Goodness-of-Fit for Mechanical Properties Distribution of Larch

Authors

  • J. X. Lu
  • J. H. Jiang
  • Y. Q. Wu
  • Y. Liu

Keywords:

Larch dimension lumber, goodness-of-fit, distribution, MOE, MOR, UTS, UCS

Abstract

Six different probability distributions, Johnson's SB, 2p-lognormal, 3p-lognormal, normal, 2p-Weibull, and 3p-Weibull, were used for testing their relative goodness of fit in describing modulus of rupture (MOR), modulus of elasticity (MOE), ultimate tension strength (UTS), and ultimate compression strength (UCS) of larch (Larix gmelini) dimension lumber. The populations of lumber consisted of 80 data sets with different mechanical properties, sizes, and structural grades. The Kolmogorov-Smirnov test was selected to be the goodness-of-fit criteria in this study. The 5- and 50-percentile values of these four different mechanical properties of larch lumber were estimated using both the inverse function of various distribution functions and the nonparametric method. Results indicated that 3p-lognormal was the optimal function in describing MOE of larch lumber. The 5- and 50-percentile estimations using the inverse function of 3p-lognormal were the closest values derived through the nonparametric method. Johnson's SB was the best one in describing MOR, UTS, and UCS. The 5- and 50-percentile estimations using the inverse function of Johnson's SB were the closest values derived with the nonparametric method. The distributions of these four mechanical properties of larch lumber were independent of the structural grade and size.

References

ASTM (2004a) D 1990-00. Standard practice for establishing allowable properties for visually graded dimension lumber from in-grade test of full-size specimens. American Society for Testing and Materials, West Conshohocken, PA.nASTM (2004b) D 4761-02a. Standard test methods for mechanical properties of lumber and wood base structural material. American Society for Testing and Materials, West Conshohocken, PA.nBarrett JD, Lau W (1994) Canadian lumber properties. Canadian Wood Council, Ontario, Canada. p. 41ff.nde Melo JE, Pellicane PJ, de Souza MR (2000) Goodness-of-fit analysis on wood properties data from six Brazilian tropical hardwoods. Wood Sci Technol 34:83-97.nLu JZ, Charles JM, Wu QL (2007) Fitting Weibull and lognormal distributions to medium-density fiberboard fiber and wood particle length. Wood Fiber Sci 39(1):82-94.nMathwave Technologies (2004) Easy Fit 5.5 Professional Evaluation Versions. Washington. http://www.mathwave.com'>http://www.mathwave.comnNational Lumber Grades Authority (2007) Standard grading rules for Canadian lumber. Surrey, British Columbia, Canada. pp. 70-75.nPellicane PJ (1983) A sampling strategy useful in full-distribution simulation.d Wood Sci Technol 17:279-286.nPellicane PJ, Bodig J (1981) Sampling error in the bending strength distribution of dimension lumber. Wood Sci Technol 15:211-225.nPellicane PJ, Collins F (1984) Application of the SB distribution to the simulation of correlated lumber properties data. Wood Sci Technol 18:147-156.nPellicane PJ, Collins F (1985) Goodness-of-fit analysis for lumber data. Wood Sci Technol 19:117-129.nRanta-Maunus A, Fonselius M (2001) Timber strength distributions. COST Action E24, reliability based design of timber structures. Coimbra, Portugal.n

Downloads

Published

2013-01-10

Issue

Section

Research Contributions