Alterations to the bending mechanical properties of Pinus sylvestris timber according to flatwise and edgewise directions and knot position in the cross-section
DOI:
https://doi.org/10.22320/s0718221x/2024.43Keywords:
Knot area ratio, margin knot area ratio, modulus of elasticity, modulus of rupture, shear effectAbstract
Given the heterogeneity of the material, the behaviour of a timber beam may differ depending on which of its sides is subjected to tension and which one is subjected to compression. An analysis is undertaken in the present work of the behaviour in non-destructive bending tests on the four sides of 57 samples of Pinus sylvestris (scots pine) of structural size (2000 × 100 × 70 mm3). A study is additionally performed of the influence of the size and position of knots in the cross-section. The modulus of elasticity in flatwise direction was found to be 3 % higher than in edgewise direction. This difference could be attributable to the shear effect. While the introduction of knottiness variables did not improve modulus of elasticity prediction, it did decrease the error in the prediction of the modulus of rupture. The margin knot area ratio corresponding to the outer eighth of the cross-section’s width occupied by knots was the knottiness variable with the lowest error in modulus of rupture prediction.
Downloads
References
Alexander, D.L.J.; Tropsha, A.; Winkler, D.A. 2015. Beware of R2: Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models. Journal of Chemical Information and Modeling 55(7): 1316-1322. https://doi.org/10.1021/acs.jcim.5b00206.
Algin, Z. 2019. Multivariate performance optimisation of scaffold boards with selected softwood defects. Construction and Building Materials 220: 667-678. https://doi.org/10.1016/j.conbuildmat.2019.05.190
Arriaga, F.; Esteban, M.; Argüelles, R.; Bobadilla, I.; Íñiguez-González, G. 2007. The effect of wanes on the bending strength of solid timber beams. Materiales de Construccion 57(288): 61-76. https://doi.org/10.3989/mc.2007.v57.i288.65
Arriaga, F.; Iniguez-Gonzalez, G.; Esteban, M.; Divos, F. 2012. Vibration method for grading of large cross-section coniferous timber species. Holzforschung 66(3): 381-387. https://doi.org/10.1515/HF.2011.167
Arriaga, F.; Monton, J.; Segues, E.; Iniguez-Gonzalez, G. 2014. Determination of the mechanical properties of radiata pine timber by means of longitudinal and transverse vibration methods. Holzforschung 68(3): 299-305. https://doi.org/10.1515/hf-2013-0087
Baillères, H.; Hopewell, G.; Boughton, G.; Brancheriau, L. 2012. Strength and stiffness assessment technologies for improving grading effectiveness of radiata pine wood. BioResources 7(1): 1264-1282. https://doi.org/10.15376/biores.7.1.1264-1282
Boström, L. 1994. Machine strength grading. Comparison of four different systems. Swedish National Testing and Research Institute. SP Report 1994:49. http://ri.diva-portal.org/smash/get/diva2:961864/FULL-TEXT01.pdf
Boström, L. 1999. Determination of the modulus of elasticity in bending of structural timber - Comparison of two methods. Holz Als Roh - Und Werkst 57(2): 145-149. https://doi.org/10.1007/s001070050030
Brancheriau, L.; Bailleres, H.; Guitard, D. 2002. Comparison between modulus of elasticity values calculated using 3 and 4 point bending tests on wooden samples. Wood Science and Technology 36(5): 367-383. https://doi.org/10.1007/s00226-002-0147-3
BS. 2017. Visual Strength Grading of Softwood. Specification. BS 4978-2007+A2-2017: London, UK.
Conde García, M.; Fernández-Golfín Seco, J.I.; Hermoso Prieto, E. 2007. Mejora de la predicción de la resistencia y rigidez de la madera estructural con el método de ultrasonidos combinado con parámetros de clasificación visual. Materiales de Construccion 57(288): 49-59. https://doi.org/10.3989/mc.2007.v57.i288.64
EN. 2002. Moisture content of a piece of sawn timber. Part 1: Determination by oven dry method. EN 13183-1-2002. Brussels, Belgium.
EN. 2012. Timber structures. Structural timber and glued laminated timber. Determination of some physical and mechanical properties. EN 408-2011+A1-2012. Brussels, Belgium.
EN. 2016. Structural timber. Strength classes. EN 338-2016. Brussels, Belgium.
EN. 2018. Round and sawn timber - Methods of measurements - Part 3: Features and biological degradations. EN 1309-3-2018: Brussels, Belgium.
Faydi, Y.; Brancheriau, L.; Pot, G.; Collet, R. 2017. Prediction of oak wood mechanical prop- erties based on the statistical exploitation of vibrational response. BioResources 12(3): 5913-5927. https://doi.org/10.15376/biores.12.3.5913-5927
França, F.J.N.; França, T.S.F.A.; Seale, R.D.; Shmulsky, R. 2020. Use of longitudinal vibration and visual characteristics to predict mechanical properties of No. 2 southern pine 2x8 and 2x10 lumber. Wood and Fiber Science 52(3): 280-291. https://doi.org/10.22382/wfs-2020-026
França, F.J.N.; Seale, R.D.; Shmulsky, R.; França, T.S.F.A. 2019. Modeling mechanical properties of 2 by 4 and 2 by 6 southern pine lumber using longitudinal vibration and visual characteristics. Forest Products Journal 68(3): 286-294. https://meridian.allenpress.com/fpj/article/68/3/286/73763/Modeling-Mechanical- Properties-of-2-by-4-and-2-by
Guindos, P.; Guaita, M. 2014. The analytical influence of all types of knots on bending. Wood Science and Technology 48(3): 533-552. https://doi.org/10.1007/s00226-014-0621-8
Guindos, P.; Ortiz, J. 2013. The utility of low-cost photogrammetry for stiffness analysis and finite-element validation of wood with knots in bending. Biosystems Engineering 114(2): 86-96. https://doi.org/10.1016/j.biosystemseng.2012.11.002
Guntekin, E.; Emiroglu, Z.; Yilmaz, T. 2013. Prediction of bending properties for Turkish Red Pine (Pinus brutia Ten.) Lumber using stress wave method. BioResources 8(1): 231-237. http://dx.doi.org/10.15376/biores.8.1.231-237
Hashim, U.R.; Hashim, S.Z.M.; Muda, A.K. 2016. Performance evaluation of multivariate texture descriptor for classification of timber defect. Optik 127(15): 6071-6080. https://doi.org/10.1016/j.ijleo.2016.04.005
Hassan, K.T.S.; Horacek, P.; Tippner, J. 2013. Evaluation of stiffness and strength of scots pine wood using resonance frequency and ultrasonic techniques. BioResources 8(2): 1634-1645. http://dx.doi.org/10.15376/ biores.8.2.1634-1645
Hautamäki, S.; Kilpeläinen, H.; Verkasalo, E. 2013. Factors and models for the bending properties of sawn timber from Finland and north-western Russia. Part I: Norway spruce. Baltic Forestry 19(1): 106-119. https://jukuri.luke.fi/handle/10024/517641
Hautamäki, S.; Kilpeläinen, H.; Verkasalo, E. 2014. Factors and models for the bending properties of sawn timber from Finland and north-western Russia. Part II: Scots pine. Baltic Forestry 20(1): 142-156. https://jukuri.luke.fi/handle/10024/518279
Kim, K.M.; Shim, K.B.; Lum, C. 2010. Predicting tensile and compressive moduli of structural lumber. Wood and Fiber Science 43(1): 83-89. https://wfs.swst.org/index.php/wfs/article/view/610
Krzosek, S.; Grześkiewicz, M.; Burawska-Kupniewska, I.; Mańkowski, P.; Wieruszewski, M. 2021. Mechanical properties of polish-grown Pinus sylvestris L. structural sawn timber from the butt, middle and top logs. Wood Research 66(2): 231-242. https://doi.org/10.37763/wr.1336-4561/66.2.231242
Lam, F.; Barrett, J.D.; Nakajima, S. 2005. Influence of knot area ratio on the bending strength of Canadian Douglas fir timber used in Japanese post and beam housing. Journal of Wood Science 51(1): 18-25. https://doi.org/10.1007/s10086-003-0619-6
Lever, J.; Krzywinski, M.; Altman, N. 2016. Points of Significance: Model selection and overfitting. Nature Methods 13(9): 703-704. https://doi.org/10.1038/nmeth.3968
Lukacevic, M.; Füssl, J.; Eberhardsteiner, J. 2015. Discussion of common and new indicating properties for the strength grading of wooden boards. Wood Science and Technology 49(3): 551-576. https://doi.org/10.1007/s00226-015-0712-1
Mansfield, S.D.; Iliadis, L.; Avramidis, S. 2007. Neural network prediction of bending strength and stiffness in western hemlock (Tsuga heterophylla Raf.). Holzforschung 61(6): 707-716. https://doi.org/10.1515/HF.2007.115
Martins, C.E.J.; Dias, A.M.P.G.; Marques, A.F.S.; Dias, A.M.A. 2017. Non-destructive methodologies for assessment of the mechanical properties of new utility poles. BioResources 12(2): 2269-2283. https://doi.org/10.15376/biores.12.2.2269-2283
Pošta, J.; Ptáček, P.; Jára, R.; Terebesyová, M.; Kuklík, P.; Dolejš, J. 2016. Correlations and differences between methods for non-destructive evaluation of timber elements. Wood Research 61(1): 129-140. http://www.woodresearch.sk/cms/correlations-and-differences-between-methods-for-non-destructive-evalua-tion-of-timber-elements/
R Core Team. 2019. R: A language and environment for statistical computing. Version 3.6.1. R Foundation for Statistical Computing: Vienna, Austria. https://www.r-project.org/
Ranta-Maunus, A.; Denzler, J.K.; Stapel, P. 2011. Strength of European timber. Part 2. Properties of spruce and pine tested in Gradewood project. VTT Technical Research Centre of Finland VTT Working Pa- pers, No. 179. https://publications.vtt.fi/pdf/workingpapers/2011/W179.pdf
Šilinskas, B.; Varnagiryte-Kabašinskiene, I.; Aleinikovas, M.; Beniušiene, L.; Aleinikoviene, J.; Škema, M. 2020. Scots pine and Norway spruce wood properties at sites with different stand densities. Forests 11(5): 1-15. https://doi.org/10.3390/F11050587
Simic, K.; Gendvilas, V.; O’Reilly, C.; Harte, A.M. 2019. Predicting structural timber grade-determining properties using acoustic and density measurements on young Sitka spruce trees and logs. Holzforschung 73(2): 139-149. https://doi.org/10.1515/hf-2018-0073
Steffen, A.; Johansson, C.J.; Wormuth, E.W. 1997. Study of the relationship between flatwise and edge-wise moduli of elasticity of sawn timber as a means to improve mechanical strength grading technology. Holz Als Roh - Und Werkst 55(4): 245-253. https://doi.org/10.1007/bf02990556
Timoshenko, S. 1938. Strength of materials. D. Van Mostrand Company, Inc.: New York, USA.
Villasante, A.; Iniguez-Gonzalez, G.; Puigdomenech, L. 2019. Comparison of various multivariate models to estimate structural properties by means of non-destructive techniques (NDTs) in Pinus sylvestris L. timber. Holzforschung 73(4): 331-338. https://doi.org/10.1515/hf-2018-0103
Waikato University. 2014. WEKA software. Version 3.6.12. Waikato University: Hamilton, New Zealand. https://ml.cms.waikato.ac.nz/weka/index.html
Walker, J. 1993. Primary Wood Processing: Principles and Practice. Chapman & Hall: London, UK.
Wright, S.; Dahlen, J.; Montes, C.; Eberhardt, T.L. 2019. Quantifying knots by image analysis and modeling their effects on the mechanical properties of loblolly pine lumber. European Journal of Wood and Wood Products 77(5): 903-917. https://doi.org/10.1007/s00107-019-01441-8
Yang, B.Z.; Seale, R.D.; Shmulsky, R.; Dahlen, J.; Wang, X. 2015. Comparison of nondestructive test- ing methods for evaluating no. 2 southern pine lumber: Part B, modulus of rupture. Wood and Fiber Science 47(4): 375-384. https://wfs.swst.org/index.php/wfs/article/view/2367
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Los autores/as conservarán sus derechos de autor y garantizarán a la revista el derecho de primera publicación de su obra, el cuál estará simultáneamente sujeto a la Licencia de Reconocimiento de Creative Commons CC-BY que permite a terceros compartir la obra siempre que se indique su autor y su primera publicación esta revista.