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An advanced virtual grading method for wood based on surface information of knots

  • A. Khaloian SarnaghiEmail author
  • J. W. G. van de Kuilen
Original
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Abstract

Strength grading of timber boards is an important step before boards can be used as lamellas in glued laminated timber. Grading is generally done visually or by machine, whereby machine grading is the faster and more accurate process. Machine grading gives the best strength prediction when dynamic modulus of elasticity (MoEdyn) is measured and some kind of knot assessment algorithm is included as well. As access to the actual density for the measurement of MoEdyn may be impossible in some conditions, this grading method may face some problems in strength prediction. As the strength of a board is related to its natural defects and the ability of the stress waves to propagate around these defects, a virtual method for more accurate strength predictions is developed based on the knot information on the surface. Full 3D reconstruction of the boards, based on knot information on the surfaces of these boards, is an important step in this study. Simulations were run for 450 boards of spruce, Douglas fir, beech, ash and maple, covering a large quality range. Abaqus and Python were used for the numerical simulations. From the numerical simulations, three different stress concentration factors were calculated in the vicinity of the defects. Additionally, a virtual longitudinal stress wave propagation was modeled for the determination of the dynamic modulus of elasticity. The FEM results were used to predict the tensile strength. By means of a regression analysis, the correlation with actual visual and machine readings was validated. An improvement in the strength prediction was observed based on the virtual method, when compared to currently available grading machines. It shows the potential of numerical methods for strength prediction of wood based on visual knot information.

Notes

Acknowledgements

The authors gratefully acknowledge the support of the Bayerische Landesanstalt für Wald und Forstwirtschaft for funding the Project X042 “Beechconnect” which allowed for the work presented in this paper.

Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Supplementary material

226_2019_1089_MOESM1_ESM.docx (76 kb)
Supplementary material 1 (DOCX 76 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • A. Khaloian Sarnaghi
    • 1
    Email author
  • J. W. G. van de Kuilen
    • 1
    • 2
    • 3
  1. 1.Department of Wood TechnologyTechnical University of MunichMunichGermany
  2. 2.Faculty of Civil Engineering and GeosciencesDelft University of TechnologyDelftThe Netherlands
  3. 3.CNR-IvalsaFlorenceItaly

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