DISTRIBUTIONS OF MODULUS OF ELASTICITY AND MODULUS OF RUPTURE IN FOUR MILL RUN LUMBER POPULATIONS

Authors

  • Frank C Owens Mississippi State University
  • Steve P Verrill USDA Forest Products Laboratory
  • Rubin Shmulsky Mississippi State University
  • Robert J Ross USDA Forest Products Laboratory

Keywords:

full lumber population, structural lumber, mill run, modulus of elasticity, modulus of rupture, normal distribution, Weibull, lognormal, skew normal, mixed normal, pseudo-truncation

Abstract

The modulus of elasticity (MOE) and modulus of rupture (MOR) of graded lumber populations are commonly modeled by normal, lognormal, or Weibull distributions, but recent research has cast doubt on the appropriateness of these models. Such modeling has implications for ultimate performance and efficiency of resource use. It has been shown mathematically that the distribution of MOR in a graded subpopulation does not have the same theoretical form as the full, ungraded (or “mill-run”) population from which it was drawn; rather, its form is pseudo-truncated, exhibiting thinned tails. Although the phenomenon of pseudo-truncation in graded populations has been well substantiated, the form of the underlying full distribution—an essential factor in characterizing the distribution of the graded population—remains unsettled. The objective of this study was to characterize the distributions of both MOE and MOR in four diverse mill-run lumber populations to determine if and to what extent the distributions of strength and stiffness in mill-run lumber are similar from mill to mill. The authors collected a mill-run sample of 200 southern pine 24 specimens from each of four sawmills, for a total of 800 test pieces. After measuring MOE and MOR, they fit candidate distributions to those data by mill and evaluated each distribution for goodness of fit. Results suggest that perhaps none of the traditional distributions of normal, lognormal, or Weibull is adequate to model MOE or MOR across all four mills; rather, MOE and MOR in full lumber populations might be better modeled by skew normal or mixed normal distributions.

Author Biographies

Frank C Owens, Mississippi State University

Assistant Research Professor

Department of Sustainable Bioproducts

Steve P Verrill, USDA Forest Products Laboratory

Mathematical Statistician

Rubin Shmulsky, Mississippi State University

Professor and Department Head

Department of Sustainable Bioproducts

Robert J Ross, USDA Forest Products Laboratory

Supervisory Research General Engineer

References

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Verrill SP, Owens FC, Kretschmann DE, Shmulsky R, Brown L (2019) Visual and MSR grades of lumber are not two-parameter Weibulls and why it matters (with a discussion of censored data fitting). Under review. http:// www1.fpl.fs.fed.us/weib2.new.pdf (12 November 2018).

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Published

2019-04-17

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Research Contributions