Tensile strength grading of beech (Fagus sylvatica L.) lamellas from multiple origins, cross sections and qualities

Tensile strength grading of beech (Fagus sylvatica L.) lamellas from multiple origins, cross sections and qualities

Westermayr, Maximilian (Technische Universität München)
Zeilhofer, Monika (Technische Universität München)
Rais, Andreas (Technische Universität München)
Kovryga, Andriy (Technische Universität München)
van de Kuilen, J.W.G. (TU Delft Bio-based Structures & Materials; Technische Universität München)

2022

The market share of European beech (Fagus sylvatica L.) wood in the construction sector is low despite an increase in beech stock in Central European Forests in recent years. More efficient sawing techniques, higher lamella grading yields and solving of adhesion challenges may increase the competitiveness of beech glulam and promote its use. The aim of this paper is to revise the lamella grading system in the current German technical approval for beech glulam Z-9.1-679:2019 (DIBt (2019). BS-Holz aus Buche und BS-Holz Buche Hybridträger und zugehörige Bauarten. Allgemeine bauaufsichtliche Zulassung Z-9.1-679:2019. Deutsches Institut für Bautechnik) and to suggest modifications in the lamella grading rules for glulam production allowing higher yields and reliable tensile strength values at the same time. The unique dataset in this study combined different origins of lamellas and covered a wide range of visual, physical and mechanical wood characteristics including a high amount of low quality material. Indicating properties (IPs) for tensile strength, such as knot parameters and dynamic modulus of elasticity, were contrasted with tensile strength and static modulus of elasticity. Beech lamellas, graded by means of Z-9.1-679:2019 (DIBt (2019). BS-Holz aus Buche und BS-Holz Buche Hybridträger und zugehörige Bauarten. Allgemeine bauaufsichtliche Zulassung Z-9.1-679:2019. Deutsches Institut für Bautechnik), did not achieve the tensile strengths required for glulam production in many grading classes and the yield was low. A machine grading approach with dynamic modulus of elasticity as a single grading criterion gave higher yields than the current grading procedure and high reliability for tensile strength prediction with a prediction accuracy of R2 = 0.67.

grade determining properties (GDPs)
grading classes
hardwood
indicating properties (IPs)

http://resolver.tudelft.nl/uuid:0e8cab24-90c0-4293-abd5-7a5f186aae8c

https://doi.org/10.1515/hf-2021-0029

2023-07-01

0018-3830

Holzforschung: international journal of the biology, chemistry, physics and technology of wood, 76 (5), 397-407

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2022 Maximilian Westermayr, Monika Zeilhofer, Andreas Rais, Andriy Kovryga, J.W.G. van de Kuilen