Knots and their effect on the tensile strength of lumber: A case study

References

• ASTM International. 2007. D1990-07: Standard practice for establishing allowable properties for visually-graded dimension lumber from in-grade tests of full-size specimens. West Conshohocken, PA: ASTM International.
   Google Scholar
• ASTM International. 2012. D6874-12: Standard test methods for nondestructive evaluation of the stiffness of wood and wood-based materials using transverse vibration or stress wave propagation. West Conshohocken, PA: ASTM International.
   Google Scholar
• ASTM International. 2015. D198-15: Standard test methods of static tests of lumber in structural sizes. West Conshohocken, PA: ASTM International.
   Google Scholar
• ASTM International. 2019. D4761-19: Standard test methods for mechanical properties of lumber and wood-base structural material. West Conshohocken, PA: ASTM International.
   Google Scholar
• Barbosa, M. C., J. Street, F. C. Owens, and R. Shmulsky. 2019. The effect of multiple knots in close proximity on southern pine lumber properties. Forest Products Journal 69 (4):278–82.
   Web of Science ®Google Scholar
• Battaini, M., G. Yang, and B. Spencer. 2000. Bench-scale experiment for structural control. Journal of Engineering Mechanics 126 (2):140–8.
   Web of Science ®Google Scholar
• Biggeri, A., F. Barbone, C. Lagazio, M. Bovenzi, and G. Stanta. 1996. Air pollution and lung cancer in Trieste, Italy: spatial analysis of risk as a function of distance from sources. Environmental Health Perspectives 104 (7):750–4.
   PubMed Web of Science ®Google Scholar
• Bithell, J. 1995. The choice of test for detecting raised disease risk near a point source. Statistics in Medicine 14 (21–22):2309–22.
   PubMed Web of Science ®Google Scholar
• Canadian Lumber Standards Accreditation Board. 2021. Lumber grades. Accessed February 26, 2022. https://www.clsab.ca/faq-items/how-were-the-design-values-established-for-structural-lumber/.
   Google Scholar
• Castéra, P., C. Faye, and A. El Ouadrani. 1996. Prevision of the bending strength of timber with a multivariate statistical approach. Annals of Forest Science 53 (4):885–96.
   Web of Science ®Google Scholar
• Courchene, T., F. Lam, and J. Barrett. 1998. The effect of edge knots on the strength of SPF MSR lumber. Forest Products Journal 48 (4):75–81.
   Web of Science ®Google Scholar
• Cramer, S., and J. Goodman. 1983. Model for stress analysis and strength prediction of lumber. Wood and Fiber Science 15 (4):338–49.
   Web of Science ®Google Scholar
• Diggle, P. J. 1990. A point process modelling approach to raised incidence of a rare phenomenon in the vicinity of a prespecified point. Journal of the Royal Statistical Society: Series A (Statistics in Society) 153 (3):349–62.
   Web of Science ®Google Scholar
• Divos, F., and T. Tanaka. 1997. Lumber strength estimation by multiple regression. Holzforschung 51 (5):467–71.
   Web of Science ®Google Scholar
• Fink, G., and J. Kohler. 2014. Model for the prediction of the tensile strength and tensile stiffness of knot clusters within structural timber. European Journal of Wood and Wood Products 72 (3):331–41.
   Web of Science ®Google Scholar
• Foley, C. 2003. Modeling the effects of knots in structural timber. PhD diss., Lund Institute of Technology.
   Google Scholar
• França, F., R. D. Seale, R. Shmulsky, and T. França. 2018. 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):286–94.
   Web of Science ®Google Scholar
• García, D. A., and M. B. Rosales. 2017. Deflections in sawn timber beams with stochastic properties. European Journal of Wood and Wood Products 75 (5):683–99.
   Web of Science ®Google Scholar
• Gelman, A., J. B. Carlin, H. S. Stern, D. B. Dunson, A. Vehtari, and D. B. Rubin. 2013. Bayesian data analysis. Boca Raton, FL: Chapman and Hall/CRC.
   Google Scholar
• Gelman, A., D. Simpson, and M. Betancourt. 2017. The prior can often only be understood in the context of the likelihood. Entropy 19 (10):555.
   Web of Science ®Google Scholar
• Green, D. W., and K. A. McDonald. 1993. Investigation of the mechanical properties of red oak 2 by 4’s. Wood and Fiber Science 25 (1):35–45.
   Web of Science ®Google Scholar
• Harte, A. M. 2017. Mass timber – the emergence of a modern construction material. Journal of Structural Integrity and Maintenance 2 (3):121–32.
   Web of Science ®Google Scholar
• Hietaniemi, R., and O. Silvén. 2011. Camera based lumber strength classification system. In MVA2011 IAPR Conference on Machine Vision Applications, 251–254.
   Google Scholar
• Issa, C. A., and Z. Kmeid. 2005. Advanced wood engineering: glulam beams. Construction and Building Materials 19 (2):99–106.
   Web of Science ®Google Scholar
• Jun, S.-H., S. W. Wong, J. V. Zidek, and A. Bouchard-Côté. 2019. Sequential decision model for inference and prediction on nonuniform hypergraphs with application to knot matching from computational forestry. The Annals of Applied Statistics 13 (3):1678–707.
   Web of Science ®Google Scholar
• Kandler, G., J. Füssl, and J. Eberhardsteiner. 2015. Stochastic finite element approaches for wood-based products: theoretical framework and review of methods. Wood Science and Technology 49 (5):1055–97.
   Web of Science ®Google Scholar
• Kretschmann, D. E., J. W. Evans, and L. Brown. 1999. Monitoring of visually graded structural lumber, vol. 576. Madison, WI: US Department of Agriculture, Forest Service, Forest Products Laboratory.
   Google Scholar
• Lam, F., and E. Varoglu. 1991. Variation of tensile strength along the length of lumber. Wood Science and Technology 25 (5):351–9.
   Web of Science ®Google Scholar
• Lukacevic, M., J. Füssl, and J. Eberhardsteiner. 2015. Discussion of common and new indicating properties for the strength grading of wooden boards. Wood Science and Technology 49 (3):551–76.
   Web of Science ®Google Scholar
• Madsen, B., and A. H. Buchanan. 1986. Size effects in timber explained by a modified weakest link theory. Canadian Journal of Civil Engineering 13 (2):218–32.
   Web of Science ®Google Scholar
• NLGA. 2017. Standard grading rules for Canadian lumber. Vancouver, Canada: National Lumber Grades Authority.
   Google Scholar
• Oh, J.-K., K.-M. Kim, and J.-J. Lee. 2010. Use of adjacent knot data in predicting bending strength of dimension lumber by x-ray. Wood and Fiber Science 42 (1):10–20.
   Web of Science ®Google Scholar
• Pan, S., S. Fan, S. W. Wong, J. V. Zidek, and H. Rhodin. 2021. Ellipse detection and localization with applications to knots in sawn lumber images. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 3892–901.
   Google Scholar
• Reynolds, R. V. R., and A. H. Pierson. 1923. Lumber cut of the United States, 1870-1920. Number 1119. Washington, DC: US Department of Agriculture.
   Google Scholar
• Stan Development Team. 2020. RStan: the R interface to Stan. R package version 2.21.2.
   Google Scholar
• Taylor, S., D. Bender, D. Kline, and K. Kline. 1992. Comparing length effect models for lumber tensile strength. Forest Products Journal 42 (2):23–30.
   Web of Science ®Google Scholar
• Tegel, W., R. Elburg, D. Hakelberg, H. Stäuble, and U. Büntgen. 2012. Early neolithic water wells reveal the world’s oldest wood architecture. PLoS One 7 (12):e51374.
   PubMed Web of Science ®Google Scholar
• Vikram, V., M. L. Cherry, D. Briggs, D. W. Cress, R. Evans, and G. T. Howe. 2011. Stiffness of Douglas-Fir lumber: effects of wood properties and genetics. Canadian Journal of Forest Research 41 (6):1160–73.
   Web of Science ®Google Scholar
• Wong, S. W., C. Lum, L. Wu, and J. V. Zidek. 2016. Quantifying uncertainty in lumber grading and strength prediction: a Bayesian approach. Technometrics 58 (2):236–43.
   Web of Science ®Google Scholar
• Yard, A. 2017. Mass timber in North America. Architect 106 (5):54–7.
   Web of Science ®Google Scholar
• Zidek, J. V., and C. Lum. 2018. Statistical challenges in assessing the engineering properties of forest products. Annual Review of Statistics and Its Application 5:237–64.
   Web of Science ®Google Scholar