United States

Department of

Agriculture Accelerated Aging Forest Service

Forest

Products

Laboratory

of Phenolic-Bonded

Research

Paper

FPL 393 Hardboards and

April 1981 Flakeboards
Abstract

This report is the second on results

of a continuing series of investigations that establish an information

base on durability of new exteriortype, wood-based panel products.

Four nominal 1/2-inch-thick commercial. hardboards were exposed to

various accelerated aging treatments;

results were compared with results

from an earlier study of flakeboards,

plywood, and solid wood exposed to

the same treatments. Actual values

for original properties and properties

retained after aging were generally

lower for the flakeboards and the

hardboards than they were for the

plywood; however, for the best performing boards degradation rates and

percentages of original property retained were comparable to those of

plywood. The conclusion is the best

performing flakeboards and hardboards are suitable for long-term exterior applications.

Acknowledgment

The laboratory exposure of hardboards and much of the testing was

conducted by Anne Slack, a student

trainee. E. A. Okkonen of the

Laboratory staff assisted with testing

and performed the data processing.
United States

Department of

Agriculture

Forest Service

Forest

Products

Laboratory1

Research

Paper

FPL 393

Accelerated Aging

of Phenolic-Bonded

Hardboards and

Flakeboards

BY

BRYAN H. RIVER, Forest Products Technologist

ROBERT H. GILLESPIE, Chemist

and

ANDREW J. BAKER, Chemical Engineer

Introduction

The variety of structural panel products produced from wood increases

yearly, spurred by the increasing use

of a wider variety of particle geometries, board designs, manufacturing

processes, and adhesive systems. Information about the durability of

these new products is important to all

segments of the building industry.

This report describes the second of a

series of investigations designed to

obtain basic information on durability

of exterior-type, wood-based panel

products. In this work, results of the

behavior of four exterior-type hardboard materials are compared to

those of solid wood, plywood, and

structural flakeboard in a previous investigation (2). 2

All materials were exposed to four

regimes for aging the boards:

(1) Cyclic boil-dry, (2) cyclic vacuumpressure, soak-dry, (3) ASTM D-1037

accelerated aging, and (4) outdoor

weathering. Degradation was

evaluated by changes in: (1) Modulus

of rupture (MOR), (2) modulus of

elasticity (MOE), (3) internal bond

strength (IB), and (4) thickness. The

results are presented in the form of

fitted regression lines of each property versus the number of aging cycles

and in histograms that present comparisons of the initial value of each

property with the value after 80 cycles

of boil-dry or soak-dry aging. Results

of outdoor weathering will be summarized in a later report.

Background

The principal factors in bond

degradation are heat, moisture, and

stress; most laboratory aging tests

consist of some sequence of these

factors. Although to suppose

laboratory aging exposures can quantitatively duplicate an actual service

environment is unreasonable, many

artificial exposures have been found

to degrade weather-resistant

materials at a rapid rate. These exposures are useful for a quick comparison of the performance of new

products to that of products with a

history of successful service. By

these comparisons, materials can be

ranked, and their service lives

estimated.

The prescribed test for durability of

type-2, mat-formed wood particleboard is described in ASTM Method

D-1037 (1). The aging exposure consists of six cycles of soaking, steaming, freezing, and drying for a 12-day

period. Some people feel the test effects are the equivalent of 50 years of

aging, but no actual data support

this. Researchers at the West Coast

Adhesive Manufacturers Association

(WCAMA) studied effects of various

portions of the ASTM D-1037 cycle

(14). They found two cold-water soak

swell-shrink treatments were not as

deleterious as two boil treatments in

each D-1037 cycle. But the study also

showed the freeze treatment in each

D-1037 cycle was relatively ineffective. In a followup to this study, the

researchers at WCAMA found a

simplified test requiring only 6 days

and consisting of vacuum-pressuresoak, boil and dry (WCAMA method

6.1) correlated with 5-year test fence

results as well as those of more complex ASTM D-1037 test (13). Shen and

Wrangham (12) have presented an

accelerated-aging test using a 2-hour

boil followed by wet testing as defined in the German Standard DIN 68761

(7) for determining change in internal

bond strength. This treatment has

1

 Maintained at Madison, Wis., in cooperation

with the University of Wisconsin. 2

 Italicized numbers in parentheses refer to

Literature Cited at end of report.
also been included in the Canadian

Standard CSA-0188-75 (3), and is applied to bending specimens.

None of these exposure sequences

provides a means to follow aging or

deterioration of a board. Instead, they

are “torture tests” that provide only a

comparison of the mechanical properties before and after the treatment.

They do not provide an indication of

the various rates at which degradation will proceed during the life of a

product.

Actual testing of particleboard performance in outdoor exposure has

been limited. The most information is

from work reported by Hann, Black,

and Blomquist (8, 9), Jokerst (10), and

Geimer, Heebink, and Hefty (6). Investigations have also beer: reported

by the WCAMA (13, 14) and by Clad

and Schmidt-Hellerau (5). In summary,

the results of these investigations

showed a pattern of rapid loss of

strength and stiffness during the first

and second year followed by a much

slower rate of loss in ensuing years.

Baker and Gillespie (2) in the first

report of this series compared the

behavior of phenolic-bonded

flakeboard with that of solid wood

and plywood exposed to four

accelerated-aging exposures: (1) Up to

80 cycles of boiling and drying at

elevated temperature, (2) up to 40

cycles of vacuum-pressure soaking

and drying at an intermediate

temperature, (3) the six-cycle, ASTM

D-1037 exposure, and (4) continuous

outdoor weathering at Madison, Wis.

The first and the second tests revealed the pattern of degradation and

the rate of degradation, which are

new dimensions in estimating service

life of particleboard. The initial

strength and the initial stiffness of

the flakeboards were lower than

those of both plywood and solid

wood. Many flakeboards exhibited the

same rapid initial loss of properties

noted in outdoor weathering, but the

rates of property loss after the initial

drop were comparable between the

flakeboards and the plywood. The

authors concluded the phenolicbonded flakeboards were suitable for

structural applications in which conventional wood products are used.

Another class of exterior-grade

panel products are thick hardboards

of the type commonly used for house

siding. Their durability, however, has

not been compared to other exterior

panel materials.

2

Experimental

Materials

Four nominal 1/2-inch-thick (12.7

mm) commercial hardboards were

selected, and were assigned the

alphabetical identifications S, T, U,

and V. No information about their

manufacture was available except a

phenolic binder was used; all material

of a given type was from a single

panel. S, T, U, and V and other

materials are listed in table I (also

with alphabetical identifiers); the

other materials are from the first investigation (2).

Specimens

Each panel was cut into bending

specimens 2 inches by 12 inches (50

x 305 mm) with the 12-inch dimension

parallel to the long axis of the panel.

After the bending test, internal bond

specimens 1/2 inch by 2 inches by 2

inches (12.7 x 50 x 50 mm) were cut

from one end of each bending specimen. For mounting the specimens on

racks, 1/4-inch (6.35 mm) holes were

drilled in the opposite end of each

bending specimen. Specimens were

stored at 80° F (27° C), 65 percent

relative humidity until exposure. During exposure, the specimens were

spaced 1/4 inch (6.35 mm) apart on

the racks.

Exposures

The equipment and procedures

were the same as those described by

Baker and Gillespie (2) and will only

be briefly summarized:

Controls.—Ten specimens of each

type were conditioned to equilibrium

at 80° F (27° C), 65 percent relative

humidity, and tested to provide control data.

Boil-dry exposure.—Thirty

specimens of each type were initially

saturated with water by vacuumpressure soak, which consisted of 30

minutes under 29-inch (735 mm) mercury vacuum followed by 30 minutes

under 60 pounds per square inch (420

kPa) pressure while immersed in

water, then subjected to the required

number of cycles of the following

treatment (the vacuum-pressure soak

treatment was applied only before the

first boil-dry cycle): 10 minutes in boiling water followed by 3-3/4 hours of

drying in an air-circulating oven at

225° F (107° C). Five randomly

selected specimens of each panel

type were removed for testing after 1,

5, 10, 20, 40, and 80 boil-dry cycles.

Vacuum-pressure, soak-dry exposure. —Twenty-five specimens of

each type were subjected to cycles

consisting of the vacuum-pressure

soak described in the preceding

paragraph, then 23 hours of drying in

an air-circulating oven at 180° F (82°

C). Five randomly selected specimens

of each type were removed for testing

after 1, 5, 10, 20, and 40 cycles.

ASTM D-1037 accelerated-aging exposure. —Five specimens of each

board type were subjected to six

cycles of the following treatment:

1. Soaking in water at 120° F (49°

C) for 1 hour.

2. Spraying with steam and water

vapor at 200° F (93° C) for 3 hours.

3. Storing at 10° F (-12° C) for 20

hours.

4. Drying at 212° F (100° C) for 3

hours.

5. Spraying with steam and water

vapor for 3 hours.

6. Drying at 212° F (100° C) for 3

hours.

After exposure, all of the specimens

were removed for testing.

Weathering. —Thirty specimens of

each type were placed on exposure at

an angle of 60° above horizontal, facing south at the outdoor exposure

site of the Forest Products Laboratory, Madison, Wis. The angle was

chosen arbitrarily to prevent water

from upper specimens dripping on

lower specimens. Five random

specimens of each type will be removed for testing after 1 year and at

five intervals of approximately 1 year

thereafter.

Conditioning,

Measurements, and Testing

After removal from exposure,

specimens were reconditioned to

equilibrium at 80° F (27° C), 65 percent relative humidity. Thickness,

width, and weight were measured

before testing. Each specimen was

then tested to obtain the bending

load-deformation curve; internal bond

strength (IB) was determined by the

procedures outlined in ASTM D-1037

and from those described in the

previous report (2).

Data Analysis

In this work, modulus of rupture

(MOR) and modulus of elasticity
(MOE) were calculated on the basis of

the dimensions measured after reconditioning at 80° F (27° C), 65 percent

relative humidity after exposure. This

is in contrast to the calculations in

the first report (2), which were based

on the dimensions before exposure.3

For comparison here, data from the

first study were also recalculated using dimensions after exposure. The

specimens used in this work were

smaller than those specified in ASTM

D-1037 for determining MOR and MOE

of 1/2-inch-thick (12.7 mm) specimens.

Further analysis of the data from

the cyclic boil-dry and soak-dry exposures was carried out using the

Minitab II Statistical Computing

System (11). The change in MOR,

MOE, IB, and the percent thickness

swelling of each specimen compared

to the average of the control

specimens was determined for each

test interval (1, 5, 10, 20, 40, 80

cycles). Then these changes expressed as “percent” or “percent retained”

were fitted to each of the following

regression models using the number

of aging cycles as the independent

variable, X, and the percent or percent

retained as the dependent variable, Y.

Linear: Y = AO + A1X (1)

Hyperbolic: Y = AO + A1X + A2/X (2)

Log: Y = AO + A1

 log X (3)

In the earlier report, Baker and

Gillespie used the linear model (1).

Analysis of variance (ANOVA) was

conducted to test two hypotheses:

First, that the variability explained by

the regression of the observed property (MOE, MOR, etc.) was not significantly greater than the variability (error) expected from the choice of the

regression model and pure error; and

second, that the error attributable to

the choice of the regression model

was not significantly greater than expected from pure error (natural

3

 In this work, MOR and MOE were evaluated

primarily as measures of degradation. Both properties are more sensitive and less variable if

calculated using thickness after aging. It is

understood designers prefer MOR and MOE

calculated using original, or unaged thickness.

These values can be approximated from the data

in this Report by the equation:

MOR’ or MOE’ =

Vo x RN [to (1 + SN)]2

to

2

where Vo = unaged MOR or MOE from figs. 9, 13,

or 10, 14.

RN = pct retention of MOR or MOE after N

cycles from figs. 1, 5, or 2, 6.

to = the unaged thickness from table 1.

SN = pct swelling after N cycles from figs.

4 or 8.

material variability and experimental

error).

The format of the ANOVA table

was the following:

S.S. d.f. M.S. F

---------------------------------------------------------------

Regression

Residual

Lack of fit

Pure error

Total

where: S.S. = sum of squared deviations of observed property value from property value predicted by

regression model.

d.f. = degrees of freedom

MS. = S.S. ÷ d.f.

F = ratio of M.S.

Note: Residual S.S. = Lack of fit S.S.

+ Pure error S.S.

The F value is calculated for each

hypothesis as:

Hypothesis 1

F = Regression M.S. ÷ Residual

S.S.

Hypothesis 2

F = Lack of fit S.S. ÷ Pure error

S.S.

The calculated F is evaluated against

the value of F that can be expected

solely on the basis of pure error and

one of the following conclusions

drawn:

Hypothesis 1: Slope = 0

N.S.—Hypothesis is accepted. No

relationship exists between observed

property and number of aging cycles.

*—Hypothesis is rejected. A relationship exists between observed property and number of aging cycles at 95

percent level of confidence.

**—Hypothesis is rejected. A relationship exists between observed property and number of aging cycles at

99 percent level of confidence.

Hypothesis 2: Model fits

N.S.—Hypothesis is accepted. Error

due to lack of fit of model to data is

not significant compared to pure error; model is adequate.

*—Hypothesis is rejected. Error due

to lack of fit of model to data is

significantly greater than expected

pure error at 95 percent level of confidence.

**—Hypothesis is rejected. Error due

to lack of fit of model to data is

significantly greater than expected

pure error at 99 percent level of confidence.

Results and Discussion

Comparison of Degradation

Model Equations

The average properties of unexposed specimens are listed in table 1.

The percent retention of each property as a function of the number of aging cycles was fitted to each regression model. The capability of each

model to accommodate the data was

judged on the basis of the R

2

 statistic

and the “lack of fit” test. (R2, the correlation coefficient squared, may also

be interpreted as the fraction of the

variation in the property that can be

explained by the regression equation.)

Subjectively, the hyperbolic model

was distinctly better (higher R

2

’s and

fewer “lack of fit” indications) than

the linear model and was from

somewhat to distinctly more satisfactory than the log model. For uniformity, all of the comparisons in the

results are based on the hyperbolic

model. The coefficients of the fitted

equations plus the R

2

 values and the

“lack of fit” test results for each

equation are shown in tables 2

through 9.

Four categories of R

2

 and “lack of

fit” were evaluated: (1) Lack of fit (NS)

and R

2

 (high), (2) lack of fit (* or **)

and R

2

 (high), (3) lack of fit (NS) and

R

2

 (low), and (4) lack of fit (* or **)

and R

2

 (low). Of these, the first

category is the most desirable. The

second is also desirable because the

R

2

 in this case is generally very high

and the “lack of fit” indication results

only from the error term of the regression being very small. One hundred

and eight regression equations were

fitted; 45 of the regressions fell into

categories 1 and 2; and 51 fell into

category 3. Category 3 can be interpreted as meaning the data are so

scattered almost any model will fit

the data. All but two (18 of 20) of the

regressions for solid wood and

plywood fell in category 3. This probably reflects the greater natural variability of solid wood compared to that

of the more homogeneous particleboards and fiberboards. Twelve

regressions fell in category 4, significant lack of fit and low R

2

. A better fit

3
may be possible for these regressions, but again the data are scattered and not worthy of a model more

elaborate than that of the hyperbolic

equation.

Hyperbolic Model for

Degradation

The aging behavior of bonded wood

products frequently is characterized

by a rapid initial property loss (occasionally gain), a transition zone, and a

prolonged linear rate of loss (occasionally gain) for the major portion of

the life of the product. These stages

of degradation are evident in the

plots of the fitted equations shown in

figures 1 through 8.

The hyperbolic model provides a

coefficient descriptive of each stage

in the aging process. The AO term of

the hyperbolic equation is related to

the rapid initial property change; its

size reveals both magnitude and

direction of initial change. The A,

term describes transition from the

fast initial rate to the slower prolonged rate; its size indicates the

abruptness of the transition and its

sign, the direction of change. A large

A, coefficient indicates a gradual

transition. A positive coefficient indicates the curve is concave upward.

The A, coefficient describes the

slower rate of property change during

the major portion of a material’s serviceable life; a negative A, coefficient

indicates the property is decreasing.

Variability of Regression

Equations

The standard deviations of the fitted hyperbolic equations are listed in

tables 10 and 11. The fitted equations

for plywood (P) and solid wood

specimens (W and X) generally had

the largest standard deviations for

mechanical properties among all of

the boards and the lowest standard

deviations for thickness swelling. The

high variability of mechanical properties should be expected from the

variability of size and distribution of

solid wood defects. The low standard

deviation for thickness swelling

should be expected from the higher

degree of bonding in solid wood than

in reconstituted wood panels. In most

cases the fitted equations for hardboard mechanical properties had

small standard deviations. They were

consistently smaller than were the

standard deviations for particleboards

after the vacuum-pressure, soak-dry

treatment. However, the difference

was less pronounced after the boildry treatment. The smaller standard

deviations for hardboard might be expected because of small size and

homogeneity of defects in the hardboards. Among the mechanical properties, MOE had the lowest average

standard deviation (7.47 pct in boildry; 7.14 pct in soak-dry) for all

boards. (Standard deviations for

thickness swelling equations were by

far lower, but they are not comparable because the equations for

thickness are based on the percent of

swelling that never exceeded 30 percent, whereas the equations for

mechanical properties are based on

percent remaining that varied from

about 100 to 30 percent.) Equations

for internal bond strength had the

highest average standard deviations

(13 pct) for all boards.

Change of Properties After

80 Cycles of Aging

Figures 9 through 16 (computer

histograms) show the initial values of

three mechanical properties and the

magnitude of the changes in the properties caused by 80 cycles of boil-dry

or soak-dry treatment. Examination of

the histograms reveals the best performing flakeboards and hardboards

are comparable to plywood for MOR

retained after 80 cycles of the aging

treatment. However, they are less

comparable for MOE retained. The

best performing flake and hardboards

retain their internal bond strength as

well as or better than does plywood,

and surprisingly, better than solid

Douglas-fir in the soak-dry treatment.

The thickness swelling of the best

performing hardboards compares

favorably to swelling of solid wood

and plywood, especially in the soakdry treatment.

Hardboards U and V were initially

slightly thinner than were boards S

and T and the flakeboards, but the

specific gravities, or densities, of

boards U and V, at 0.89 and 0.83,

were significantly higher than were

boards S and T and most flakeboards;

none of the flakeboards exceeded

0.71 specific gravity (table 1). It would

be reasonable to think boards U and

V might swell more than would the

other materials, on the contrary, they

swelled less. Boards U and V probably had a higher resin content or

bonding conditions were better.

Effect of Aging Treatments

on Degradation Rate

Inspection of figures 1 through 8

shows that the boil-dry treatment

caused slower rates of degradation

as indicated by the A, coefficient

than did the vacuum-pressure, soakdry treatment and that rates among

the various boards were more uniform

in the boil-dry treatment than they

were in the vacuum-pressure, soakdry. This is summarized in table 12,

which shows that generally the

degradation rates for mechanical

properties were approximately 1.5

times greater in the vacuum-pressure,

soak-dry treatment than they were in

the boil-dry. Secondly, the coefficients of variation of the degradation

rates range from 1.2 to almost 4

times greater in the vacuum-pressure,

soak-dry treatment than in the boildry. No difference is apparent in the

means of the rates of thickness swelling between the treatments; however,

the coefficients of variation of rates

of the vacuum-pressure, soak-dry

treatment are again about twice

those of the coefficients of variation

of the boil-dry.

Carroll reported differences in effects between boil-dry and cold-water

soak-dry treatments on phenolicbonded plywood (4). One difference is

attributed to completion of cure of

undercured phenolic adhesives in the

boil-dry treatment compared to no further cure in the soak-dry treatment. If

all bonds reach complete cure by boiling, then degree-of-cure is removed as

a cause of variability among the

various products. Differences in

amount of rapid initial loss are probably caused by differences in degreeof-cure and residual internal stresses

from bonding. After these factors

have been equalized by the first boildry cycle, the degradation proceeds

at a uniform rate with small differences caused by species, adhesive

formulation, particle size, and board

density.

Large differences in amount of

rapid initial loss are also apparent

after the first cycle of the vacuumpressure, soak-dry treatment, but

because elevated temperature is not

part of the treatment, differences in

adhesive cure among boards remain

during the entire exposure. This must

account for the great differences in

degradation rates (A, coefficients)

noted in the vacuum-pressure, soakdry treatment.

4
Comparison of ASTM

D-1037 with Boil-Dry and

Soak-Dry Treatments

In figures 1, 2, 5, and 6, values of

MOR and MOE retained after the

ASTM D-1037 exposure are plotted on

the corresponding boil-dry and

vacuum-pressure, soak-dry degradation rate curves. The dangers of the

ASTM test not providing any indication of the rate of degradation can be

seen in the figures. It is evident some

degree of correspondence exists between the MOR or the MOE retained

after ASTM exposure and the other

cyclic exposures. However, very little

correspondence is seen in the number of cycles to produce the same

amount of degradation. For example,

figure 2 shows only two boil-dry

cycles of board U were required to

produce a loss of MOR equivalent to

the loss caused by the six-cycle

ASTM exposure. By contrast, 65 boildry cycles of board B were required to

produce loss equivalent to that in the

ASTM exposure. Furthermore, misleading conclusions can be drawn by

assuming a board with a higher retention after the ASTM test will last

longer than a board with a lower

retention. The danger is not knowing

each board’s current degradation rate

and position on the curve. For example, in figure 2, board Z has a higher

ASTM retention than board L, but the

board Z ASTM value is far to the right

and its degradation rate is faster;

therefore, it will certainly reach zero

strength before board L does. (A fair

assumption is that respective rates

will remain constant in late stages of

degradation.) Similar examples are

boards S and B in figure 5 and boards

0 and S in figure 6.

These results demonstrate that a

test such as the ASTM D-1037

accelerated-aging test (or WCAMA

test 6.1) can be useful for quality control but this type of test should never

be assumed to predict long-term performance of exterior-type board products.

Conclusions

1. A simple hyperbolic equation,

Y = AO + A1X + A2/X, provides a

useful model for change in bending

strength, modulus of elasticity, internal bond strength, and thickness

swelling of panel products exposed to

boil-dry or vacuum-pressure, soak-dry

cycles (Y = property, X = number of

cycles).

2. Degradation of most panel products is characterized by a rapid initial change in a property followed by

transition to a much slower linear

degradation.

3. Test data for hardboards were

generally the least variable and gave

the best fit to the model equations.

Data for plywood and solid wood

were consistently the most variable,

and gave the poorest fit to all equations.

4. Long-term degradation rates

from boil-dry exposures were much

more uniform among all materials

tested than were rates from vacuumpressure, soak-dry exposures. The

conclusion was the difference was

caused by removal of the degree of

resin cure as a source of variability in

the boil-dry test.

5. The best performing hardboards

and flakeboards retained percentages

of original properties after 80 cycles

of exposure comparable to the

percentages retained by plywood.

Although the actual flakeboard and

hardboard property values were lower

than were those for plywood (or

higher for thickness swelling), the

data indicate some flakeboards and

hardboards should perform very well

in long-term exterior applications.

Table 1 .—Properties of unexposed boards (average)

Specific Thick. Bending Bending Internal

gravity ness strength bond stiffness strength

Board Material

-------------------------------------------------------------------------------------------------------

A

B

C

D

F

L

O

P

S

T

U

V

W

X

Z

Laboratory flakeboard

Laboratory flakeboard

Commercial waferboard

Commercial overlaid

particleboard1

Three layer commercial

flakeboard1

Laboratory flakeboard

Laboratory flakeboard

Douglas-fir plywood

Commercial hardboard2

Commercial hardboard2

Commercial hardboard2

Commercial hardboard2

Douglas-fir lumber

Southern pine lumber

Commercial flakeboard1

0.64

.61

.60

.56 .64

.70 .53

.63 .54

.62 .52

.47 .48

.71 .45

.66 .41

.89 .39

.83 .39

.48 .50

.52 .50

.65 .54

In.

0.51

.52

.53

Lb/in.2Lb/in.2

4,930 677,000

3,800 608,000

2,660 508,000

1,570 260,000

6,580 997,000

4,590 711,000

4,890 670,000

6,660 965,000

3,020 351,000

2,490 419,000

6,370 566,000

4,390 424,000

14,350 2,007,000

16,180 1,990,000

5,210 799,000

Lb/in.2

164

83

69

74

112

107

125

127

48

21

347

346

372

612

125

1

 Results from first investigation but were not in the earlier report (2).

2

 New boards included in this investigation.
Table 2.—Regression equations percent MOR (modulus of rupture) retention versus

number of cycles of boll-dry treatment

Equation1 coefficients ANOVA “F” test2

Board A0 A1 A2 Regression Lack of fit R

2

-------------------------------------------------------------------------------------------------------------------------

A

B

C

D

F

L

O

P

S

T

U

V

W

X

Z

63.6

52.0

35.7

59.7

60.8

52.8

50.6

88.8

52.4

55.2

70.3

81.7

107

87.5

59.0

-0.275 + 12.3

-.259 + 12.3

- .231 + 20.2

- .182 + 18.6

- .183 + 11.1

- .182 + 5.04

- .171 + 10.6

- .308 + 0.333

- .343 + 16.6

- .253 + 8.31

- .185 + 17.7

- .217 + 10.7

- .323 - 9.32

- .226 + 11.2

- .181 + 10.1

**

**

**

**

* *

**

**

**

**

**

**

**

*

**

**

NS

*

NS

*

NS

NS

NS

*

NS

NS

*

NS

NS

NS

0.70

.50

.64

.45

.50

.43

.58

.35

.69

.81

.80

.60

.23

.38

.57

1

 y^ = A0 + A1X + A2 1/X.

2

 *, Error caused by lack of fit is significant at 95 pct level of confidence; **, error caused by lack of fit

is significant at 99 pct level of confidence; and NS, error caused by lack of fit of model to data is significant compared to error attributed to pure error; model is adequate. (Further explanation in Data Analysis

section of text.)

Table 3.—Regression equations percent MOE (modulus of elasticity) retention versus

number of cycles of boil-dry treatment

Equation1 coefficients ANOVA “F” test2

Board A0 A1 A2 Regression Lack of fit R

2

-------------------------------------------------------------------------------------------------------------------------

A 62.7

B 49.6

C 35.6

D 57.8

F 54.9

L 61.6

O 51.0

P 96.7

S 46.9

T 39.2

U 53.6

V 68.7

W 98.1

X 94.9

Z 55.7

- 0.234 + 3.29

- .193 + 9.80

- .263 + 16.5

- .157 + 12.3

- .124 + 12.0

- .255 -4.80

- .124 + 8.74

- .069 -1.04

- .327 + 12.0

- .218 + 9.64

- .178 + 20.8

- .177 + 11.3

- .028 + 2.25

- .064 + 0.337

- .351 + 10.3

* *

* *

* *

* *

**

*

**

NS

**

**

**

**

NS

NS

**

* *

**

**

NS

NS

 **

NS

NS

**

**

NS

**

NS

NS

NS

0.63

.60

.80

.47

.61

.26

.50

.03

.61

.86

.86

.64

.02

.02

.82

1

 y^ = A0 + A1X + A2 1/X.

2

*, Error caused by lack of fit is significant at 95 pct level of confidence; **, error caused by lack of fit

is significant at 99 pct level of confidence; and NS, error caused by lack of fit of model to data is significant compared to error attributed to pure error; model is adequate. (Further explanation in Data Analysis

section of text.)
Table 4.—Regression equations percent IB (internal bond strength) retention versus

number of cycles of boil-dry treatment

Board

Equation1 coefficients ANOVA “F” test2

A0 A1 A2 Regression Lack of fit R

2

-----------------------------------------------------------------------------------------------------------------------------------

A

B

C

D

F

L

O

P

S

T

U

V

W

X

z

58.2 - 0.269

27.7 - .248

12.2 - .138

47.4 - .320

52.8 - .352

50.3 - .331

48.2 - .303

98.9 - .718

44.3 - .293

70.3 - .426

13.0 - .028

27.7 + .067

86.5 - .416

97.5 - .712

29.8 - .362

+ 34.5

+ 24.2

+ 20.1

+ 0.356

+ 40.2

+ 27.4

+ 22.9

- 3.29

+ 30.7

- 6.52

+ 6.48

+ 11.5

- 14.2

- 9.68

+ 11.9

**

**

**

NS

**

**

**

**

* *

**

NS

NS

*

**

**

NS

NS

**

NS

NS

NS

NS

NS

NS

NS

NS

* *

NS

NS

NS

0.69

.66

.55

.19

.53

.65

.82

.40

.72

.81

.08

.11

.21

.45

.48

1

 y^ = A0 + A1X + A2 1/X.

2

 *, Error caused by lack of fit is significant at 95 pct level of confidence; **, error caused

by lack of fit is significant at 99 pct level of confidence; and NS, error caused by lack of fit

of model to data is significant compared to error attributed to pure error; model is

adequate. (Further explanation in Data Analysis section of text.)

Table 5.—Regression equations percent thickness increase versus number of cycles of

boil-dry treatment

Equation1 coefficients ANOVA “F” test2

Board A0 A1 A2

Regression Lack of fit R

2

-----------------------------------------------------------------------------------------------------------------

A 15.8 + 0.018 - 2.51

B 25.4 + .008 - 4.82

C 27.0 + .191 - 9.26

D 14.5 + .009 - 4.32

F 16.6 + .030 - 2.80

L 22.0 + .001 - 2.32

0 27.2 - .015 - 7.76

P 3.19 + .003 - .563

S 16.0 + .145 - 3.58

T 18.3 + .067 + 1.43

U 11.1 - .005 - 5.59

V 5.31 + .012 - 2.52

W 1.47 - .005 - .713

X 1.53 + .013 - .548

Z 22.5 - .013 - 4.04

* *

**

**

**

**

NS

**

NS NS

**

**

**

**

NS

NS

**

NS

NS

NS

NS

NS

NS

**

*

NS

NS

* *

NS

NS

NS

0.41

.37

.66

.64

.36

.12

.57

.07

.71

.35

.49

.29

.14

.11

.47

1

 y^ = A0 + A1X + A2 1/X.

2

 *, Error caused by lack of fit is significant at 95 pct level of confidence; **, error caused

by lack of fit is significant at 99 pct level of confidence; and NS, error caused by lack of fit

of model to data is significant compared to error attributed to pure error; model is

adequate. (Further explanation in Data Analysis section of text.)
Table 6.—Regression equations percent MOR (modulus of rupture) retained versus number

of vacuum-pressure, soak-dry treatment

Equation1 coefficients ANOVA “F” test2

Board A0 A1 A2 Regression Lack of fit R

2

-------------------------------------------------------------------------------------------------------------------------

A

B

C

D

3

F

3

L

0

P

S

T

U

V

W

X

3

Z

68.7 - 0.323

76.6 - .862

64.8 - 1.05

— —

9.91

- 10.1

7.94

—

0.36

.22

.70

—

—

64.5

70.6

76.0

50.1

32.8

67.7

77.6

100

— —

- .479 -3.47

- .68? -3.50

- .120 12.3

- .061 23.7

- .306 37.7

- .109 20.5

- .135 4.16

- .059 -1.48

—

- .115

—

8.26

—

.24

.50

.29

.85

.96

.78

.35

.O

—

.27

* *

**

NS

**

**

**

NS

—

**

—

*

*

NS

NS

* *

—

—

NS

NS

NS

NS

*

NS

NS NS

—

NS

—

*

—

57.1

1

 y^ = A0 + A1X + A2 1/X.

2

 *, Error caused by lack of fit is significant at 95 pct level of confidence; **, error caused

by lack of fit is significant at 99 pct level of confidence: and NS, error caused by lack of fit

of model to data is significant compared to error attributed to pure error; model is

adequate. (Further explanation in Data Analysis section of text.)

2

 No data.

Table 7.—Regression equations percent of MOE (modulus of elasticity) retained versus

number of vacuum-pressure, soak-dry treatment

Board

Equation1 coefficients ANOVA “F” test2

A0 A1 A2 Regression Lack of fit R

2

----------------------------------------------------------------------------------------------------------------------------------------------

A

B

C

D

3

F

3

L

O

P

S

T

U

V

W

X

3

Z

66.1 -0.376

55.5 - .268

58.5 - .775

— —

— —

62.0 - .413

71.5 - .680

85.1 - .179

43.5 - .120

28.1 - .411

51.8 - .179

62.9 - .035

107 - .037

—

55.5

—

- .198

—

1.89

- 4.86

13.6

22.3

34.7

31.7

12.6

- 2.98

13.2

9.46

16.4

—

—

11.1

—

**

**

**

**

**

**

**

* *

* *

**

—

**

**

**

NS

—

NS

NS 0.62

NS .38

NS .73

— —

—

*

* *

NS

—

.36

.66

.38

* .73

.97

.87

.59

.02

—

.61

NS

—

**

1

 y^ = A0 + A1X + A2 1/X.

2

 *, Error caused by lack of fit is significant at 95 pct level of confidence; l *, error caused

by lack of fit is significant at 99 pct level of confidence; and NS, error caused by lack of fit

of model to data is significant compared to error attributed to pure error; model is

adequate. (Further explanation in Data Analysis section of text.)

3

 No data.

a
Table 8.—Regression equations percent IB (internal bond strength) retention versus

number of cycles of vacuum-pressure, soak-dry treatment

Board

Equation1 coefficients

A0 A1 A2

ANOVA “F” test2

Regression Lack of fit R

2

---------------------------------------------------------------------------------------------------------------------------

A 75.7

B 56.2

C 40.1

D

3 —

F

3 —

L 84.3

O 74.7

P 107

S 48.4

T 78.1

U 8.77

V 16.8

W 110

X

3 —

Z 35.5

- 0.274

- .707

- .749

—

— —

- .752 - 9.98

- .688 -6.22

- .632 -11.4

- .339 31.7

- .674 61.9

- .008 18.0

+ .155 35.9

- 1.34 - 28.5

— —

- .156 22.5

12.2

- 12.5

8.15

—

—

*

NS

NS

**

**

**

NS

**

**

—

**

NS

—

**

*

NS

NS

—

0.15

.42

.50

—

— —

NS .33

NS .23

NS .10

NS .75

NS .94

NS .90

NS .81

NS .20

—

NS

—

.55

1

 y^ = A0 + A1X + A2 1/X.

2

 *, Error caused by lack of fit is significant at 95 pct level of confidence; **, error caused

by lack of fit is significant at 99 pct level of confidence; and NS, error caused by lack of fit

of model to data is significant compared to error attributed to pure error; model is

adequate. (Further explanation in Data Analysis section of text.)

3

 No data.

Table 9.—Regression equations percent thickness increase versus number of cycles of

vacuum-pressure, soak-dry treatment

ANOVA “F” test2

Regression Lack of fit

Equation1 coefficients

Board A0 A1 A2 R

2

---------------------------------------------------------------------------------------------------------------------------

A 12.5

B 18.4

C 15.3

D

3 —

F

3 —

L 16.2

O 17.6

P 2.45

S 15.8

T 23.8

U 11.9

V 8.42

W 1.16

X

3 —

Z 17.6

+ 0.073 - 1.56 ** NS 0.51

+ .170 - 2.18   .73

+ .275 - 2.75 **  NS .54

— — — — —

— — — — —

+ .141 - 1.68 ** * * .50

+ .145 - 1.34 * * NS .58

+ .048 - 1.17 * * NS .61

+ .146 - 7.51 ** ** .49

- .001 - 15.3 ** ** .76

- .174 - 8.16 * * ** .73

- .185 - 6.12   .68

- .004 - .774 NS NS .19

— — — — —

+ .098 - 2.99 **  * .64

1

 y^ = A0 + A1X + A2 1/X.

2

 *, Error caused by lack of fit is significant at 95 pct level of confidence; **, error caused

by lack of fit is significant at 99 pct level of confidence; and NS, error caused by lack of fit

of model to data is significant compared to error attributed to pure error; model is

adequate. (Further explanation in Data Analysis section of text.)

3

 No data. 9
Table 10.—Standard deviations of y

^

 about regression line1 (boil-dry treatment)

Y

Modulus Modulus internal

Board of of bond Thickness

rupture elasticity strength swelling

---------------------------------------------------------------------------------------------------------------------------

A 7.2 5.8 12.2 1.54

B 10.5 6.5 10.0 2.52

C 9.2 6.1 9.2 5.65

D 11.6 8.4 19.1 1.29

F 8.1 5.6 20.1 2.22

L 7.4 11.2 12.5 2.35

O 6.6 6.0 7.0 2.30

P 12.3 9.9 24.3 .97

S 9.5 9.8 10.8 3.16

T 4.6 3.5 5.3 2.32

U 5.1 4.6 7.2 2.04

V 7.3 6.0 10.2 1.80

W 14.8 11.7 20.1 .54

X 12.0 13.0 20.9 1.40

Z 5.3 3.9 9.3 1.58

1

 y^ = A0 + A1X + A2 1/x.

where y = Modulus of rupture, modulus of elasticity, internal bond strength, or thickness swelling,

x = number of cycles of boil-dry treatment.

Table Il.-Standard deviations of y

^

 about the regression line1 (vacuum-pressure, soak-dry

treatment)

Modulus Modulus internal

Board of of bond Thickness

rupture elasticity strength swelling

---------------------------------------------------------------------------------------------------------

A 10.5 7.6 18.6 1.51

B 20.4 8.8 9.8 1.89

C 11.7 9.8 13.4 4.49

L 11.4 8.8 13.2 2.58

O 9.4 6.4 16.5 2.15

P 11.1 15.2 22.5 .84

S 7.2 6.2 9.2 2.36

T 3.5 3.1 8.3 3.40

U 4.8 5.4 2.4 1.55

V 4.5 4.4 6.2 1.56

W 11.5 10.5 31.6 .53

Z 7.3 5.3 9.4 9.45

1

 y^ = A0 + A1X + A2 1/x.

where y = Modulus of rupture, modulus of elasticity, internal bond strength, or thickness swelling,

x = number of cycles of boil-dry treatment.

10
Table 12.—Comparison of average and variability of degradation rates’ caused by boil-dry

and vacuum-pressure, soak-dry treatments

Standard Coefficient

deviation of variation

Mean rate

of ail

boards

Treatment

----------------------------------------------------------------------------------------------------------------

Modulus of Boil-dry

rupture Vacuum-pressure,

soak-dry

Modulus of Boil-dry

elasticity Vacuum-pressure,

soak-dry

lnternal bond Boil-dry

Vacuum-pressure,

soak-dry

Thickness

swelling

Boil-dry

Vacuum-pressure,

soak-dry

-0.235 ± 0.057 24

- .359 ± .339 94

- .184 ± .094 51

- .300 ± .245 82

- .323 ± .209 65

- .514 ± .407 79

+ .031 ± .060 200

+ .037 ± .145 392

1

 A1 coefficient of hyperbolic model (2).

11
Figure 1.—Fitted hyperbolic equations for residual modulus of rupture (MOR)

as function of number of boil-dry cycles. (ASTM D 1037 values, ( l ).)

(M 149 015)

12
Figure 2.—Fitted hyperbolic equations for residual modulus of elasticity (MOE)

as function of number of boil-dry cycles. (ASTM values, ( l ).)

(M 149 014)

12
Figure 3.—Fitted hyperbolic equations for residual internal bond strength (IB)

as function of number of boil-dry cycles.

(M 150 038)

14
Figure 4.—Fitted hyperbolic equations for residual thickness swell as function

of number of boil-dry cycles.

(M 150 036)

15
Figure 5.—Fitted hyperbolic equations for residual modulus of rupture (MOR)

as function of number of vacuum-pressure, soak-dry cycles. (ASTM values,

( l ).)

(M 149 013)

16
Figure 6.—Fitted hyperbolic equations for residual modulus of elasticity (MOE)

as function of number of vacuum-pressure, soak-dry cycles. (ASTM values,

( l ).)

(M 149 012)

17
Figure 7.—Fitted hyperbolic equations for residual internal bond strength (IB)

as function of number of vacuum-pressure, soak-dry cycles.

(M 150 037)

18
Figure 8.—Fitted hyperbolic equations for residual thickness swell as function

of number of vacuum-pressure, soak-dry cycles.

(M 150 039)

19
Figure 9.—Original modulus of rupture (MOR) and residual modulus of rupture

(MOR) after 80 cycles of boil-dry treatment.

(M 149 011)

20
Figure 10.—Original modulus of elasticity (MOE) and residual modulus of

elasticity (MOE) after 80 cycles of boil-dry treatment.

(M 149 010)

2 1
Figure 11.—Original internal bond strength (IB) and residual internal bond

strength (IB) after 80 cycles of boil-dry treatment.

(M 149 009)

22
Figure 12.—Thickness swell after one boil-dry cycle and after 80 cycles of

treatment.

(M 149 008)

23
Figure 13.—Original modulus of rupture (MOR) and residual MOR after 80

cycles of vacuum-pressure (V.P.), soak-dry treatment.

(M 149 007)

24
Figure 14.—Original modulus of elasticity (MOE) and residual MOE after 80

cycles of vacuum-pressure (V.P.), soak-dry treatment.

(M 149 006)

25
Figure 15.—Original internal bond strength (IB) and residual IB after 80 cycles

of vacuum-pressure (V.P.), soak-dry treatment.

(M 149 005)

26
Figure 16.—Thickness swell after one vacuum-pressure (V.P.), soak-dry cycle

and after 80 cycles of treatment.

(M 149 004)

27
Literature Cited

28

U.S. GOVERNMENT PRINTING OFFICE. 1981-750-027/55 2.5-29-4/81
U.S. Forest Products Laboratory.

Accelerated aging of phenolic-bonded hardboards

and flakeboards, by Bryan H. River, Robert H. Gillespie,

and Andrew J. Baker. Madison, Wis., For. Prod. Lab.,

1980.

29 p. (USDA For. Serv. Res. Pap. FPL 393).

Second in a series of investigations to establish

information base on durability of new exterior-type,

wood-based panel products.