Probabilistic strength prediction of adhesively bonded joints composed of wooden adherends

Vallée, T.; Tannert, T.; Lehmann, Martin; Brunner, Maurice Yaw (July 2009). Probabilistic strength prediction of adhesively bonded joints composed of wooden adherends In: 12th International Conference on Fracture 2009. Ottawa, Canada. 12-17 Jul 2009.

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The strength prediction of adhesively bonded wooden joints is difficult due to the anisotropic and brittle nature of the adherends, the complex stress distribution as well as the uncertainties regarding the associated material resistance. This paper describes a probabilistic method for the strength prediction of balanced double lap joints composed of wooden adherends and epoxy adhesives. The method considers the scale sensitivity of material strength modeled using a Weibull statistical function, and considers both the statistical variation and the size effect in the strength of the material. It considers not only the magnitude of the stress distributions, but also the volume over which they act. The probabilistic method presents a mechanical explanation for the increased resistance of local zones subjected to high strain or stress peaks.

Item Type:	Conference or Workshop Item (Paper)
Division/Institute:	School of Architecture, Wood and Civil Engineering School of Architecture, Wood and Civil Engineering > Institute for Materials and Wood Technology BFH Centres and strategic thematic fields > BFH Centre for Wood - Resource and Material School of Architecture, Wood and Civil Engineering > Institut for Building Materials and Biobased Products IBBM
Name:	Vallée, T.; Tannert, T.; Lehmann, Martin0000-0002-0813-7023 and Brunner, Maurice Yaw
Subjects:	Q Science > QA Mathematics T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TH Building construction T Technology > TJ Mechanical engineering and machinery
ISBN:	9781617382277
Language:	English
Submitter:	Martin Lehmann
Date Deposited:	22 Apr 2020 12:33
Last Modified:	09 Nov 2022 11:15
Related URLs:	Publication
ARBOR DOI:	10.24451/arbor.11372
URI:	https://arbor.bfh.ch/id/eprint/11372