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    RESEARCH 1

    DEVELOPMENT OF A RELIABILITY-BASED DURABILITY DESIGN METHOD

    FOR TIMBER CONSTRUCTION

    Agonos, Kim Nio!"

    B#n$ig#n, M#%& C!"o

    C#m'os#no, R#("! Ann

    C#s)i!!o, K#("# *o(#&n"

    I+ INTRODUCTION

    Durability is one of the most important considerations in the use of wood in

    construction. While many timber durability guidelines and design aids are available to

    engineers and designers, the current approach to timber durability design is still very much

    an art; design solutions vary from person to person and control of performance depend

    almost exclusively on compliance to good building practice. This tends to inhibit innovation

    and optimization of building design, and is not useful for assessing the impact of rapid

    changes enforced by legislation (e.g., banning of chemicals.

    !f the factors affecting durability and the mechanisms of degradation, including

    inherent uncertainties, are "uantified, design procedures can be developed so that a product

    or building can be designed to perform satisfactorily with a given level of confidence, much

    li#e the way it is currently done in structural design. $ut while the technology of structural

    engineering is well developed and applied with confidence in design, the technology re"uired

    for an engineering approach to durability is far behind.

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    II+ OB*ECTIVE OF THE STUDY

    The long%term goal is to develop tools and methods to enable designers to&

    '. redict the durability of any type of timber construction located anywhere in

    )ustralia;

    *. +a#e informed decisions on important variables affecting timber durability and

    their influence on performance;

    . Design and specify a durable system for any use or application that will achieve

    its performance goals.

    III+ SCOPE AND LIMITION

    This paper presents an overview and some preliminary results of a ma-or 

    multidisciplinary timber durability research effort in )ustralia, focused on the development

    of a reliability%based durability design method for timber construction. ne factor that helps

    us appreciate the complexity of this underta#ing is the fact that since the inception of the

     pro-ect, about /00 related references have been collected and reviewed.

    The general prediction models can also be used to assess the performance of new and

    innovative products and the impact of rapid changes enforced by legislation (e.g., banning of 

    chemicals. !n con-unction with a non%destructive testing method, the models can be used to

     predict the residual life of a timber element and to develop an optimized inspection and

    maintenance program. Thus, the models are #ey components of an improved asset

    management system for timber structures.

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    IV+ DEPENDENT AND INDEPENDENT VARIABLES

    V+ SUMMARY OF METHODOLOGY

    A+ P%o"$%"s

    • 1ub%program '& +odel development and calibration

    2igure ' illustrates the #ey steps in the development of the attac# models and

    the design procedure. !n the case of decay, for example, we start with classical models

    of moisture movement in porous media, using fundamental material parameters.

    3limate, soil and other environmental data are used to identify the context of 

    durability performance, and as input to predicting performance. ) simplified

    degradation or attac# model, with new material parameter inputs that can be easily

    and "uic#ly measured and with reasonable prediction capability (compared to the

    fundamental model, is then developed and calibrated using all available data

    including historical durability index properties, new field and laboratory data

    generated in the present pro-ect (e.g., from 1ub%programs * and and, when

    necessary, expert opinion. Then, the durability design procedure is developed from a

    composite of all the attac# models.

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    • 1ub%program *& 4nvironmental agents 5 maps and databases

    Detailed climate data have been collected and are being related to

    microclimate within the house, and eventually to local element condition (2igs. * and

    . This process re"uires climate sub%models that relate global climate data to a

    specific site, from external climate to microclimate within the house, and from

    microclimate in the cavity to moisture conditions of the timber (2ig. *. 3limate data

    that have been collected include rainfall, temperature, relative humidity, wind,

    evaporation, cloud cover and various components of solar radiation. +icroclimate

    data being monitored in cavities of selected houses in locations with tropical,

    subtropical and temperate climates are temperature and relative humidity (2ig. ;

    also being monitored are 1implified Degradation6)ttac# +odel 4ngineering

    rocedures 2undamental 4"uations 3limate Data ther 4nvironmental Data 7se

    fundamental parameters of materials. 3onditions that are conducive to degradation

    (initiation and6or acceleration are being investigated.

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    $ased on seven years of  

    )ustralian data on exposed 8%-oint

    specimens and the mean monthly

    temperature and rainfall in )ustralia, an

    above ground decay hazard map for 

    )ustralia has been plotted (2ig. 9a

    using the 1cheffer:s index. nowing

    that faster evaporation in the )ustralian

    climate allows wetted timber to dry out

    faster than in the northern hemisphere

    (where the 1cheffer:s index was originally derived, a new decay index, referred to as

    the D! index, has been derived as a function of percentage of wet days and the

    average vapour pressure deficit (+. 3ause, private communication. This index fits

    the updated nine%year 8%-oint data better than the 1cheffer:s index did. The

    differences are seen in comparing 2igs. 9a and 9b; the D! index provides a more

    refined and appropriate above ground decay hazard map for )ustralia. 2urther 

    refinements in the calculation of the above ground durability hazard are being

    investigated.

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    The termite hazard map will be based on a combination of results of a public

    survey and prediction using the attac# model. The first stage of a national survey

    has been completed and the second stage is on%going at the time of this writing.

    +etal corrosion is a combination of atmospheric corrosion on exposed steel and

    cathodic corrosion on the embedded steel. 2or the case of atmospheric corrosion,

    critical attac# parameters are the effective time of wetness and concentration of air 

     pollutants, particularly sea%salt. $ased on analysis of available exposure test data

    and modeling results, 2ig. < shows the estimated corrosion of a metal plate of mild

    steel containing copper.

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    • 1ub%program & +aterial resistance and test protocols

    art of this sub%program is focused on developing standardised durability

    assessment methods for materials, including the suitability of accelerated field

    simulation laboratory techni"ues to determine resistance to termites, fungi and

    corrosion. )nother focus is the determination of durability rating resistance of 

    common timber products for prescriptive design guidelines and of degradation rates

    of treated and untreated timber for prediction models. The latter is based on both new

    field data and previously collected data originally intended to obtain durability index

     properties.

    ) considerable amount of material resistance evaluation is in progress, with

    decay and termites, both in%ground and above ground, for both treated and untreated

    wood. There are also above ground wood panel exposure tests and corrosion tests

    with both nails and metal plates

    B+ S)#)is)i#! Too!s

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    The #ey to developing a design procedure is first to have predictive models for 

    durability. 2igure = illustrates the way the models and design procedure will be used. ) set of 

    input parameters is used to define the design situation, a particular hazard type is selected,

    and a calculation model is used to predict the performance of the element or building system.

    Typical input parameters are those that relate to the hazard, building location,

     building construction, building element and maintenance programs (or user action.

    erformance criteria will be classified as either structural collapse, unserviceability (such as

    excessive deflections, water entry or loss of material or aesthetic deterioration. The hazards

    considered include attac# by&

    • 2ungi

    • Termites

    • 3orrosion agents

    • +echanical degradation

    1ince there are uncertainties in the data, models and analysis methods, it is natural to

    apply probabilistic techni"ues and recognize and incorporate these uncertainties in the model

    development process. 4ach attac# model is assumed to comprise a se"uence of events as

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    shown in 2ig. >. The duration of each event is a random variable. This leads to a prediction in

    statistical terms as shown in 2ig. ?.

    VI+ RESULTS AND CONCLUSION

    This pro-ect provides a framewor# and method of using fundamental degradation

    models, and climate and relevant environmental factors to develop general durability

     prediction models and formal design procedures for timber construction.

    @esearch to date indicates that the development of formal durability design

     procedures, based on prediction models, is not only feasible but is a better and more flexible

    approach to ensure durable timber construction. The existence of formal timber durability

    design procedures, similar in concept to structural design, will facilitate the teaching and

    globalization of the technology, and hopefully lead to the day when failures related to

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    durability will be regarded as failures of applied technology, and not ta#en to be an un#nown

    ris# associated with the use of timber.

    V+ RECOMMENDATION OF THE READER 

    +uch research is needed to better understand fundamental degradation mechanisms

    of timber in%service, improve the attac# models and provide more reliable data to validate

    and calibrate the prediction models.

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