sorption isotherm. Separate sorption isotherm data were obtained for specimens

initially dry (adsorption isotherm) and for specimens initially saturated (desorption isotherm).

A detailed description of this measurement method is given elsewhere (Richards et al. 1992).

The mean of the absorption and desorption isotherm measurements was fit to an equation of the

form:

(2)

(1+B,(J))(1-B,(1))

The coefficients Bj, Bj, and B3 were determined by regression analysis and are sunmiarized in

Table 5 . The sorption isotherm data for sugar pine and corresponding curve-fit are illustrated

in Figure 14.

23
SUGAR PINE SORPTION MEASUREMENTS

30

& 25

ILU 20

O

15

UJ

§ 10

CO

o

1 1 1 1 1 1 • Adsorption measurements

Desorption measurements

1 1 1

0.192(1)

Y - (1+2.05 (j)) (1-0.765(1))

(Y,(|) expressecd as fraction)

\

^--^^ 1 1 1 1 1 1 1 1 20 40 60 80

RELATIVE HUMIDITY (%)

100

Figure 14

24
Table 5

Sorption Isotherm Regression Coefficients

Materials Bi B2 B3

Cellulo'se loose fill 0.274 5 95 0 9995

Fiberboard sheathinff 1.14 50.6 0 923

Polyisocyanurate foam 0.0528 2.51 0.773

Glass-fiber insulation 0.00170 1 X 10"^ 0.963

Gypsum wallboard 0.00336 1 X 10"^ 0.901

Kraft paper with asphalt mastic 51.9 2538 0.902

Plywood sheathing (fir) 0.488 8.93 0.804

Sugar pine 0.192 2.05 0.765

Permeability Measurements

The water vapor permeability of the rigid hygroscopic materials was determined using

permeability cups placed in controlled environments. Five circular specimens, 140 mm in

diameter, of each material were sealed at the top of open mouth glass dishes. The dishes were

subsequently placed and sealed inside glass vessels maintained at a fixed temperature. Saturated

salt-in-water solutions were used inside the glass dish and surrounding glass vessels to generate

a relative humidity difference of approximately 10 percent across each specimen. By using

different salt solutions, the mean relative humidity across the specimen ranged from "dry" to a nearly saturated state. A detailed description of the permeability measurement method is given

elsewhere (Burch et al. 1992).

Permeability data were plotted versus the mean relative humidity across the specimen and fit to an equation of the form:

= exp(Cj + CjCl) + Cgtt)^) . (3)

The coefficients Ci, Cj, and C3 were determined by regression analysis and are summarized in

Table 6.

25
Table 6

Permeability Regression Coefficients

Materials C3

Cellulose loose filP -22.425 0.0 0.0

Fiberboard sheathing -24.054 -.1004 0.0

Polyisocyanurate foam -26.686 0.5224 0.0

Glass-fiber insulation^ -22.425 0.0 0.0

Gypsum wallboard -23.475 0.0 0.0

Kraft paper with asphalt mastic -32.239 -1.168 3.058

Plywood sheathing (fir) -25.534' -0.9178' 0.8858'

Sugar pine -28.677 -0.9198 4.576

^Assumed to be equal to stagnant air layer,

^These coefficients were fit to the equation: [i = exp [Cj + C2(A (1 - C,(j>)]

The permeability of one material, sugar pine, is illustrated in Figure 15. As noted in Figure 15

and previous data (Burch et al. 1992), measurements conducted at 7 °C and 24 °C revealed that,

for the given range, temperamre has only a small effect on permeability.

Special water vapor transmission measurements (Appendix B) were conducted to determine the

permeance of the paint layers applied to interior and exterior surfaces of the wall specimens.

The Lewis relationship between heat and mass transfer (Threlkeld 1970) was used to calculate

the vapor permeance of the cavity airspace for wall specimen 7. The permeance of the paint

layers and the cavity airspace are given in Table 7.

Table 7

Permeance of Paint Layers and Convective Airspace

Layers

Permeance

(lO^kg/sm'Pa)

Interior latex paint 977

Exterior latex paint 190

Exterior oil-base paint 80.4

Cavity airspace 13,300

26
SUGAR PINE PERMEABILITY MEASUREMENTS

Figure 15

27
Thermal Conductivity Measurements

The thermal conductivities of the wall specimens were determined using NIST's one-meter

guarded hot plate apparatus, ASTM Test Method C 177 (ASTM 1994). The apparatus is designed to determine the steady-state thermal transmission properties of flat specimens of

building materials. A schematic diagram of the operating principle for the apparatus is illustrated in Figure 16. In practice, the apparatus produces a one-dimensional heat flow normal

to the meter area of the guarded hot plate. Under steady-state conditions, the thermal

conductivity of the specimen was determined from Fourier's equation for one-dimensional heat

flow, namely:

Q = XA^ . (4)

L

Specimens of cellulose and rigid materials were prepared from the surplus materials used to construct the wall specimens. The cellulose specimen was prepared by first lofting and then

hand-pouring the insulation into a fine wire-mesh basket. The wire mesh was subsequently

neglected in the thermal conductivity measurement. The amount of cellulose was determined

to provide the same nominal density as that installed in the wall specimen. The specimens of

glass-fiber thermal insulation were taken carefully from each wall specimen at the conclusion

of the calibrated hot box experiment and measured individually. The specimens were

preconditioned at 21 ± 2 °C and 40 to 60 percent relative humidity for about 2 months prior

to the guarded hot plate tests.

The thermal conductivity of each specimen was measured at nearly the same mean temperamre

that the material experienced during the steady-state winter exposure in the calibrated hot box

experiment. Consequently, the thermal conductivity of gypsum wallboard was determined at a mean temperamre of 20.5 °C; the thermal insulations in the wall cavity, at 15 °C; the exterior

sheathing, at 8.5 °C; and the exterior siding, at 7.5 °C. The specimens of cellulose and glassfiber thermal insulation were tested at the same thickness as the wall cavity, 81.4 mm. A

temperature difference of 20 °C was selected for these materials and a value of 10 °C for the

other specimens. The densities of the cellulose and glass-fiber specimens were determined for

a 406-mm-diameter section corresponding to the meter area of the guarded hot plate. The

results of the guarded hot plate tests are summarized in Table 8.

28
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The thermal conductivities of the glass-fiber thermal insulation were plotted as a function of

density as illustrated in Figure 17. Each point is individually identified by the specimen number

and the type of symbol (square or diamond) indicated the presence of a vapor retarder. A

regression curve of the form (Boulant et al. 1983)

A = Dq + D^p + — (5)

P

was fit to the data and is shown as a solid line in Figure 17. Values of Do, Dj, and were

determined to be 0.0121, 9. 11 x 10""^, and 0.219, respectively. This equation was subsequently

used to compute values of thermal conductivity of the glass-fiber insulation at other densities.

After the guarded hot plate tests, core samples of the glass-fiber insulation were taken to determine the local in-situ density corresponding to the location of the heat flux transducer.

Cylindrical core samples, having the same diameter as the heat flux transducers, were taken in- line with the heat flux transducers. Using eq (5), thermal conductivity values for the glass-fiber

insulation were determined for the wall specimens and are summarized in Table 9. It should

be noted that the densities obtained for the core samples for wall specimens 4 and 6 were below

the range (8-11 kg/m-') of the density/thermal-conductivity correlation.

31
o

cr

LU

Ch • ^

/ M) AllAllOnaNOO iviaihbhi

32
Table 9

Local Thermal Conductivities for

Cylindrical Core Samples of

Glass-Fiber Batt Insulation

Wall Specimen Mr Density

(kg/m^)

Thermal

Conductivity

(W/mK)

1 9.09 0.0445

2 9.17 0.0443

3 10.4 0.0426

4 5.98 0.0542

5 8.78 0.0450

6 6.16 0.0533

9 7.00 0.0468

10^ 10.7 0.0421

IV 10.9 0.0417

12 9.51 0.0438

' The heat flux transducer for this wall specimen was

installed off center and the in-situ density could not be

ascertained. The thermal conductivity was determined

for a bulk density corresponding to the 305 -mmdiameter meter section of the wall specimen.

33
COMPARISON OF EXPERIMENTAL RESULTS TO MOIST

At the completion of the calibrated hot box experiment, the measured moisture contents of

selected material layers and the heat fluxes through the specimens were compared to predicted

values from MOIST simulations. For the simulations, the experimental air temperature and

relative humidity in the metering and climatic chambers were used as input boundary conditions.

The material properties of the wall specimens were determined from measurements described

in the previous section and input to the program. The thermal insulation in the wall cavity was

modeled as a nonstorage layer. That is, the storage of heat and moisture within the insulation

was neglected and constant values of permeance and thermal resistance for the insulation were

specified in the program. The results of the comparisons are summarized in this section.

Moisture Content Comparisons

In order to make meaningful comparisons between the experimental data and MOIST, it was

vital to assess whether the moisture transfer through the circular meter section was one- dimensional. To investigate the one-dimensional transfer of moismre, an array of five moisture

sensors was installed at the inside surface of the sugar pine (fig. 8c). The moisture contents of

these five sensors are plotted versus time in Figure 18. The variability of the moisture content

measurements ranged within ±1.6 percent moisture content. Therefore, the results do not

indicate significant departure from one-dimensional moisture transfer.

Base Case - Wall Specimen 1

The moisture content at the inside surface of the sugar pine for wall specimen 1 is given in

Figure 19. The measured and predicted values are indicated by the solid and dashed lines,

respectively. At time zero, the exterior air temperature decreased from 21 °C to 7.2 °C (fig. 5)

and water vapor from the interior air diffused into the wall construction accumulating in the

sugar pine. The moisture content increased to 24 percent after 48 days. This peak value of

moisture content was only 3 percent below the fiber saturation of 27 percent shown in Figure 14.

After 48 days, the air temperature at the exterior surface of the wall was increased to 32 °C

causing water vapor to migrate towards the inside environment. Consequently, the moisture

content at the inside wood surface decreased rapidly. The moisture content fluctuations (fig. 18

and 19) were caused by the diurnal sinewaves in the exterior ambient temperature.

34
DISTRIBUTION OF MOISTURE CONTENT ON

INTERIOR SURFACE OF SUGAR PINE

0 10 20 30 40 50 60

ELAPSED TIME (Days)

Figure 18

MEASURED AND PREDICTED MOISTURE CONTENT

WALL SPECIMEN 1

0 10 20 30 40 50 60

ELAPSED TIME (Days)

Figure 19

35
The predicted values of the moisture content (fig. 19) are for a 3.2-mm-thick layer of the inside

surface of sugar pine. The average difference between the measured and predicted moisture

content was expressed as a root-mean-square difference, or: E (Kf (6)

n = l N

As noted in Figure 19, the 6rms difference was 1.1 percent moisture content.

It was not possible to compare the measured and predicted moisture content at the outside

surface of the sugar pine because the moisture content decreased below the minimum detectable

limit (i.e., 6 percent) of the moisture meter. This drop in moisture content occurred because

the outside wood surface was exposed to ambient air having a low relative humidity of 3 to 1

percent. The low relative humidity in the climatic chamber was necessary in order to minimize

frost accumulation on the chamber's refrigeration coil. The authors acknowledge that such a low

relative humidity is atypical of prevailing outdoor winter relative humidities.

Effect of Vapor Retarder - Wall Specimen 2

A comparison of the measured and predicted moisture contents at the inside surface of the sugar

pine for wall specimen 2 is given in Figure 20. The 6rms is 0.9 percent moisture content.

Comparing Figures 19 and 20 indicates that the presence of the kraft-paper vapor retarder

considerably reduced the water vapor diffusion into the wall construction, thereby significantly

reducing the moisture content at the inside wood surface. In addition, the presence of the kraftpaper vapor retarder reduced the flow of moisture during the drying period, causing the moisture

content at the inside wood surface to decrease at a slower rate.

Effect of Paint Coatings - Wall Specimens 3 and 4

The results for wall specimen 3 with interior latex paint and exterior oil-base paint are given in

Figure 21. Here the 6rms was 0.5 percent moisture content. The presence of the interior latex

paint reduced the passage of water vapor into the wall construction, lowering the peak moisture

content compared to wall specimen 1 (fig. 19).

Results for wall specimen 4 with interior and exterior latex paint are given in Figure 22. This

wall is identical to wall specimen 3, except that exterior latex paint is used instead of exterior

oil-base paint. Here the 6rms is 1.1 percent moisture content. Comparing Figures 21 and 22,

very little difference in moisture content occurs as a result of using exterior latex paint instead

of exterior oil-base paint. Moisture accumulation within the wood layer is caused by a difference between the inflow and outflow rates to the wood layer. A large difference in

temperature and water vapor pressure across the gypsum wall board and the insulation layer causes a large inflow of moisture from the metering chamber to the wood layer. On the other

'RMS

36
MEASURED AND PREDICTED MOISTURE CONTENT

WALL SPECIMEN 2

30

111 Z 20

O

LU5 15

coO

10 -

8rms = 0-9% MC

Wall

specimen

2

Predicted

Measured

0 10 20 30 40 50 60 70

ELAPSED TIME (Days)

Figure 20

MEASURED AND PREDICTED MOISTURE CONTENT

WALL SPECIMEN 3

30

^RMS = 0-5% MC

^ 25

0 10 20 30 40 50 60 70

ELAPSED TIME (Days)

Figure 21

37
MEASURED AND PREDICTED MOISTURE CONTENT

WALL SPECIMEN 4

30

25

>RMS = 1.1% MC Latex

paint

Measured

Latex

paint

Wall

'I'.iir.iN specimen

4

Predicted

0 10 20 30 40 50

ELAPSED TIME (Days)

60 70

Figure 22
hand, a rather small difference in temperature and water vapor pressure exists across the wood

layer. This causes the outflow of moisture to be relatively small in comparison with the inflow

rate. The exterior paint permeance unquestionably affects the outflow of moismre. However,

since the outflow rate is relatively small, the effect of exterior paint permeance on the rate of

moisture accumulation within the wood layer is small.

Effect of Sheathing - Wall Specimens 5 and 6

A comparison between measured and predicted moisture content at the inside sheathing surface

and the inside surface of the sugar pine for wall 5 is given in Figure 23. This wall is identical

to wall specimen 1 , except that fiberboard sheathing is installed between the insulation and the

sugar pine. The 6rms is 0.8 percent moisture content at the inside surface of the fiberboard and

1.1 percent moisture content at the inside surface of the sugar pine, indicating good agreement

between measured and predicted moisture contents. Comparing Figures 23 and 19, it is seen

that the fiberboard sheathing provides additional moisture storage and reduces the peak moisture

content at the inside wood surface.

A similar comparison for wall specimen 6 with plywood sheathing is given in Figure 24. Here

the agreement between measured and predicted moisture contents is not as close. The 6rms

between the measured and predicted is 1.5 percent moisture content at the inside plywood

surface and 5.3 percent moisture content at the inside wood surface. The unsatisfactory

prediction by MOIST for this wall specimen was attributed to the nonhomogeneity of the

plywood, i.e., plywood is comprised of distinct layers of wood and glue. In the computer

simulations, plywood was modeled as a homogeneous material.

Effect of Cavity Insulation - Wall Specimens 7 and 8

The results for wall specimen 7 are given in Figure 25. This wall is identical to wall

specimen 1, except that thermal insulation was excluded leaving only an airspace in the wall

cavity. The 6rms of 0.6 indicates good agreement between the measured and predicted moisture

contents. Comparing Figures 25 and 18, the measured peak moisture content reached 14 percent

moisture content with an air cavity and 24 percent moisture content with insulation in the cavity.

Therefore, the presence of thermal insulation in the cavity increased the peak moisture content

at the sugar pine by approximately 10 percent moisture content.

It was not possible to make a meaningful comparison for wall specimen 8 with cellulose

insulation because the moisture content sensor at the inside wood surface malfunctioned during

the experiment and gave unreasonably high values (i.e., considerably above fiber saturation).

The presence of fire-retardant salts in the cellulose insulation caused the metered moisture

content to read unreasonably high compared to the actual moisture content at the wood surface

(Laurenzi 1994).

39
MEASURED AND PREDICTED MOISTURE CONTENT

WALL SPECIMEN 5

Inside surface fiberboard

30 I

\ \ \ 1 1 1 1

ELAPSED TIME (Days)

Inside surface sugar pine

0 10 20 30 40 50 60 70

ELAPSED TIME (Days)

Figure 23

40
MEASURED AND PREDICTED MOISTURE CONTENT

WALL SPECIMEN 6

Inside surface plywood

30

LU

\-

z

O

o

25 -

20 -

^RMS = 1 .5% MC Plywood

sheathing

Predicted

Wall

specimen

6

H

Z

LU

I-Z

o

o

LU

DC

D

hCO

O

30

25 -

20

15

20 30 40 50

ELAPSED TIME (Days)

Inside surface sugar pine

60 70

o 10

SrMS = 5.3% MC Plywood

sheathing

Wall

specimen

6

Predicted

Measured

0 10 20 30 40 50

ELAPSED TIME (Days)

Figure 24

60 70

41
MEASURED AND PREDICTED MOISTURE CONTENT

WALL SPECIMEN 7

30

ILU

Z 20

oO

LU

§ 15

I-

§10

^RMS = 0-6% MC

Cavity

airspace

Predicted Wall specimen 7

0 10 20 30 40 50

ELAPSED TIME (Days)

70

Figure 25

42
Modeling Insulation as a Storage Layer

For the comparisons of wall specimens 1 through 7, the cavity insulation was modeled as a nonstorage layer. In order to validate the capabilities of MOIST, a separate series of

comparisons with the cavity insulation modeled as a storage layer were conducted. The

agreement between measured and predicted results for these comparisons was comparable to the

previous comparisons with the insulation modeled as a nonstorage layer. However, when the

insulation was modeled as a storage layer, the authors encountered difficulty in achieving

convergence of the MOIST predictions. It was necessary to specify a large number of finitedifference nodes (i.e., greater than 20) within the insulation layer in order to achieve

convergence of the mathematical solution. Moreover, the MOIST predictions converged slowly

to the exact solution as the number of nodes was increased. Consequently, this made it difficult

to determine if a sufficient number of nodes were being used for convergence.

Typical Wall Construction and Vapor Retarder Defects - Wall Specimens 9 to 12

As mentioned above, wall specimens 9 through 12 were selected as representative of current

building practice. The effect of a vapor retarder was investigated for these four walls. The

walls were constructed of gypsum wallboard, glass-fiber insulation, foil-faced polyisocyanurate

sheathing and vinyl siding. Wall specimens 9, 10, and 11 were constructed with a vapor

retarder, whereas no vapor retarder was used on wall specimen 12. Wall specimens 10 and 11 were constructed purposely with a defect in the vapor retarder to simulate air leakage around

an electric outlet. Moisture content sensors on a sugar pine substrate (Figure 8d), were placed

at the center of each measurement section on the interior side of the polyisocyanurate sheathing.

The relative humidity at the interior surface of the polyisocyanurate sheathing was obtained by

converting the measured output of the moisture content sensors using the sugar pine adsorption

curves. The moisture content readings associated with wall specimen 11 were erroneous and

are not presented. The resulting measured relative humidities for wall specimens 9, 10, and 12

are compared in Figure 26. Note that the surface relative humidity of wall specimen 12 (without

vapor retarder) is saturated (100 percent) between the two sinusoidal conditions. On the other

hand, the surface relative humidity for wall 9 (with a kraft-paper vapor retarder) rises to 92

percent during the same period. Use of the vapor retarder reduced the flow of water vapor into

the wall resulting in a reduced water vapor pressure and relative humidity at the interior surface

of the polyisocyanurate sheathing. It is interesting to note that the result for wall 10 (with a 11.5-mm hole in the vapor retarder) falls between the cases with and without a vapor retarder.

MOIST was used to predict the relative humidity at the interior surface of the polyisocyanurate

sheathing of wall specimen 9 (with a kraft-paper vapor retarder). The predicted surface relative

humidity (dashed line) is compared to the measured value (solid line) in Figure 27. There is generally good agreement between measured and predicted values, except during the diurnal

sinewaves. During the sinusoidal conditions, the variation in amplitude of the MOIST

predictions are considerably larger than those measured. This may be attributed to the time

response of the moisture content sensors. A similar comparison is given in Figure 28 for wall

43
MEASURED SURFACE RELATIVE HUMIDITIES

WALL SPECIMENS 9, 10 and 12

>

t

Q

X

LU

>

I5

LU

DC

LJJ O

<

LL

tr

Z)

0)

r

100

90

80

70

60

50 -

40 - _

mi^} I L.

30

20

Wall 9 (with vapor retarder)

Wall 10 (1 1 .5 mm hole in vapor retarder)

Wain 2 (without vapor retarder)

1 1

0 10 20 30 40 50 60

ELAPSED TIME (Days)

Figure 26

44
MEASURED AND PREDICTED SURFACE RELATIVE HUMIDITY

WALL SPECIMEN 9

& 100

>

Q

I

LU>

I-5

LU

cr

LUo

<

11. cc

C/)

'iiiililii!!

With

vapor

retard erMeasured

MOIST

Wall specimen 9

20 30 40

ELAPSED TIME (Days)

Figure 27

50 60

MEASURED AND PREDICTED SURFACE RELATIVE HUMIDITY

>

3

X

LU>

ILU

DC

LUO

<

LL

CC3

CO

WALL SPECIMEN 12

50

40

30

20

Measured

MOIST

No vapor

retard er

Wall specimen 12

0 10 20 30 40

ELAPSED TIME (Days)

Figure 28

50 60

45
specimen 12 (without a vapor retarder). The agreement between measured and predicted values

is again seen to be good. It was not possible to use MOIST to predict the response for wall

specimens 10 and 11 because the penetrations in these walls caused significant departure from

one-dimensional moisture transfer.

Summary of Moisture Content Comparisons

The ^RMs for wall specimens 1 through 7 is summarized in Table 10. Comparisons were not

possible for wall specimen 8 due to the malfunctioning moisture content sensor. Wall specimens

9 through 12 did not include a hygroscopic sheathing or siding material and therefore moisture

content comparisons were not made. With the exception of wall specimen 6, MOIST was able

to predict the measured moisture contents with a maximum 6rms of 1. 1 percent moisture content.

Table 10

Summary of Root-Mean-Square Differences

Between Measured and Predicted Moisture Contents

Wall

Specimen

Wall Description

(Parameter of Interest)

Root-Mean-Square

Differences

(%MC)

1 Base case 1.1

2 Vapor retarder of kraft paper and asphalt mastic 0.9

3 Interior latex paint and exterior oil-base paint 0.5

4 Interior and exterior latex paint 1.1

5 Fiberboard sheathing

• Inside sheathing surface

• Inside wood surface

0.8

1.1

6 Plywood sheathing

• Inside sheathing surface

• Inside wood surface

1.5

5.3

7 Cavity airspace 0.6

Heat Flux Comparisons

The heat flux measured by the heat flux transducers at the inside surface of the twelve wall

specimens was compared to corresponding values predicted by MOIST. For the computer

predictions, the glass-fiber insulation was again modeled as a nonstorage layer (i.e., the storage

of heat and moisture was neglected). The measured and predicted heat flux for wall specimen 1

46
were compared for the entire test period as shown in Figure 29. At time zero, the air

temperature at the exterior surface was decreased suddenly (fig. 5) causing, in this case, a positive heat flux at the interior surface (i.e., a heat loss). The large fluctuations in heat flux

during days 1 to 7 and 41 to 48 were caused by the diurnal sinewaves of the exterior air

temperature. After 48 days, the exterior air temperature was suddenly increased to 32 °C

causing the heat flux to change abruptly to a negative value (i.e., a heat gain). As observed in

Figure 29, the heat flux predicted by MOIST tracks the measured heat flux. However, the longtime scale and the close proximity of the two curves make it difficult to ascertain the level of

agreement. In-depth comparisons are examined below to assess the accuracy of MOIST heat

flux predictions.

For a one-week steady-state period proceeding the second series of sinewaves, the measured and

predicted heat fluxes for the 12 wall specimens were averaged and compared. The results are given in Figure 30 as a series of bar graphs. The first bar gives the measurement by the heat

flux transducer; the second, the prediction by MOIST. The agreement was within ±10 percent.

The differences between measured and predicted values are summarized in Table 1 1

Table 11

Comparison of Steady Heat Fluxes (W/m^)

Wall

Specimen

Measured

(W/m')

MOIST

(W/m')

Difference

(%)

1 6.24 5.93 -5.0

2 5.76 6.05 5.0

3 5.30 5.84 10.2

4 6.71 7.09 5.6

5 5.19 5.40 4.0

6 6.04 6.33 4.6

7 21.5 20.02 -6.9

8 6.04 5.46 -9.6

9 5.32 5.11 -3.9

10 4.34 4.70 8.3

11 4.81 4.79 -0.4

12 4.65 5.08 9.2

47
MEASURED AND PREDICTED HEAT FLUX

20

15

WALL SPECIMEN 1

6rms = 0.85 W/m'

Measured

20 30 40

ELAPSED TIME (Days)

Figure 29

60

COMPARISON BETWEEN MEASURED AND

PREDICTED STEADY-STATE HEAT FLUXES

X

<

LJU X

25

20

15

lOh

Heat flux transducer

MOIST prediction

4 5 6 7 8 9

WALL SPECIMEN

10 11 12

Figure 30

48
For the second series of diurnal sinewaves, a comparison of the measured and predicted timedependent heat fluxes for wall specimens 1 through 12 is given in Figure 31. The Sr^s given

in each of the plots is summarized in Table 12. The above comparisons show very good

agreement between measured and predicted time-dependent heat fluxes. The 6rms is expressed

in absolute units of W/m^ If we divide the d^^s by the mean heat flux, then the 6rms be

expressed as a percentage which ranges from 4 to 15 percent.

Table 12

Summary of Root-Mean-Square

Differences Between Measured and

Predicted Heat Fluxes

Wall

Specimen

Root-Mean-Square

Differences

(W/m^)

1 0.68

2 0.78

3 0.72

4 0.65

5 0.69

6 0.77

7 1.44

8 0.88

9 0.19

10 0.56

11 0.22

12 0.56

49
MEASURED AND PREDICTED HEAT FLUXES

WALL SPECIMEN 1 WALL SPECIMEN 2 WALL SPECIMEN 3

"T 1 1 1 HFT measurements &rms ~ ''^^ W/m^

- Moist prediction

I HFT measurements 8^(1^5 = 0,78 W/m -

Moist predictions

43 44 45 ELAPSED TIME (Days)

43 44 45 ELAPSED TIME (Days)

10

1 1 HFT measurements

Moist prediction

1 1 6rms = 0.72 W/nn2 -

_ Wall 3 Jm

\ L

_ V

1

m\ m J V V

1

- V V

1

1 43 44 45 ELAPSED TIME, Days

46

12

^10 «all^

(W/i g 8

LUI

WALL SPECIMEN 4

HFT measurements 6riuis = 0 65 W/m^

Moist prediction

43 44 45 ELAPSED TIME (Days)

WALL SPECIMEN 5 WALL SPECIMEN 6

HFT measurements 6p|j^g = 0.69 W/m^

Moist predictions

47 41

12 -

10

I HFT measurements

- Moist predictions

: 0.77 Wlm"

43 44 45 ELAPSED TIME (Days)

43 44 45 ELAPSED TIME (Days)

WALL SPECIMEN 7 WALL SPECIMEN 8 WALL SPECIMEN 9

HFT measurements bf^^^ = 1 ,44 W/m^

Moist predictions

43 44 45 ELAPSED TIME (Days)

42 43 44 45 46 ELAPSED TIME (Days)

I HFT measurements 6^^/13 = 0. 1 9 W/m^

-Moist predictions

47 41 42 43 44 45 46 47 ELAPSED TIME (Days)

WALL SPECIMEN 10 WALL SPECIMEN 11 WALL SPECIMEN 12

43 44 45 ELAPSED TIME (Days)

43 44 45 ELAPSED TIME (Days)

43 44 45 ELAPSED TIME (Days)

Figure 31

SO
COMPARISONS OF MOIST AND TARP

In order to provide another independent verification of the accuracy of the heat transfer

algorithms of MOIST, simulations of MOIST and the Thermal Analysis Research Program,

TARP (Walton 1983), were compared. TARP is a computer program developed at NIST to compute space heating and cooling loads for buildings. The program can compute sensible heat

transfer at interior surfaces of buildings, but does not account for either moisture transfer or the

latent heat effect due to adsorbed and desorbed moisture. Therefore, in order to make the

comparisons meaningful, a vapor impermeable paint layer was included in the MOIST geometry.

For boundary conditions, a constant interior air temperature of 21.15 °C and the exterior air

temperature from the calibrated hot box experiment were input for both programs. The interior

heat flux predicted by MOIST and TARP for the first seven days of the experiment are compared in Figure 32 for wall specimen 1 . The good agreement between MOIST and TARP

provides another independent verification of the heat transfer algorithms of MOIST.

51
MOIST AND TARP PREDICTED HEAT FLUXES

WALL SPECIMEN 1

01 \ \ I I \ \ I 0 1 2 3 4 5 6 7

ELAPSED TIME (Days)

Figure 32

52
COMPARISON OF STEADY-STATE HEAT FLUX MEASUREMENTS

TO ASHRAE PREDICTIONS

Additional comparisons were performed to determine the effectiveness of simple hand

calculations for predicting the steady-state heat flux through the wall specimens. In this case, the measured steady-state heat flux was compared to values calculated using procedures outlined

in the ASHRAE Handbook of Fundamentals (ASHRAE 1993). Following the ASHRAE

procedure, the overall thermal resistance for each wall specimen was calculated by summing the

thermal resistance of each individual layer of construction and the thermal resistance due to the

inside and outside air film coefficients or:

Here, J was equal to 3 or 4 depending on the number of material layers used in the construction

of the wall specimen. The thermal resistance of each layer was determined by:

By modifying the combined (free and forced) convection equation for a 0.5 m^ plate (Duffie and

Beckman 1991) to include the effects of natural convection, forced convection, and radiation,

the following equation was developed for the inside and outside air film coefficients:

In our experimental set-up, the surface temperatures were not measured in every case. Consequently, AT^^^ and T^^ were not known and had to be calculated. The thermal transmittance

and heat flux through each wall specimen were computed from the following equations:

^

W ^ h„

(7)

(8)

a I AT .

I I ^ + bv . + 4eaT I air I air m

(9)

U =

1 (10)

R^

q = U(T.-T^) . (11)

53
To determine q, eqs (7-11) were prepared and solved simultaneously for each wall specimen.

The input data for the inside and outside air temperatures and velocities were obtained from the

calibrated hot box experiment for days 10 through 14. For most of the wall materials, the

thicknesses and thermal conductivities were obtained from the results of the guarded hot plate

tests (Table 8). The values of thermal conductivity for the glass-fiber thermal insulation were

taken from Table 9 and accounted for the in situ density as installed in the wall specimen. For

the vinyl-lapped siding and the cavity airspace (wall specimen 7), thermal resistance values of

0.13 and 0.17 m^-K/W, respectively, were obtained (ASHRAE 1993). The input data,

computed thermal resistance, transmittance, and heat flux for each wall specimen are summarized in Table 13.

As anticipated, the most pronounced result of the analysis was the effect of installing thermal

insulation within the cavity airspace. The thermal resistance of wall specimen 7 (cavity airspace)

was approximately three times less than similar constructions with insulation. Consequently, the

heat flux through this specimen was about three times greater than the other wall specimens.

The specimen heat flux was also decreased by the addition of a layer of sheathing. Using wall

specimen 1 as the basis, the addition of plywood was found to increase the overall thermal

resistance by 7 percent; fiberboard, by 10 percent; and, polyisocyanurate foam, by 25 percent.

Note that the variations in heat flux for specimens with glass-fiber thermal insulation were

caused by the local density variations of the glass-fiber insulation.

The measured thermal resistance for each wall specimen was computed for days 10 through 14

(120 hours) of the winter test condition, the same interval used for the ASHRAE calculations.

For this interval, the measured thermal resistance of each wall specimen was determined by

dividing the summation of the (air) temperature difference across the wall specimen by the

summation of the heat flux from the heat flux transducer, or:

120

R_, = ill (12) HFT 120

t=i

The differences between the measured and predicted values are summarized in Table 14 and

plotted in Figure 33. In general, the differences ranged from -13 to -1-5 percent.

54
Table

13

Steady-State

Thermal

Transmission

Properties

and

Predicted

Heat

Fluxes

5.77 5.87 5.68 6.91 5.31 6.22 19.66 II

5.38 1

4.96 4.71 4.95

Thermal Transmittance

(W/m^

-K)

0.417 0.416 0.403 0.483 0.382 0.442 1.396 0.371 0.353 0.331 0.329 0.339

Thermal Resistance (m'-K/W)

2.40 2.41 2.48 2.07 2.62 2.26 0.72 2.69 2.83 3.02 3.04 2.95

Experimental

Outside

Air

Temperature (°C)

r- q

r-"

00

no' m 1-H q

NO q OnNO NO

Calculated

Outside

Film

Coefficient

(W/m'

K) 00

(N00 00(N

00 00

00

od On

00 00

rt- 00 00Tt; 00 00

Thermal Resistance Layer

4

(m^KAV)

1 1 1 1 0.21 0.21

1 0.13 0.13 0.13 0.13

S a >- C

.a

0.21 0.21 0.21 0.21 0.25 0.17 0.21 0.21 0.61 0.61 0.61 0.61

Thermal Resistance Layer

2

(m^K/W)

1.83 1.84 1.91 1.50 1.81 1.53 0.17 2.12 1.74 OS 1.95 1.86

Thermal Resistance Layer

1

K-KAV)

0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08

Calculated

Inside

Film

Coefficient (W/m'K)

m

NO

>nNO NO NO

NO NO NO r- NO NO

"^

NO NO

TtNO

Experimental

Inside

Air

Temperature (°C)

(N tN r-H T-H (N

(N

(N

<N <s fS

aa IT) NO t^ 00 OS O^H

55
R-Value Com

Table 14

parison for Days 10 through 14

Wall T T till Specimen (m'K/W) (m^K/W) (m^K/W) (%)

1 2.40 2.17 -0.23 -9.6

2 2.41 2.37 -0.04 -1.5

3 2.48 2.58 0.10 4.2

4 2.07 2.07 0.00 0.0

5 2.62 2.58 -0.04 -1.6

6 2.26 2.23 -0.03 -1.5

7 0.72 0.63 -0.09 -12.6

8 2.69 2.40 -0.29 -10.7

9 2.83 2.62 -0.21 -7.6

10 3.02 3.17 0.15 5.1

11 3.04 2.92 -0.12 -4.1

12 2.95 3.04 0.09 2.9

56
MEASURED VERSUS PREDICTED THERMAL RESISTANCE

3.5

3.0

2.5

CM

LJJ o

< 2.0

LJJ 1 .5

CL

< 1.0

DC

LJJ X 0.5

0

ASHRAE calculation

I I Heat flux transducer

4 5 6 7 8

WALL SPECIMEN

10 11 12

Figure 33

57
EFFECT OF MOISTURE ON HEAT TRANSFER

The effect of moisture on heat transfer was investigated by comparing the measured heat fluxes

from the first and second series of diurnal sinewaves. These sinewaves were separated by a 34-

day steady-state winter condition in which moisture accumulated in the hygroscopic sheathing

and siding materials. Thus, the wall specimens were comparatively "dry" during the first series

of diurnal sinewaves because insufficient time had elapsed for moisture to accumulate.

However, by the second series, a considerable amount of moisture had accumulated in the

sheathing and siding. To accenmate the potential effect, two wall specimens without a vapor

retarder were selected for the comparison, wall specimen 1 (glass-fiber cavity insulation) and

wall specimen 8 (cellulose cavity insulation).

The exterior air temperatures for the first and second series of diurnal sinewaves are compared

for 4 days in Figure 34. The two waveforms are nearly the same, varying from 1. 1 to 15.6 °C.

During both periods, the interior air temperamre was maintained at 21.2 ± 0.1 °C. The

corresponding diurnal heat fluxes for wall specimens 1 and 8 are shown in Figure 35. The

waveforms are nearly the same, indicating that for these temperatures (note that there was no

reversal in heat flux) moisture accumulation had little or no effect on the heat transfer.

Although considerable moisture had accumulated in the sugar pine of the wall specimens

(fig. 19), the level was below the fiber saturation point. Therefore, no liquid water was in the

pore space of the materials. The authors recognize that under other temperature conditions when

liquid water is present in construction, latent heat can have a large effect on heat transfer (Hedlin

1988).

58
COMPARISON OF AMBIENT OUTDOOR

TEMPERATURES

(FIRST VERSUS SECOND SERIES SINEWAVES)

20

1 2 3

RELATIVE ELAPSED TIME (Days)

Figure 34

59
COMPARISON OF HEAT FLUXES

(FIRST VERSUS SECOND SERIES SINEWAVES)

Wall Specimen 1

Glass-fiber

insulation

First series of sinewaves --0-- Second series of sinewaves

0 1 2 3

RELATIVE ELAPSED TIME (Days)

Wall Specimen 8

First series of sinewaves --o-- Second series of sinewaves

0 1 2 3

REUMIVE ELAPSED TIME (Days)

Figure 35

60
SUMMARY AND CONCLUSIONS

A comprehensive laboratory study was conducted to verify the accuracy of MOIST, a personal

computer program that predicts the transient one-dimensional heat and moisture transfer in

building envelopes. The rate of heat transfer and moisture content of twelve wall specimens,

typical of residential wood-frame construction, were measured and subsequently compared to simulations by MOIST. In addition, the steady-state heat fluxes of each wall specimen were compared to values calculated using procedures outlined in the ASHRAE Handbook of

Fundamentals .

The twelve wall specimens were assembled collectively in the NIST calibrated hot box and

exposed to both steady-state and transient temperature conditions over a continuous period of 104

days. Eight of the wall specimens were designed to examine the relative effects of different

constructions on the accumulation of moisture in the wall specimen. The other four specimens

investigated the effectiveness of vapor retarders in controlling the movement of moisture. The

interior ambient air was maintained at fixed levels of temperature and relative humidity during

the experiment. The exterior ambient air was varied to promote moisture accumulation in the

specimens during transient and steady winter conditions and drying during the steady summer

condition.

Each wall specimen was constructed with an isolated circular meter section in order to promote

one-dimensional moisture transfer through the specimen. The rate of heat transfer through each

specimen was measured using a single heat flux transducer located at the interior surface of the

wall specimen. The moisture content of selected building materials within the specimen was

determined using electrical-resistance moisture content sensors. An extensive calibration was

conducted to provide an individual calibration for each heat flux transducer and moisture content

sensor. Results of the moisture content sensor calibration showed significant sensor-to-sensor

variability indicating serious errors would have occurred if only a single sensor calibration had

been used.

MOIST simulations were conducted using the same boundary conditions as those imposed on the

wall specimens during the calibrated hot box experiment. In addition, to minimize the

uncertainties associated with material variability, the material properties - sorption isotherm,

permeability, and thermal conductivity - were measured for each of the materials used in the

wall specimens. Comparisons were conducted for eight wall specimens instrumented with

moisture content sensors in their exterior hygroscopic materials. In general, the agreement

between predicted and measured moisture content was good. For six of these walls, the root- mean-square differences were less than 1 . 1 percent moisture content. The largest difference was

5.3 percent moisture content for a wall specimen with plywood sheathing. A comparison with

a wall specimen that contained cellulose loose-fill insulation was not possible because the sensor

failed.

61
The other four walls were constructed with a sheathing layer of foil-faced polyisocyanurate

foam. Here, moisture content sensors on a sugar pine substrate were applied and used to determine the relative humidity at the interior surface of the sheathing. The measured relative

humidities were in close agreement with those predicted by MOIST. For the interior and

exterior ambient conditions used in the experiment, the inclusion of a vapor retarder did not

significantly reduce the relative humidity at the interior surface of the sheathing. If climatic

conditions had existed in which the interior surface of the sheathing was below the dew point

of interior air, then the presence of a vapor retarder would have had a larger effect on the

moisture content of the building materials.

In general, the values of heat flux predicted by the MOIST simulations were in good agreement

with the measured values. For the twelve wall specimens, the predictions of steady-state heat

flux were within 10 percent of the measured values. During the transient portion of the

experiment, the root-mean-square differences between the predicted and measured values for the

12 specimens ranged from 4 to 15 percent. The predicted values of heat flux from the MOIST

simulations were also in good agreement with the predictions of the Thermal Analysis Research

Program, a computer program for building and cooling load simulations. The measured steadystate heat flux of the twelve wall specimens ranged from —13 to -1-5 percent of the values

predicted using the procedures outlined in the ASHRAE Handbook of Fundamentals . For these

particular experiments, moisture was found to have an insignificant effect on heat transfer.

62
ACKNOWLEDGMENTS

We appreciate discussions with the following reviewers: Dale Bentz, Dr. Walter Rossiter at NIST and Dr. William C. Thomas at the Virginia Polytechnic Institute and State University.

Their comments greatly improved the report. We also acknowledge the following persons and

contributions. The wall specimens were constructed under the supervision of Donn Ebberts with

assistance from John Judge. Programming for data acquisition was provided by Kevin Simmons.

Daily monitoring of the calibrated hot box during testing was provided by Kenneth Kramp and

Daniel Shapiro. The moisture content sensors were calibrated by Kenneth Kramp and Holly

Chandler. We also thank Kimberly Whitter for preparing this manuscript for publication.

63
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the NBS Calibrated Hot Box," ASTM Journal of Testing and Evaluation. 1987 May. Vol. 15,

No. 3, pp. 167-177.

65
APPENDIX A

BUILDING MATERIALS

1) Cellulose—loose-fill insulation comprised mostly of macerated paper, chemically treated

with fire retardants. The cellulose was hand installed in the wall cavity at a nominal

density of 56 kg/m^ (3.5 Ib/ft^).

2) Fiberboard, intermediate grade—12.7 mm (Vj in.) rigid board comprised of small lignin

and cellulosic fibers (usually wood or cane) interfelted for intermediate type exterior

sheathing (see ASTM Specification C 208). This particular product contained an added

binder, probably asphalt.

3) Glass-fiber insulation—fibrous-glass batt cavity insulation with phenolic binder. Two types were acquired. The first type was manufactured without a vapor retarder (i.e. , no backing)

and the second type was manufactured with a vapor retarder of kraft paper with asphalt

mastic.

4) Gypsum wallboard—12.7 mm (Vj in.) interior sheathing of essentially gypsum core with

paper bonded to the core (see ASTM Specification C 36.)

5) Paint, latex—coating of water-based paint consisting of one coat primer and one coat finish.

The paint was white in color and applied with a brush. The exterior latex paints contained

a fungicide to discourage the growth of mildew fungi.

6) Paint, oil—coating of oil-base paint consisting of one coat primer and one coat finish. The

paint was white in color and applied with a brush. The exterior oil paints contained a fungicide to discourage the growth of mildew fungi.

7) Pine, sugar— 19.1 mm (V4 in.) clear (i.e., no knots) planks of sugar pine 324-mm-wide,

for tongue-in-groove siding.

8) Plywood, fir—12.7 mm (Vj in.) rigid board for exterior sheathing comprised of five layers

of thin sheets of wood (group 1 , grade A-C veneer) glued so that grains of adjacent layers were at right angles.

9) Polyisocyanurate, foil-faced—12.7 mm (Vj in.) rigid board for exterior sheathing comprised

of a cellular plastic foam core reinforced with laminated foil facers on both sides.

10) Vinyl plastic lapped siding— white in color with a simulated wood-grain finish. Length:

3.4 m (135 in.) in increments of 127 mm (5 in.); Thickness: 1.0 mm (0.04 in.).

66
APPENDIX B

PERMEANCE MEASUREMENTS

Thermal Insulation Materials

The permeance of the glass-fiber insulation was assumed to be equal to that of a stagnant air

layer. This assumption is reasonable because the glass fibers of the insulation occupy a very

small fraction of its volume. In this situation, it would be expected that bound-water diffusion

along the glass fibers would be very small compared with molecular diffusion through the pore

space. This assumption is supported by data contained in ASHRAE (1993) which shows that

the permeability of mineral wool is very nearly the same as that for a stagnant air layer. A

series of measurements, described below, were conducted to investigate whether the permeability

is dependent upon the mean relative humidity across an air layer.

The experimental setup is depicted in Figure B-1 (a). Five precision-bore tubes, 3 mm in

diameter and about 100 mm in length, were sealed into the top of glass vials. The vials were

placed inside sealed glass vessels. Saturated salt-in-water solutions were used inside the glass

vials and glass vessels to generate steady relative humidity environments at the lower and upper

surfaces of the precision-bore tubes. For the five vial/vessel assemblies, the salt solutions given

in Table B-1 were used to provide small differences in relative humidity of about 10 percent

across the precision-bore tubes, covering the entire humidity range (fig. B-1 (b)). The

measurements were conducted at an ambient temperature of 23.4 + 0.1 °C.

Table B-1

Relative Humidities^ above Salt Solutions

No.

Salt Solutions Relative Humidities (%)

Vial Vessel Vial Vessel

1 LCI KC2H3O2 11.30 22.74

2 MgCl2 K2CO3 32.88 43.16

3 NaBr KI 58.12 69.20

4 NaCl KCl 75.36 84.59

5 Sr(N03)2 K2SO4 85.66 97.39

' Equilibrium relative humidities above saturated salt solutions were taken

from Greenspan (1977).

67
PERMEABILITY TEST METHOD FOR

FIBROUS INSULATIONS

To

laboratory

balance

Rubber

seal

Support string

Plastic

cup

Fibrous

insulation

Porous

screen

Plexiglas

cover

Vacuum

grease

seal

Glass

vessel

Salt solution

or dessicant

Salt solution

Experimental setup

INSULATION THICKNESS (L)

Analysis procedure

Figure B-1

68
The vials were weighed, placed in the glass vessels, and then weighed again at the end of a 2-

month period. The water vapor transfer rate through the tubes was taken as the difference

between the initial and final weights divided by the elapsed time. From Kreith (1968), the

permeability may be determined from the relation:

w A|i atm In

atm gv P -P atm V /

(B-1)

A plot of permeability measurements versus mean relative humidity is given in Figure B-2. The

permeability is seen to be a constant value of 1.82 x 10 '° kg/s-m-Pa and therefore does not

depend on relative humidity. This permeability measurement agrees within 4 percent of the

value published by ASHRAE (1993). The above permeability measurement of a stagnant air

layer was also used for the cellulose insulation.

Gypsum Wallboard

The permeance of gypsum wallboard was determined using three cup/vessel assemblies shown

in Figure B-3. One sheet of gypsum wallboard was installed in the first cup, two (stacked) in

the second cup, and three (also stacked) in the third cup. The measurements were conducted

at a temperature of 21.4 °C. Magnesium-nitrate (MgNOj) salt solutions were placed in the

cups, while potassium-carbonate (K2CO3) salt solutions were placed in the glass vessels. The

ambient relative humidity above the solutions of MgNOj and K2CO3 were measured using a precision dew-point hygrometer and found to be 51.3 percent and 42.5 percent, respectively.

The interior surface of the gypsum wallboard faced the relative humidity of 51.3 percent. The

water vapor transfer rate through the three specimens was determined by weighing the cups once

a week as described above.

The total water vapor resistance, including the two air layers at the upper and lower surfaces of

the specimen, was determined by the relation:

AV* L_ (3.2)

w 1.75 X

10~'°

The last term of the above equation accounts for the reduction in the water vapor transfer

resistance of the air layers due to the presence of the specimen.

The total water vapor resistance for the three cup/vessel assemblies was plotted versus the

thickness of the specimen, as shown in Figure B-4. Again, the y-intercept at zero thickness

represents the water vapor transfer resistance of the two air layers (extrapolated to a hypothetical zero thickness). The reciprocal of the slope (m) of this best-fit line is equal to a permeability

of 6.38 X 10-1' kg/s-m-Pa.

69
to 2 5

CD

2.0 -

o 1.5 h

b

> 1.0 h

LLJ

DC

LU_

0

WATER VAPOR PERMEABILITY OF A

STAGNANT AIR LAYER

(Tambient - 23.3°C)

Ii= 1.82x10'''°kg/s-m-Pa

• NIST measurement

1 1 L 1

0 10 20 30 40 50 60 70

RELATIVE HUMIDITY (%)

J_ 80 90 100

Figure B-2

70
PERMEABILITY TEST METHOD FOR GYPSUM WALLBOARD

Glass

Vessel

Vacuum

Grease Seal

Specimen

Wax

Seal

Saturated Salt Solutions

Experimental set-up.

Figure B-3

WATER VAPOR TRANSFER RESISTANCE

VERSUS THICKNESS FOR GYPSUM WALLBOARD

0 5 10 15 20 25 30 35 40

THICKNESS (mm)

Figure B-4

71
Paint Layers

Latex Paint Applied to Gypsum Wallboard

Four cup/vessels assemblies were prepared as shown in Figure B-3 . A single layer of gypsum

wallboard was installed in the first cup. The other three cups contained gypsum wallboard with

the interior latex paint system (i.e., a primer and finish coat) applied to its interior surface.

Note that the coatings of paint were applied at the same time as the wall specimens. The

measurements were subsequently conducted as described above for the gypsum wallboard.

The total water vapor transfer resistance for each of the four cups was determined by eq (B-2).

The resistance for each of the paint layers was determined by taking the difference in resistance

between a cup with a latex paint and the cup without latex paint. The permeance of each of the

paint layers is the reciprocal of its resistance. The permeance of the three paint layers was

found to be 9.04 x lO"*" kg/s-m^-Pa, 1.029 x 10"" kg/s-m^-Pa, and 1.00 x 10"^

kg/s-m^-Pa. The average permeance is 9.77 x 10"^° kg/s-m^-Pa.

Oil and Latex Paint Applied to Sugar Pine

Similar measurements were conducted to determine the permeance of the exterior latex and

exterior oil-base paint systems. Both of the paint systems were comprised of a primer and finish

coat. Three cup/vessel assemblies were prepared. The first cup contained a single layer of

sugar pine. The other cups contained single layers of sugar pine with latex and oil-base paint

systems applied. In this case, the measurements were carried out at a temperature of 6.7 °C.

Potassium-acetate (KC2H3O2) salt solutions were placed in the cups, while calcium-chloride

(CaClj) desiccant was placed in the glass vessels. The ambient relative humidity above the

solutions of KC2H3O2 and CaClj was 23.2 and 1.4 percent, respectively. The painted surfaces

of the sugar pine faced the relative humidity of 1.4 percent. Applying the method above, the

permeance of the latex and oil-base paint systems were found to be 1.9 x 10"'° kg/s-m^-Pa and

8.04 X 10"'' kg/s-m^-Pa, respectively.

Convective Airspace

The water vapor permeance of the vertical airspace for specimen 7 was calculated using a modified form of the Lewis relation (Threlked 1970):

Le = 0.622 — . (B-3)

hw

c P^ p atm

Taking the Lewis number as 0.927, the convective conductance of the airspace as 2.00 W/m^-K,

the specific heat of air as 1000 J/kg-K, and the atmospheric pressure as 1.01 X 10^ Pa, the

water vapor permeance of the vertical airspace was determined to be 1.33 x 10"^ kg/s-m^-Pa.

* tr.S. GOVEBNMENT PRTCmilG OFFICE: 1995 . 386-627 - 814/37905

72
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