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Presenting an analysis of different approaches for predicting the
service life of buildings, this monograph discusses various
statistical tools and mathematical models, some of which have
rarely been applied to the field. It explores methods including
deterministic, factorial, stochastic and computational models and
applies these to facade claddings. The models allow (i)
identification of patterns of degradation, (ii) estimation of
service life, (iii) analysis of loss of performance using
probability functions, and (iv) estimation of service life using a
probability distribution. The final chapter discusses the
differences between the different methodologies and their
advantages and limitations. The authors also argue that a better
understanding of the service life of buildings results in more
efficient building maintenance and reduced environmental costs. It
not only provides an invaluable resource to students, researchers
and industry professionals interested in service life prediction
and sustainable construction, but is also of interest to
environmental and materials scientists.
Presenting an analysis of different approaches for predicting the
service life of buildings, this monograph discusses various
statistical tools and mathematical models, some of which have
rarely been applied to the field. It explores methods including
deterministic, factorial, stochastic and computational models and
applies these to facade claddings. The models allow (i)
identification of patterns of degradation, (ii) estimation of
service life, (iii) analysis of loss of performance using
probability functions, and (iv) estimation of service life using a
probability distribution. The final chapter discusses the
differences between the different methodologies and their
advantages and limitations. The authors also argue that a better
understanding of the service life of buildings results in more
efficient building maintenance and reduced environmental costs. It
not only provides an invaluable resource to students, researchers
and industry professionals interested in service life prediction
and sustainable construction, but is also of interest to
environmental and materials scientists.
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