Inference on stiffness and strength of existing chestnut timber elements using Hierarchical Bayesian Probability Networks

Sousa, Hélder S. and Branco, Jorge M. and Lourenço, Paulo B. and Neves, Luís C. (2015) Inference on stiffness and strength of existing chestnut timber elements using Hierarchical Bayesian Probability Networks. Materials and Structures . pp. 1-16. ISSN 1871-6873

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Abstract

The assessment of the mechanical properties of existing timber elements could benefit from the use of probabilistic information gathered at different scales. In this work, Bayesian Probabilistic Networks are used to hierarchically model the results of a multiscale experimental campaign, using different sources of information (visual and mechanical grading) and different sample size scales to infer on the strength and modulus of elasticity in bending of structural timber elements. Bayesian networks are proposed for different properties and calibrated using a large set of experimental tests carried out on old chestnut (Castanea sativa Mill.) timber elements, recovered from an early 20th century building. The obtained results show the significant impact of visual grading and stiffness evaluation at different scales on the prediction of timber members’ properties. These results are used in the reliability analysis of a simple timber structure, clearly showing the advantages of a systematic approach that involves the combination of different sources of information on the safety assessment of existing timber structures.

Item Type: Article
Additional Information: The final publication is available at Springer via http://dx.doi.org/10.1617/s11527-015-0770-8
Keywords: Structural reliability, Bayesian Probabilistic Networks, � Existing timber structures, Bending stiffness, � Bending strength
Schools/Departments: University of Nottingham UK Campus > Faculty of Engineering
Identification Number: https://doi.org/10.1617/s11527-015-0770-8
Depositing User: Eprints, Support
Date Deposited: 23 Mar 2016 13:58
Last Modified: 14 Sep 2016 12:09
URI: http://eprints.nottingham.ac.uk/id/eprint/32488

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