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Title: Java image analysis program for lumber knots, and related nonlinear least squares routines for fitting lumber modulus of rupture to strength predictors

Source: FS General Technical Report

Author(s)Verrill, Steve; Owens, Frank C.; Shmulsky, Rubin; Ross, Robert

Publication Year: 2021  View PDF »

Category: General Technical Reports

Abstract: To properly evaluate the reliability of lumber structures, good models for the strength distributions of their components are needed. Modulus of rupture (MOR) distributions of grades of structural lumber have often been modeled as two-parameter Weibulls. However, in a series of papers, Verrill and others have established that strength properties of visual and machine stress rated grades of lumber are not distributed as two-parameter Weibulls and that modeling them as two-parameter Weibulls can yield large over- or underestimates of probabilities of breakage. Instead, grades of lumber have “pseudo-truncated” distributions. Recent research also established that the appropriate MOR model can change significantly with location and time and that model differences have practical significance. Verrill and others concluded that “there may be significant efficiencies that can be obtained through the development of computer models that yield real-time in-line estimates of lumber properties based on measurements of stiffness, specific gravity, knot size and location, slope of grain, and other strength predictors.” Verrill and others have now published a paper that proposes such models and fits them to mill run data. In this report, we discuss a computer program that was developed and used to obtain the knot portion of the data and other computer programs that were developed and used to fit the models.

Keywords: modulus of rupture; modulus of elasticity; specific gravity; slope of grain; knots; Weibull distribution; pseudo-truncated distributions; strength prediction models; lumber strength models; knot measurement

Publication Review Process: Informally Refereed (Peer-Reviewed)

File size: 7,168 kb(s)

Date posted: 12/27/2021

This publication is also viewable on Treesearch:  view
RITS Product ID: 10405
Current FPL Scientists associated with this product (listed alphabetically)
Ross, Robert J.
Supervisory Research Gen. Engineer
Verrill, Steve P.
Mathematical Statistician

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