A Dynamic Bayesian Network framework for spatial deterioration modelling and reliability updating of timber structures subjected to decay. (15th April 2020)

• Record Type: Journal Article
• Authors: Tran, Thanh-Binh; Bastidas-Arteaga, Emilio; Aoues, Younes
• Is Part Of: Engineering structures. Volume 209(2020)
• Publication Date: 2020-04-15
• Subjects: Spatial variability -- Reliability -- Updating -- Maintenance -- Inspection -- Dynamic Bayesian Networks -- Timber decay; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2020.110301
• Languages: English
• ISSNs: 0141-0296

Abstract

Highlights: A Dynamic Bayesian Network framework is used for reliability assessment and updating. The Framework was applied to timber structures subjected to decay. The Framework is able to take into account spatial and temporal variability of deterioration processes. The Framework is useful for reliability updating when using spatially distributed data. Abstract: Reliability assessment of existing timber structures subjected to deterioration processes is an important task to evaluate their serviceability and safety levels. Towards this aim, data collected after inspection campaigns are often used for updating structural reliability and planning future maintenance/inspection activities. Under natural conditions, timber decay involves a large number of uncertainties related to material properties and environmental exposure. These uncertainties are also affected by temporal and spatial variability of associated deterioration processes. In this context, the main objective of this study is to propose a Dynamic Bayesian Network approach for updating the structural reliability of deteriorating timber structures using inspection data. The proposed approach can account for the uncertainties in the decay process and the effect of spatial variability. It is also useful for reliability updating considering the uncertainties of inspection techniques. The proposed methodology is illustrated with the reliability updating of a timber beam subjected to decay deterioration. Results indicate that this approach is useful for evaluating and updating of structural reliability from spatially distributed inspection data. Reliability updating could also be carried out from partial observations at given areas, which is very useful for large-scale infrastructure.