Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

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Publications (1/1 displayed)

  • 2024Caractérisation de la résistance au cisaillement du bois de 12 essences feuillues du Bassin du Congo et modélisation statistique1citations

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Njankouo, Jacques Michel
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Gérard, Jean
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2024

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  • Njankouo, Jacques Michel
  • Gérard, Jean
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article

Caractérisation de la résistance au cisaillement du bois de 12 essences feuillues du Bassin du Congo et modélisation statistique

  • Ohandja, Louis Max Ayina
  • Njankouo, Jacques Michel
  • Gérard, Jean
Abstract

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.

Topics
  • density
  • impedance spectroscopy
  • cluster
  • strength
  • wood