Hierarchical modeling of structural timber material properties by means of Bayesian Probabilistic Networks

M. Deublein*, M. Schlosser, M. H. Faber

*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

6 Citations (Scopus)

Abstract

In the pursuit of modeling the performance of timber structures the probabilistic representation of the variability of timber material properties is an issue of special interest. Material properties can be represented by random variables and the statistical characteristics of these variables can be described by distribution models together with the corresponding parameters which are calibrated based on data taken from standard test samples and grading machine measurements. In the present paper special emphasis is directed on how to represent multi-scale spatial variability of timber material properties. Variability of timber material properties is considered at different levels and, subsequently, brought together into one consistent hierarchical model by means of a Bayesian probabilistic network. The hierarchical model is used to determine the influence of the origins and cross-sectional dimensions of the timber on the probability distribution of timber material properties.

Original languageEnglish
Title of host publicationApplications of Statistics and Probability in Civil Engineering -Proceedings of the 11th International Conference on Applications of Statistics and Probability in Civil Engineering
Number of pages9
Publication date2011
Pages1377-1385
ISBN (Print)9780415669863
Publication statusPublished - 2011
Externally publishedYes
Event11th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP - Zurich, Switzerland
Duration: 1 Aug 20114 Aug 2011

Conference

Conference11th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP
Country/TerritorySwitzerland
CityZurich
Period01/08/201104/08/2011
SponsorBundesamt fur Strassen (ASTRA), Walt + Galmarini AG, BKW FMB Energie AG, Det Norske Veritas AS, Swiss Federal Institute of Technology Zurich

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