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NBS TECHNICAL NOTE 1120

U.S. DEPARTMENT OF COMMERCE/ National Bureau of Standards

An Approach to

Improved Durability Tests for

Building Materials and Components

53

L120

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NATIONAL BUREAU OF STANDARDS

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An Approach to Improved Durability Tests

for Building Materials and Components

NATIONAL BCXajkV or atAtroAKOt LIBRABT JUL 2 5 1980

0.6 fOO

Geoffrey Frohnsdorff

Larry W. Masters

Jonathan W. Martin

Center for Building Technology

National Engineering Laboratory

National Bureau of Standards

Washington, DC 20234

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U.S. DEPARTMENT OF COMMERCE, Philip M. Klutznick, Secretary

Luther H. Hodges, Jr., Deputy Secretary

Jordan J. Baruch, Assistant Secretary for Productivity, Technology and Innovation

NATIONAL BUREAU OF STANDARDS, Ernest Ambler, Director

Issued July 1980
National Bureau of Standards Technical Note 1120

Nat. Bur. Stand. (U.S.), Tech. Note 1120, 35 pages (July 1980) CODEN: NBTNAE

U.S. GOVERNMENT PRINTING OFFICE

WASHINGTON: 1980

For sale by the Superintendent of Documents, U.S. Government Printing Office, Washington, D.C. 20402

Price $2.25

(Add 25 percent for other than U.S. mailing)
AN APPROACH TO IMPROVED DURABILITY

TESTS FOR BUILDING MATERIALS AND COMPONENTS

Geoffrey Frohnsdorff, Larry W. Masters, and Jonathan W. Martin

Structures and Materials Division

Center for Building Technology

National Engineering Laboratory

National Bureau of Standards

Washington, D.C. 20234

ABSTRACT

Durability tests usually provide relative measures of the time building

materials and components will perform their intended functions under the

expected service conditions. This is not adequate to ensure the proper selection of new building materials and components because quantitative measures

of long-term performance are needed. Although many tests have been developed

to accelerate degradation processes of building materials, they are seldom

fully adequate for reliably predicting long-term performance. In this paper,

a recommended practice, ASTM E 632-78, which provides a framework for the development of improved durability tests, is outlined. The application of the recommended practice, which does not specify an analysis procedure, is illustrated

by examples from the literature using both deterministic and probabilistic

approaches.

While probabilistic concepts have not been applied extensively to materials durability problems in the construction industry, these concepts offer

new opportunities for obtaining improved quantitative predictions of the service life of building materials.

Keywords: Accelerated aging tests; building components; building materials;

durability; life testing; prediction; recommended practice;

reliability service life.

iii

1. INTRODUCTION

New building components and systems are constantly being designed and

manufactured to satisfy the ever-growing needs of society. Many of these

components will be subjected to adverse conditions over their life and

these adverse conditions can affect their ability to perform as Intended.

Since materials are the fundamental building blocks of components and

systems, it is essential that appropriate materials be selected if the

components and systems are to perform their intended functions when

initially installed and over their expected service lives.

Building materials usually fall into one of two categories - traditional

materials and innovative materials engineered for a particular application.

With materials of either category, the operating and stress conditions to

which they will be subjected are difficult to predict; therefore, it is

difficult to predict how the materials will perform in service. It is essential that a reliable prediction of long-term performance (durability) of a

material be made, however, prior to its incorporation into a structure.

There are many definitions of durability. Two used by ASTM committees are:

Durability is the safe performance of a structure or a portion of a

structure for its expected design life. (From ASTM Standard E 241).

Durability is the capability of maintaining the serviceability of a

product, component, assembly or construction over a specified time

(From ASTM Standard E 632)

1 Stress, as used here, is any factor (mechanical, thermal, environmental, or biological) which causes a material to degrade over time.

1
where serviceability is the capability of a building product, component,

assembly or construction to perform the function(s) for which it is

designed and constructed (from ASTM Standard E 632).

Both definitions of durability incorporate the concept of design requirements being met or exceeded for a specified period of time — usually the

design life of the system. These definitions also suggest criteria which

can be used to measure the adequacy of a particular durability analysis

procedure. The optimal procedure should:

1. Give a quantitative estimate of the time to failure of a component

or material, when it is exposed to the expected operating conditions. This estimate can be derived from either in-service performance tests or from accelerated aging tests. An accelerated

aging test is a test in which the performance of a component at

in-service stress levels is predicted from its performance at

higher than normal stress levels.

2. Give results which correlate with in-service performance.

3. Identify the degradation mechanisms causing failures at high and

low stress levels. For accelerated aging tests, this is necessary to ensure the validity of extrapolating high stress level

results to normal or low operating stress levels.

Confidence that a material or component will perform as expected for a

specified time is essential to the designer of a building. Confidence

in the performance of traditional materials in the normal range of environments can be based on past experience, but it is difficult to establish the same confidence in the performance of innovative materials, or

2
of traditional materials in environments outside the normal range of

experience, e.g., solar and nuclear energy applications. However, unless

methods for providing the confidence at an acceptable cost can be established, a severe barrier to innovation will continue to exist. Marshall

and Ruegg [1] , for example, point out that a major impediment to calculating life cycle costs and savings is that such calculations require lifecycle data on performance, durability, and dependability which is seldom

available.

Interest in the prediction of durability is not new and it is not confined

to the building industry. The importance of predicting durability has

grown rapidly but, unfortunately, the state of durability testing is disorganized as has been pointed by Masters et al. [2]. Although many

durability tests are described in standards and specifications for building materials [3], there is seldom a fully satisfactory way of correlating,

with each other or with in-service performance, the results of laboratory

tests on different materials. The increasing pressures for innovation in

the building industry increase the need for development of a systematic

approach to evaluation of durability. This need is indicated in the proceedings of the joint RILEM-ASTM-CIB Symposium on the Performance Concept

in Buildings [4].

The following shortcomings of standard durability tests can be highlighted:

1. Methods are not usually provided for correlating laboratory

results with in-service results.
2. Provisions are usually not made for taking into account different

applications of a material or component,

3. In the laboratory, materials and components are usually tested

in configurations far different from in-service configurations,

making correlations between accelerated aging tests and inservice performance uncertain,

4. Recommendations are seldom made as to how the results of standard tests for different materials should be compared with each

other.

5. Quantitative estimates of time to in-service failure are seldom

made. The reason is that most standard durability tests are

comparative tests; that is, the experimental procedure only

allows for the comparison of the durability of an unknown

material or component against the performance of a reference

material or component, both exposed to identical stresses,

6. The degradation mechanisms of materials and components

are complex and not well understood so that it is difficult

to design meaningful accelerated tests.

7. The factors affecting service life are numerous, as indicated in

2 Table 1, and difficult to quantify. Thus, many existing tests do

not include all factors of importance and factors that are included

are seldom related quantitatively to in-service exposure conditions.

Due to the deficiencies in the current technology of durability testing,

ASTM subcommittee E 6.22 was formed in 1974 to provide a more general and

2

Table 1 is located at the end of this report, on page 29.
improved approach to durability testing. Specifically, its purpose was "the

development of methodologies, the dissemination of knowledge, and the stimulation of research relating to the prediction of the service life of building

components, and the demonstration of compliance with durability performance

requirements". The work of the subcommittee recently led to the publication

of the Recommended Practice for Developing Short-Term Accelerated Tests for

Prediction of the Service Life of Building Components and Materials, ASTM

E 632-78, which is based upon National Bureau of Standards (NBS) research.

The practice outlines the process of developing tests to predict the service

life of a building material or component from the results of short-term tests.

In making a prediction of the time to failure, the procedure emphasizes the

necessity of knowing as much as is practical about the nature of the item

and the service conditions, e.g., material degradation mechanisms and in-service

exposure conditions. It leaves open, however, the details as to which tests

should be used and and how the information should be analyzed.

In durability evaluation, the procedures used to measure degradation and

to analyze the durability data are very important, for durability

research is expensive in terms of money, time, equipment and space, and

seldom yields more than a small amount of data. There are two classes

of procedures for determining in-service life — deterministic (e.g.

,

i fracture mechanics) and probabilistic (e.g., reliability). In reality,

the separation is not distinct, for deterministic procedures often use

statistical methods for analyzing their data and probabilistic procedures

often use a materials justification in selecting a life distribution.
The obvious advantage in using a deterministic procedure is that the problem is addressed In terms of material parameters. Unfortunately, few,

if any, have been successful in modeling the durability of a material.

One possible reason for this failure is that deterministic procedures usually

model a material in terms of one failure mechanism whereas, in fact, failures

over time are usually the result of several time-dependent failure mechanisms

[5] . Also, failure mechanisms which cause time-dependent failures are difficult to identify, for the failure is thought to be initiated at the microscopic

or submicroscopic level. The inability to observe the initiation of failure

and to predict the time of failure for a stressed material led to the belief

that durability research could be analyzed in terms of random events [6, 7];

hence the use of probabilistic procedures. The basis for this is the observation that two or more specimens, which appear to be identical, can have failure

times which are several decades apart, even though they are subjected to the

same stress and operating conditions. The analysis of such random events is

within the domain of probabilistic procedures, especially those which address

the problem in terms of the material parameters.

2. THE REC0^D^1END£D PRACTICE FOR DEVELOPMENT OF ACCELERATED SHORT-TERM

TESTS FOR THE PREDICTION OF SERVICE LIFE

The recommended practice for developing short-term tests for the prediction of service life described in ASTM E 632 is summarized by the chart

in Figure 1. The chart indicates a sequence of steps which we recommend

be undertaken in developing and applying tests for predicting the service

lives of innovative building materials or components; or existing ones

which are to be used under conditions outside their normal ranges.
For convenience, the practice is divided into four parts: 1) Problem

Definition; 2) Pre-Testing; 3) Testing; and 4) Interpretation and Reporting

of Data. In Part 1, referring to the numbered boxes in the chart, the

first step (step 1) is to define the performance requirements to be met

by the material or component in service and to set minimum requirements

the material or components must meet to be judged serviceable. These

criteria provide an objective basis for recognizing when failure has

occurred. It should be noted that the failure criteria for a material

can change with the application. In step 2, if the material or component

is not homogeneous, it should be characterized as thoroughly as possible

in terms of the individual materials contained within it and the interfaces between the individual materials. This information is important

for gaining insights into the possible degradation mechanisms so that the

most appropriate tests can be selected. It should be noted that, because

of synergistic effects, composites can have durabilities and properties

far different from those of the constituents. The critical performance

characteristics are specified in step 3; these characteristics will be

used in delineating the limiting condition below which the material or

component is deemed unserviceable. In step 4, the expected range of degradation factors, including weathering, biological, stress, incompatibility and use factors, should be identified to help define the conditions

to which the material or component is likely to be exposed in service.

Synergistic effects between degradation factors can be identified. With

this knowledge it may be postulated (step 6) how the degradation processes

can be accelerated. If degradation processes can be accelerated without

changing the mode of failure, then laboratory test time can be reduced.

7
Once the experimental procedure has been determined, the performance requirements for the test specimens should be stated (step 7). It must be recognized

that much of the knowledge desired may not always be available. In such

cases, assumptions based on the best available experience should be made

and recorded.

When Part 1 is completed, Part 2, Pre-testing, can be initiated (step 8

3

in Figure 1). Its purpose is to demonstrate that rapid failures can be

caused by intensifying the degradation factors specified in Part 1 . These

preliminary experiments provide the background for Part 3 which begins with

the establishment of more realistic accelerated aging tests (step 9). These

accelerated tests should be conducted at different stress • levels . At the

same time (step 10), long-term tests under in-service conditions should be

initiated. The results of long-term tests provide the most convincing evidence that the results of accelerated aging tests can be extrapolated to

in-service conditions. They are important in insuring that second order

effects are not causing the failure at low stress levels. If second order

effects appear to be causing the failures, then the accelerated test conditions should be reviewed to determine whether factors which accelerate second

order effects are too severe or whether important degradation factors have

been omitted.

If the results of the accelerated tests and the long-term tests are consistent with each other. Part 4, Interpretation and Reporting of Data, can be

undertaken. This includes use of experimental data to predict the course

of degradation under expected in-service conditions (step 13) and to predict

the time at which failure, as defined by the performance criteria, will

The figures are located at the end of this report, beginning on page 30,
occur (steps 14 and 15). The performance criteria for failure in the

predictive service life tests may differ from those of the in-service tests

because of different specimen configurations and nonlinearity of response

to degradation factors. The practice concludes with the reporting of data

(step 16) in which, it must be emphasized, all assumptions should be made

clear.

The ASTM recommended practice recognizes that:

° Although it is desirable to have complete data on the material or

component, the conditions to which it is to be exposed and the

degradation mechanisms, assumptions about these will often have to

be made to keep within the constraints imposed by time and funding.

" The predicted service life of a material or component will depend

upon the range and intensity of the degration factors to which it

is exposed in service and the choice of the failure criteria.

° Because possible errors in the predictions can vary widely, it

is important that possible sources of error should be identified

and an attempt made to assess their magnitude.

As an aid to the application of the recommended practice, the attention of

the user is drawn to a list (Table 1) of degradation factors which may

I affect the performance of building materials and components. In any application, it is recommended that a matrix, similar to that in Figure 2, be

made to aid in identifying properties of importance.
3. EXAMPLES TO ILLUSTRATE THE APPLICATION OF THE RECOMMENDED PRACTICE

The recommended practice is independent of the analysis procedure, i.e., it

provides a framework for analysis. The two broad classes of analytical

procedures — deterministic and probabilistic — both readily adapt to the

format of the recommended practice. The two procedures differ in how they

obtain an answer to the basic question asked of durability test results.

Before differentiating between the two procedures, however, an understanding

of the questions that durability tests should answer must be developed.

As mentioned in the introduction, the procedure used to analyze the durability test results should have several attributes. It is particularly important

that criteria for failure be established. For most building materials

exposed to given environmental conditions, the time to failure of interest

is that time beyond which an unacceptable number (percent) of failures occurs.

For a non-critical component, for example, the user of the component might

be willing to allow ten percent of a nominal population of components to fail

prior to the expected design life of the structure. For critical components,

however, one failure in a thousand might be the maximum allowed. The difference between deterministic and probabilistic procedures lies in how the estimates of these low probable times to failure are made.

Deterministic procedures first obtain estimates of the expected time to failure under a given set of operating conditions. Once this expected time to

failure is obtained, an estimate at a low percent failure is derived by

dividing this expected time to failure by an appropriate reduction factor.

Since these reduction factors have little or no statistical significance,

the time to failure which results from their use gives only a qualitative

10
measure of assurance that few in-service failures will occur. That is to say,

reduction factors only permit the statment to be made that the probability of

an in-service failure of a component is low whereas, optimally, a statement as

to what percent of a nominal population will fail prior to a given time is

needed. A quantitative estimate gives the researcher a basis by which he can

test for a significant difference between the times to failure of two different

nominal populations of materials. Using the time to failure distribution for

a given material, reliability analysis provides a quantitative estimate of

the time at which a designated low percent of a nominal population will have

failed; hence, it provides a methodology to measure significant differences

in two nominal populations of material.

In the examples which follow, the first uses a deterministic approach and the

second uses a reliability approach. The second is not taken from the construction industry because no good examples of application of the reliability

approach are available. The third example concerns coatings and it shows how

the recommended practice will be used to aid the planning of one of our own

projects.

3.1 EXAMPLE NO.l - THE RESISTANCE OF A CONCRETE STRUCTURE TO FREEZING

AND THAWING

The first example of a possible application of the ASTM recommended practices

is based on a portion of a paper by Plum, Jessing, and Bredsdorff [8]. It

emphasizes understanding the degradation mechanisms and the development and

application of mathematical models. The procedures used by the authors follow

closely the steps prescribed in the recommended practice. Their case was a

hypothetical one in which a specific concrete structure would be exposed to

freeze-thaw cycles.

11
The implicit objective of the study was to determine the expected life for

each element of the structure. Referring to the steps of Figure 1, our

interpretation of their approach is as follows.

Step 1 . Performance Requirements and Failure Criteria - The requirement for

any element is that the concrete strength should be adequate for the structure to perform as intended. The failure of an element occurs when the

strength of the element falls below an acceptable value.

Step 2 . Characterization of the Material(s) - The chemical, physical, and

macro- and micro-structural characteristics of the material are determined

from the known ingredients of the concrete, the mix design, and the curing

conditions

.

Step 3 . Critical Performance Characteristics - The critical performance

characteristic for each element is the compressive strength. The compressive

strength can be used as an indicator of degradation.

Step 4 . Expected Type and Range of Degradation Factors - The only degradation factor considered is the freezing of water-saturated concrete. Much

information is needed about the range of temperatures, including minimum

temperature, frequency of freeze-thaw cycles, rates of cooling, and duration

of periods below 0°C, but this can be obtained, or estimated, from meteorological data.

Step 5 . Possible Degradation Mechanisms - The only degradation mechanism

judged to be important is fatigue resulting from internal stresses associated

with the cyclic freezing and thawing of water within the pores of the concrete.

12
Step 6 . Postulate Methods of Causing Accelerated Aging Similar to Aging in

Service - Carry out frequent freezing and thawing of concrete with a high

degree of water saturation.

Step 7 . Performance Requirements for Predictive Service Life Tests - The

predictive tests should produce a loss of strength of the concrete by the

same mechanism as observed in actual service. The tests should yield

results in relatively short times and the severity of the test conditions

should be able to be changed easily to facilitate study of the effects

of changing the conditions.

Step 8. Design and Perform Predictive Tests to Cause Rapid Failure and

Confirm Degradation Mechanisms - Using temperature changes from meterological data as a guide, concrete specimens with saturation coefficients,

S, greater than 0.92 are subjected to rapid cooling freeze-thaw cycles.

The loss of strength is measured as a function of the number of -freezethaw cycles.

Step 9 . Extend the Tests of Step 8 to Less Severe Conditions to Establish

the Relationships Between Severity of Conditions and Rate of Degradation -

Keeping S above 0.92, lower the frequency of cycling and lower the cooling rates. Tests with values of S less than 0.92 were judged to be

unnecessary because of previously published evidence that freeze-thaw

damage is negligible at lower S values.

Step 10 . Long-Term Tests Under Service Conditions - Long-term tests are

not mentioned by Plum et al. They appeared to believe that, from the

results of accelerated tests carried out under a wide range of conditions,

13
a performance model could be developed which would be satisfactory in

predicting behavior under all likely circumstances. Also, prior experience on the freeze-thaw behavior of concrete and information in the literature can help in assessing the realism of the accelerated tests. (In

our view, long-term tests should almost always be started even though it

is uncertain whether they will give much information in the time available) .

Step 11 . Compare the Types of Degradation Obtained in Service and in the

Predictive Service Life Tests - Such a comparison is not mentioned explicitly. However, the authors discuss procedures for extrapolating the

results of accelerated tests to in-service conditions.

Step 12 . Is the Degradation Obtained in the Predictive Tests of the Same

Nature as in the In-service Tests? - This is not commented upon explicitly but it is clear the authors believe that their proposed experiments

could meet this condition.

Step 13 . Develop Mathematical Models of Degradation and Compare the

Rates of Change in Predictive Tests with In-service Tests - The authors

believe that the complex mechanistic models they outline could be developed to cover the whole range of likely exposure conditions using the

data obtained from the predictive tests of steps 8 and 9. (The authors

noted that the models would have been too complex to use with the computers available to them at the time this research was performed).

Step 14 . Performance Criteria for Predictive Service Life Tests - The

criterion for failure appears to be the same as for in-service tests (see

step 1).

14
Step 15. Predict Service Lives - The models from step 13 should be

applied to each portion of the concrete structure to predict the time

to failure under typical exposure conditions as defined in step 4.

Step 16 . Report the Data - The authors do not comment on the reporting

of the data or on the importance of stating the assumptions and the

estimates of error. (If studies such as those they describe were actually carried out, it would, of course, be essential to comment on the

reliability of the predictions and state the assumptions and approximations made so as to minimize the possibilities for misunderstanding)

.

It may be inferred from this example that the prediction of service

life may be very complicated if knowledge (or assumptions) about the

details of degradation processes is to be incorporated in a mathematical

model. The need for such a model was lessened in the case of Example

1 because of the possibility of confirming directly that the accelerated

tests caused degradation similar to that observed in the long-term tests.

We consider it axiomatic that predictions of service life should be based

on the best possible knowledge of the degradation mechanisms of the

objects in question and the environments to which they are likely to be

subjected.

3.2 EXAMPLE NO. 2 - STATISTICAL ANALYSIS OF THE FATIGUE LIFE OF DEEPGROOVED BALL BEARINGS

The second example selected to demonstrate the applicability of the recommended practice is from one of the first published papers using reliability theory to solve a practical problem [9]. It concerns ball bearings.

We would have liked to have been able to use an example from building

15
materials technology but we do not know of any which is satisfactory for

our purpose.

The objective of the study, which was carried out by Lieblein and Zelen, was

to determine the dynamic capacity for a nominal population of deep-grooved

ball bearings. Dynamic capacity is the load at which 90% of the nominal

population will survive when subjected to one million stress cycles. Dynamic

capacity is used by the ball bearing industry to rate one nominal population

of ball bearings against another. Lieblein and Zelen' s task was to probabilistically analyze already available data using an accepted equation.

Using Figure 1, our interpretation of Lieblein and Zelen' s analysis is as

follows:

Step 1 . Performance Requirements and Failure Criteria - The function of

ball bearings is to prevent machine parts from deviating from a desired

direction. Failure of a ball bearing usually results from ball bearing

fatigue, the incipient stage is the formation of a fatigue crack. Failure

occurs when a crack propagates and a piece of the race or ball spalls out.

For this study, all ball bearing failures were assumed to have occurred in

this way.

Step 2 . Characterization of the Material - The dynamic capacity for a

nominal population of ball bearings is a function of the following factors: the number of balls, the diameter of the balls, the number of

rows of balls, the angle at which the balls are stressed (the contact

angle), the type of material used (balls, raceway, and cage), the type

of metal processing, and finally, the type of lubricant.

16
Step 3 . Critical Performance Characteristics - The characteristic used

to measure the failure of a ball bearing was either total failure of the

ball bearing causing spalling out or a change in the performance of the

ball bearing (increased friction or excessive horsepower).

Step 4 . Expected Type and Range of Degradation Factors - Some of the

factors which tend to reduce the life of a nominal population of ball

bearings are the applied load, the type of loading (uniform or nonuniform), the speed at which the bearings revolve, and the operating

temperature. The range for each of these factors must be determined

from expected in-service operating conditions.

Step 5 . Possible Degradation Mechanisms - Deep grooved ball bearings

can fail from wear-out or lubrication failure. As Burwell [10] points

out, wear-out can be classified into four categories — adhesive or

galling wear, abrasive or cutting wear, corrosive wear, and surface

fatigue. For this study, all failures were considered to be fatigue

failures.

Step 6 . Postulate Methods of Causing Accelerated Aging Similar to Aging

in Service - Unlike many other industries manufacturing materials or systems,

the ball bearing industry has extensive empirical information on the fatigue

lives of ball-bearings. From this data an equation showing the interrelationships between the factors influencing the life strengths of ball-bearings

was developed. This equation, called the Lundberg-Palmgren equation, is

expressed [9] as

17
( ^1ai 32 a3 p

4 (1)

fpZ D (i cos a)

where

Z = number of balls

D = ball diameter

i = number of rows of balls

a = contact angle

P = bearing load

L = number of revolutions that a specified

percent of bearings will fail to survive when

subjected to fatigue

and p, a-i , ao > ao , and f are unknown parameters. Since a = 0° for

deep grooved ball bearings, the above formula is greatly simplified.

Life tests for ball bearings are usually accelerated by an increase in

the applied load. Other methods which have been used to accelerate life

tests include changes in the lubricant and changes in the operating speed.

Step 7 . Performance Requirements for Predictive Service Life Tests -

Historically, time to failure data from bench tests have been shown

to be good predictors of in-service test results. These results are

usually obtained by loading the ball bearing with a known stress and then

obtaining an estimate of dynamic capacity. As Shaw and Macks [11] point

out, however, in-service tests should also be conducted.

18
Step 8 . Design and Perform Preliminary Tests to Cause Rapid Failure and

Confirm Degradation Mechanisms - Since the interrelationships between

variables was already established via Eq. 1, this step is not necessary

except when new applications are involved (e.g., ball bearings being used

in high-speed aircraft, missiles, etc.). Since new applications were not

considered, Eq. 1 was used.

Step 9. Extend the Tests of Step 8 to Less Severe Conditions to Establish the Relationships Between Severity of Conditions and Rate of Degradation or Loss of Performance - The data Lieblein and Zelen analyzed

came from four different ball bearing companies. The range of stresses

was wide enough for Lieblein and Zelen to determine the rate of degradation

at different stress levels.

Step 10 . Long-Term Tests Under Service Conditions - Lieblien and Zelen

did not carry out long-term tests under service conditions. They assumed

that Eq. 1 was correct.

Steps 11 and 12 . Compare Types of Degradation Obtained in Service and in

the Predictive Service Life Tests - The authors state that one of their

initial assumptions was that life test degradation was similar to degradation

in-service. This assumption appears to be a good one, since it is still

used [12]

.

Step 13 . Develop Mathematical Models of Degradation and Compare the Rates

of Change in Predictive Tests with In-service Tests - Lieblien and Zelen

chose the Weibull life distribution to model the life length for ball bearings

exposed to a constant stress. The choice of the Weibull distribution was

19
made because it is a limiting distribution for minimum times to failure and

because it appeared to fit the life data well.

Step 14 . Performance Criteria for Predictive Service Life Tests - Spall

out or race failure are commonly used in-service failure criteria.

Step 15 . Predict Service Lives - The authors did not do this since they

were more interested in determining the dynamic capacity of the material.

It is obvious, however, that if Eq. 1 is correct and a constant in-service

stress condition could be assumed, then the number of stress cycles such

that 90% of the specimens will survive could easily be computed for any

applied stress.

Step 16 . Report the Data - The authors explicitly state the assumptions

used in deriving their test results.

3.3 EXAMPLE No . 3 - DEVELOPMENT OF TESTS FOR CORROSION-PROTECTIVE COATING

SYSTEMS FOR STEEL STRUCTURES

The stepwise application of the recommended practice to a coating system

for protection of steel structures against corrosion [13, 14] is used as

the last example. The term "coating system" includes the surface preparation, the coating material, and the methods and environment used for

application and curing. A typical problem to be addressed is the selection, from many possible paint systems, those coating systems which will

survive, with 90% probability, fifteen or more years of in-service use.

Using the recommended practice, a possible approach includes the following steps.

20
Step 1 . Performance Requirements and Failure Criteria - The coating system

is required to protect the steel, including welds and other joints, from

rapid corrosion for 15 years in the environments to which it is to be exposed.

I One criterion of failure might be that the coating system will be considered

I

I to have failed when there is visible evidence of rusting over at least 5%

] of the surface area or over 10% of the length of welds. The exact criteria

I

I adopted will depend upon the application, but the criteria should be quantiI tative and reflect the best available knowledge and experience.

I Step 2 . Characterization of the Material (s) - The systems will consist of

\ paints of known generic types applied to prepared steel surfaces under a

range of environmental conditions. The paint films will be classified with

respect to type and volume of resin, solvent, fillers, and plasticizers

Other paint variables which will be measured include the glass transition

I temperature, molecular weight, modulus of elasticity, and paint thickness.

li Step 3 . Critical Performance Characteristics - Critical performance characteristics of the coatings are likely to be adhesive and cohesive strengths

of the film. Properties that can serve as degradation indicators are appeari ance, dielectic strengths, molecular weight change, and film modulus.

Step 4 . Expected Type and Range of Degradation Factors - Locations where the

systems are to be used should be reviewed and those with the most severe

i exposure conditions identified. The range of exposure conditions to which

I' the coatings will be subjected is determined from meteorological data.

Important degradation factors include elevated temperature, temperature

cycles, relative humidity, solar radiation, and air pollutants (including

salt spray and sulfur dioxide).

21
Step 5 . Possible Degradation Mechanisms - Loss of integrity or loss of

adhesion of the coating may result from corrosion of the steel substrate

due to migration of oxygen and water vapor through the coating or it may

result from high internal stresses. Rates of degradation in terms of

increase in permeability to oxygen and water vapor are likely to be a

function of coating thickness and coating embrittlement. Loss of adhesion

may occur due to growth of rust under the coating, particularly where the

surface was contaminated with chlorides or other salts before painting,

or where salts permeate through the coating in salt environments.

Step 6 . Postulate Methods of Causing Accelerated Aging Similar to Aging

in Service - Sets of specimens with features typical of interfaces and

joints which occur in field applications should be exposed separately to

(i) simulated solar radiation of greater intensity than would normally

be expected in-service, (ii) water, (iii) elevated temperatures, (iv)

temperature cycles and (v) acidic solutions to simulate the effects of

pollutants. Information on synergistic effects of degradation factors

should be sought through investigation of combined effects.

Step 7 . Performance Requirements for Predictive Service Life Tests -

The predictive tests should produce failure by the same mechanisms as in

service, but in a much shorter time. The tests should rank the systems

in the same order of durability as in-service exposures. The severity of

the exposure conditions should be able to be varied easily from one test

to the next.

22
Step 8. Design and Perform Preliminary Tests to Cause Rapid Failure and

Confirm Degradation Mechanisms - To confirm degradation mechanisms for

each coating system, samples should be prepared under a range of demanding conditions simulating those likely to be occur in service, e.g., painted

joints, rough surfaces or contaminated surfaces, coating of various thicknesses, and different application techniques. Specimens should be exposed

to accelerated aging conditions including ultraviolet radiation, high relative humidity, condensing moisture (with and without dissolved air pollutants), temperature aging, temperature cycling, and combinations of these.

If any experiment shows evidence of unusually rapid coating degradation, a

decision must be made as to whether to drop the system from further consideration or to carry out tests under less severe conditions as in Step 9. This

would be to determine if the severe conditions had induced degradation by a

mechanism which would not normally be important in service.

Step 9 . Extend the Tests of Step 8 to Less Severe Conditions to Establish

the Relationships Between Severity of Conditions and Rate of Degradation

or Loss of Performance - The exact conditions of test would depend upon

the rates of degradation observed in Step 8 . Emphasis would be on those

degradation factors, and combinations of factors, judged most likely to

cause failure in service.

Step 10 . Long-Term Tests Under Service Conditions - Comparison samples

of coated steels similar to those studied in Steps 8 and 9 should be placed

in outside exposures judged to be representative of those encountered inservice. Actual exposure of coatings on steel structures are useful in

determining the adequacy of the proposed models.

23
Step 11 . Compare the Types of Degradation Obtained in Service and in the

Predictive Service Life Tests - Although this comparison may not be useful

unless detectable degradation occurs in the time available for the long-term

tests, the comparison should always be made. Visual observation may be all

that is required but more careful observation with the light and scanning

electron microscopes will probably be desirable.

Step 12 . Is the Degradation Obtained in the Predictive Tests of the Same

Nature as in the In-service Tests? - The evidence from Step 11 will be

evaluated to see if, for any of the coating systems, there is any suggestion

of a difference in degradation mechanisms between the accelerated and longterm tests. For any system for which there is a difference, it is probable

that the exposure conditions in the accelerated tests were too severe to

be realistic so that the tests should be repeated under less severe conditions if the systems are still of interest. For the others. Step 13 can be

undertaken.

Step 13 . Develop Mathematical Models of Degradation and Compare the Rates

of Change in Predictive Tests with In-service tests - From the data in

Steps 8, 9, and 10, models or mathematical relationships capable of accounting

for all the available data should be developed. To the extent possible,

they should include consideration of failure mechanisms and of behavior

under individual degradation factors and combinations of factors.

Step 14 . Performance Criteria for Predictive Service Life Tests - The

performance criteria for failure in the predictive in-service life tests

will probably be similar to those for the in-service performance or longterm tests.

24
Step 15 . Predict In-service Lives - The model for each coating system will

be used to predict the service life under the various conditions of interest.

Step 16 . Report the Data - The results will be reported in as much detail as

possible with clear statements of the assumptions made and their implications

for the reliability of the service life predictions.

Systems which, according to the predictions, meet the desired performance

requirements stated in Step 1 should be identified.

The work outlined in this example would be extensive and would have to be

carefully planned to ensure that the accelerated tests simulate in-service

conditions; the plan should minimize the possibility of overlooking important

degradation factors which might adversely affect the performance of the

system.

4. SUMMARY AMD CONCLUSIONS

New materials ar.d components are constantly being introduced to help meet

societal needs. These new materials, along with more traditional materials,

f are used in applications for which little or no a priori knowledge exists

, on how they will perform in service. For this reason, there exists a need

I

J for standardized, accelerated durability tests which are capable of predicting in-service performance for a given material when used in a specified

application.

Although there are many published durability tests, they are seldom adequate

for predicting long-term performance in-service. Part of the reason for this

inability to predict in-service performance results from the use of tests

25
which have little or no bearing on the intended material application. The

framework provided by ASTM E 632 can aid in meeting the need for improved

durability test procedures. Such a framework is particularly important in

insuring that the researcher considers all aspects of the problem in designing

and carrying out research.

Although ASTM Method E 632 does not specify an analysis method, the principles

of reliability analysis have been successfully utilized in addressing a number of durability-related problems. While reliability concepts have not been

applied extensively to materials durability problems in the construction

industry, the authors conclude that the concepts offer new opportunities for

obtaining quantitative predictions of the service life of building materials.

26
5.0 REFERENCES

1. Marshall, H. C, and Ruegg, R. T., "Life-Cycle Costing Guide for

Energy Conservation in Buildings", Energy Conservation Through

Building Design, McGraw-Hill, in publication.

2. Masters, L. W. , Wolfe, W. C, Rossiter, W. J., Jr., and Shaver,

J. R., "State of the Art on Durability Testing of Building Components

and Materials", NBSIR 73-132 , National Bureau of Standards, Washington,

D.C., March 1973"!

3. Masters, L.W., Clark, E. J., Sleater, G. A., and Hockman, A.,

"Durability and Related Tests for Selected Elements and Materials Used

in the Exterior Envelope of Buildings", NBSIR 75-955 , National Bureau

of Standards, Washington, D.C. 20234, November 1975.

4. Foster, B. E. (ed.), "Performance Concept in Buldings," Proceedings of

the Joint RILEM-ASTM-CIB Symposium, National Bureau of Standards Special

Publication 361 , Volumes 1 and 2, National Bureau of Standards,

Washington, D.C, 1972.

5. Freudenthal, A. M. and Gumbel, E. J., "On the Statistical Interpretation of Fatigue Tests", Proc. Roy. Soc. (A) 1933, 216, p. 309.

6. Bolotin, U. U., Statistical Methods in Structural Mechanics. Holden Day,

San Francisco, 1969.

7. Martin, J. W. and Saunders, S. C, 1980. The relationship betwen life

test analysis and tests at constant stress ratio, in Structural Use of

Wood in Adverse Environments, Meyer, R. W. and Kellogg, R., (eds), Syracuse University Press.

8. Plum, N. M., Jessing, J., and Bredsdorff, P., "A New Approach to Testing

of Building Materials", RILEM Bulletin , New Series, No. 30, March 1965,

p. 123.

9. Lieblein, J. and Zelen, M., "Statistical Investigation of the Fatigue

Life of Deep-Grooved Ball Bearings", Research Paper 2719, Journal of

Research , National Bureau of Standards, Volume 57, Number 5: pp. 273-316,

1956.

10. Burwell, J. T., Jr., "Survey of Possible Wear Mechanisms", Wear , Volume 1,

No. 2, October 1957, pp. 119-141.

11. Shaw, M. C. and Macks, E. F., Analysis and Lubrication of Bearings .

j McGraw-Hill Book Company, Inc, 1949.

12. Bamberger, E. N., Harris, T. A., Kacmarksy, W. M. , Moyer, C. A., Parker,

R. J., Sherlock, J. J., and Zaretsky, E. V., "Life Adjustment Factors

for Ball and Roller Bearings", American Society of Mechanical Engineers , 1971.

27
13. Burns, R. M. and Bradley, W. W. , Protective Coatings for Metals , American Chemical Society Monograph No. 129, 2nd edition, Reinhold,

New York, 1955.

14. Bragdon, C. R., Film Formation, Film Properties, and Film Deteriora - tion, Interscience, Inc., New York, 1958.

28
TABLE 1. DEGRADATION FACTORS AFFECTING THE SERVICE LIFE OF

BUILDING COMPONENTS AND MATERIALS

Weathering Factors

Radiation

Solar

Nuclear

Thermal

Temperature

Elevated

Depressed

Cycles

Water

Solid (such as snow, ice)

Liquid (such as rain, condensation, standing water)

Vapor (such as high relative humidity)

Normal Air Constituents

Oxygen and ozone Carbon dioxide

Air Contaminants

Gases (such as oxides of nitrogen and sulfur)

Mists (such as aerosols, salt, acids, and alkalies dissolved in water)

Particulates (such as sand, dust, dirt)

Freeze-thaw

Wind

Biological Factors

Microorganisms

Fungi

Bacteria

Stress Factors

Stress, sustained

Stress, periodic

Stress, random

Physical action of water, as rain, hail, sleet, and snow Physical action of wind

Combination of physical action of water and wind

Movement due to other factors, such as settlement or vehicles

Incompatibility Factors

Chemical

Physical

Use Factors

Design of system

Installation and maintenance procedures

Normal wear and tear

Abuse by the user

29
PART 1 - PROBLEM DEFINITION

Define In-use perfonnance

requirements and criteria

Characterize the component or material X

Identify critical per- formance characteristics

and properties that can serve as degradation

indicators

Identify the expected type

and range of degradation

factors including those related to weathering,

biological, stress, incompatibility and

use factors

Identify possible degra- dation mechanisms

Postulate how degradation

characteristic of in- use performance can be Induced by accelerated

aging tests

Define perfonnance requirements for predictive service

life tests

PART 2 - PRE-TESTING

Design and perform preliminary accelerated aging

tests to demonstrate rapid failures caused by individ- ually applied extreme degra- dation factors and to con- firm degradation mechanisms

PART 3 - TESTING

I Design and perform

predictive service

life tests using the degradation factors of importance to determine

the dependence of the

rate of degradation on exposure conditions

Design and perform long- term tests under service conditions

Compare types of degradation obtained by both in-service and predictive

service life tests 737

<

QUESTION: Are the changes

Induced by predictive^

service life tests repre-^ sentative of those observed in-service?

res'

PART 4 INTERPRETATION AND

REPORTING OF DATA

Develop mathematical models of degradation

and compare rates of change in predictive

service life tests with

those from in-service

tests

Establish perfonnance cri- teria for predictive

service life tests

Predict service life under expected in- service conditions

Report

the data

Figure 1. Steps in the Recommended Practic for Developing

Predictive Service Life Tests

30
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IIBS-114A (REV. 9-76)

U.S. DEPT. OF COMM. BIBLIOGRAPHIC DATA

SHEET

1. PUBLICATION OR REPORT NO. NBS TN 1120

4. TITLE AND SUBTITLE

An Approach to Improved Durability Tests for Building

Materials and Components

5. Publication Date July 1980

7. AU.THOR(S)

lonffrpv Frnhnsdorff. Larrv W. Masters. Jonathan W. Martin

( Perflnming Organization Code

8. Performing Organ. Report No.

9. PERFORMING ORGANIZATION NAME AND ADDRESS

NATIONAL BUREAU OF STANDARDS

DEPARTMENT OF COMMERCE

WASHINGTON, DC 20234

11. Contract/Grant No.

12. SPONSORING ORGANIZATION NAME AND COMPLETE ADDRESS rsfreet. City, state. ziP)

Same as 9 above .

13. Type of Report & Period Covered Final

^- >-^ " '>^'

lis. SUPPLEMENTARY NOTES

I I Document describes a computer program; SF-185, FIPS Software Summary, is attached.

116. ABSTRACT (A 200-woTd or leaa factual summary of moat signiticant information. If document includes a significant bibliography or

literature survey, merttion it here.)

I Durability tests usually provide relative measures Of the time building materials and

! components will perform their intended functions under the expected service conditions

This is not adequate to ensure the proper selection of new building materials and

(components because quantitative measures of long-term performance are needed.

! Although many tests have been developed to accelerate degradation processes of building

i materials, they are seldom fully adequate for reliably predicting long-term per-

|formance. In this paper, a recommended practice, ASTM E 632-78, which provides a framework for the development of improved durability tests, is outlined. The

i application of the recommended practice, which does not specify an analysis procedure,

p's illustrated by examples from the literature using both deterministic and probabilistic approaches.

While probabilistic concepts have not been applied extensively to materials durability

problems in the construction industry, these concepts offer new opportunities for_

obtaining improved quantitative predictions of the service life of building materials.

17. KEY WORDS (six to twelve entriea; alphabetical order; capitalize only the firat tetter of the first key word unleas a proper name;

separated by aemicolona)

Accelerated aging tests; building components; building materials; durability;

life testing; prediction; recommended practice; reliability service life.

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