Treffer: Characterisation and statistical modelling of shear strength in 12 hardwood timber species from the Congo Basin

Title:
Characterisation and statistical modelling of shear strength in 12 hardwood timber species from the Congo Basin
Contributors:
National Advanced School of Engineering (University of Yaounde I), BioWooEB (UPR BioWooEB), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université de Montpellier (UM)
Source:
Bois et Forêts des Tropiques. 360:27-40
Publisher Information:
CCSD; Montpellier : CIRAD, 2024.
Publication Year:
2024
Collection:
collection:CIRAD
collection:SDE
collection:GIP-BE
collection:AGREENIUM
collection:UNIV-MONTPELLIER
collection:UM-2015-2021
collection:UM-EPE
Original Identifier:
HAL: hal-05095406
Document Type:
Zeitschrift article<br />Journal articles
Language:
English
ISSN:
0006-579X
Relation:
info:eu-repo/semantics/altIdentifier/doi/10.19182/bft2024.360.a37284
DOI:
10.19182/bft2024.360.a37284
Rights:
info:eu-repo/semantics/OpenAccess
URL: http://creativecommons.org/licenses/by/
Accession Number:
edshal.hal.05095406v1
Database:
HAL

Weitere Informationen

Shear strength is a wood property which is fundamental to the design of wood-based products and constructions. This property cannot be predicted at present for lack of sufficient knowledge, mainly because of the large number of timber species that occur in the Congo Basin. The main aim of this study was to provide a preliminary qualification of shearing in Congo Basin timber species, with consideration for its variability. For this purpose, we studied 12 timber species with very different properties, from the least dense to the densest. Their shear strength was determined experimentally using European standards specifications, on the scale of the wood material used. A statistical analysis was conducted. To reduce shear strength variability, the species were assigned to four distinct clusters defined according to FCBA Institute specifications. With a view to developing allowable design stresses to facilitate decision-making, we evaluated the relative goodness-of-fit of five probabilistic shear strength distributions (normal, lognormal, exponential, Weibull 2 parameters and Weibull 3 parameters) that are used in wood-related applications. The results of geometric regression (R2 = 0.81) show that shear strength is well correlated with density. Shear strength can be more reliably predicted with the three-parameter Weibull distribution than with the other distributions. The findings of this study open up new prospects to be considered for the design of wood-based products with regard to shear, when using tropical timber species from the Congo Basin.