TY - JOUR
T1 - Local 3D fibre orientation for tensile strength prediction of European beech timber
AU - Rais, Andreas
AU - Bacher, Martin
AU - Khaloian-Sarnaghi, Ani
AU - Zeilhofer, Monika
AU - Kovryga, Andriy
AU - Fontanini, Francesco
AU - Hilmers, Torben
AU - Westermayr, Maximilian
AU - Jacobs, Martin
AU - Pretzsch, Hans
AU - van de Kuilen, Jan Willem
N1 - Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/4/12
Y1 - 2021/4/12
N2 - In central Europe forests, the share of European beech (Fagus sylvatica L.) trees has been increased in the last decades. Machine strength grading of hardwood is challenging due to a lack of knowledge about strength predictors. However, high strength classes are needed for the utilization as glued and cross laminated timber. We used the information of an industrial scanner on fiber orientations, developed a 3D cluster value (SOG3D,150,max) for strength assessment and combined the parameter with the dynamic modulus of elasticity (MOEdyn) to compute an indicating property (IP). A sample of 407 European beech boards passed a multi-sensor scanner to detect wood density, eigenfrequency and slope of grain (SOG). Fiber angle on the surfaces of four board sides was measured using the tracheid effect. The spatial fiber orientation inside the board was modeled for a total of approximately 150,000 points per board meaning 12 points per cm3. Finally, the board section with the largest average local fiber orientation in a window of 150 mm defined the grading parameter SOG3D,150,max. The prediction of tensile strength via SOG3D,150,max reached r2 between 0.466 and 0.605 depending on the type of data transformation. A combination with the MOEdyn, the probably most common IP, increased the r2 to 0.722 at best. Local grain deviation is a suitable wood parameter for hardwood strength grading. By detecting local defects, the causality between wood strength and tree functioning as well as silvicultural steering may be further understood in future.
AB - In central Europe forests, the share of European beech (Fagus sylvatica L.) trees has been increased in the last decades. Machine strength grading of hardwood is challenging due to a lack of knowledge about strength predictors. However, high strength classes are needed for the utilization as glued and cross laminated timber. We used the information of an industrial scanner on fiber orientations, developed a 3D cluster value (SOG3D,150,max) for strength assessment and combined the parameter with the dynamic modulus of elasticity (MOEdyn) to compute an indicating property (IP). A sample of 407 European beech boards passed a multi-sensor scanner to detect wood density, eigenfrequency and slope of grain (SOG). Fiber angle on the surfaces of four board sides was measured using the tracheid effect. The spatial fiber orientation inside the board was modeled for a total of approximately 150,000 points per board meaning 12 points per cm3. Finally, the board section with the largest average local fiber orientation in a window of 150 mm defined the grading parameter SOG3D,150,max. The prediction of tensile strength via SOG3D,150,max reached r2 between 0.466 and 0.605 depending on the type of data transformation. A combination with the MOEdyn, the probably most common IP, increased the r2 to 0.722 at best. Local grain deviation is a suitable wood parameter for hardwood strength grading. By detecting local defects, the causality between wood strength and tree functioning as well as silvicultural steering may be further understood in future.
KW - Dynamic modulus of elasticity
KW - EN 14081
KW - Fagus sylvatica
KW - Fiber deviation
KW - Knots
KW - Machine strength grading
KW - Slope of grain
UR - http://www.scopus.com/inward/record.url?scp=85101393567&partnerID=8YFLogxK
U2 - 10.1016/j.conbuildmat.2021.122527
DO - 10.1016/j.conbuildmat.2021.122527
M3 - Article
AN - SCOPUS:85101393567
SN - 0950-0618
VL - 279
JO - Construction and Building Materials
JF - Construction and Building Materials
M1 - 122527
ER -