Abstract
The financial resources available for infrastructure maintenance and rehabilitation are always limited, which creates a need for efficient resources' management and for the ability to predict maintenance actions throughout the infrastructure's service life. In the context of bridges, management systems have been developed and are already implemented around the world. A much larger variety of maintenance problems and a reduced number of buildings per owner mean that building management systems (BdMSs) are still quite rare. Actually, efficient methods for the service life prediction of building materials still need to be developed. This paper discusses the service life prediction methods used in building components based on deterministic, stochastic or engineering methods. The architecture of a recently developed BdMS – BuildingsLife – is presented, where the service life analysis of components is based on an initial statistical analysis of anomalies obtained from the inspection of in-use buildings. This method analyses the corresponding degradation through the use of deterministic and stochastic models.
Acknowledgements
The authors wish to acknowledge GATEWIT SA for its support with the application of the BuildingsLife Platform. The authors also gratefully acknowledge the support of the ICIST Research Institute from IST, Technical University of Lisbon and FCT (Foundation for Science and Technology).
Notes
1. Email: [email protected]
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