Visual and machine strength grading of European ash and maple for glulam application

Journal article (2019)

Authors

Andriy Kovryga Technische Universität München
Philipp Schlotzhauer University of Göttingen
Peter Stapel Technische Universität München
Holger Militz University of Göttingen
J.W.G. van de Kuilen Technische Universität München, Bio-based Structures & Materials - CEG
Research Group
Bio-based Structures & Materials (CEG) (TU Delft)
Optimisation Tensile strength Dynamic MOE Machine grading Hardwoods Glulam Strength profiles Grading of hardwoods Mechanical properties of hardwoods Multisensor system Visual strength grading X-ray attenuation (XRA)
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Published Date

2019

Language

English

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Faculty

Civil Engineering & Geosciences

Department

Engineering Structures

Research Group

Bio-based Structures & Materials

Abstract

Medium dense hardwoods (HWs) show higher tensile strength (TS) values than softwoods (SWs). These advantages cannot be utilised effectively because HW grading is not well developed. The aim of the present paper was to analyse the utilisation potential of European ash (Fraxinus spp.) and maple (Acer spp.) grown in Central Europe, which were graded by different methods. The visual grading characteristics of 869 HW boards were determined and the dynamic modulus of elasticity (MOE dyn ) and X-ray attenuation (XRA) were measured by an industrial scanner. The specimens were subsequently tested in tension according to EN 408:2010 and according to German visual grading rules show strength values of 28 MPa and 30 MPa, respectively. Machine strength grading and for a combination of manually assessed boards and MOE dyn give rise to higher strength data. MOE dyn , in particular, results in lamella data with 62 MPa for ash and 42 MPa for maple. There is good agreement with recently presented HW tensile profiles. Machine grading with a multisensor system allows better strength prediction compared to the MOE dyn or visual strength grading. Best performance is achieved by a combined grading approach.