TY - JOUR

T1 - Probability models that relate nondestructive test methods to lumber design values of plantation loblolly pine

AU - Dahlen, Joseph

AU - Montes, Cristian

AU - Eberhardt, Thomas L.

AU - Auty, David

N1 - Funding Information:
This research was possible through support from Plum Creek Timber Company, the National Science Foundation (NSF) Center for Advanced Forest Systems (CAFS), the Wood Quality Consortium (WQC) at the University of Georgia and the NIFA McIntire-Stennis project 1 006 098. The authors wish to thank Plum Creek Timber Company, NSF CAFS, WQC and NIFA for funding this project. We also gratefully acknowledge Varn Wood Products LLC who processed the logs into structural lumber in their sawmill. Finally, we would like to thank the three anonymous reviewers and the handling editor, Dr. Alexis Achim, for their very helpful comments and suggestions in improving the manuscript.
Publisher Copyright:
© Institute of Chartered Foresters, 2018.

PY - 2018/7/1

Y1 - 2018/7/1

N2 - Within-grade variability in mechanical properties for visually graded lumber has led to increased deployment of nondestructive testing (NDT) methods, even though the relationships between static bending and NDT-predicted values are often highly variable. Dynamic modulus of elasticity (MOE dyn) was measured using two acoustic velocity instruments and one transverse vibration instrument, along with specific gravity, for 819 pieces of visually graded loblolly pine lumber. Static modulus of elasticity (MOE) and bending strength (F b) were measured via destructive testing. The probability of meeting design values was compared using (1) normal distribution linear and power regression models and (2) binomial distribution logistic regression models; the parameters of both models were fit using maximum likelihood estimation. For the normal distribution models, the standard error of the estimate, which ranged from 1.28 to 1.82 GPa for MOE and 4.47 to 5.07 MPa for F b, was incorporated into predictions in order to calculate the probability of meeting design values. At 50 per cent probability, transverse vibration MOE dyn values of 10.9 (normal) and 11.0 (binomial) GPa would meet the No. 2 MOE design value (9.7 GPa). At probabilities of 75 per cent and 95 per cent, the required values were 12.1 and 13.8 (normal) GPa and 12.0 and 13.5 (binomial) GPa, respectively. The normal and binomial approaches required similar NDT values to meet thresholds, although the advantage of the normal approach is that the regression parameters do not need to be recalculated for each threshold value, but at the expense of increased model complexity.

AB - Within-grade variability in mechanical properties for visually graded lumber has led to increased deployment of nondestructive testing (NDT) methods, even though the relationships between static bending and NDT-predicted values are often highly variable. Dynamic modulus of elasticity (MOE dyn) was measured using two acoustic velocity instruments and one transverse vibration instrument, along with specific gravity, for 819 pieces of visually graded loblolly pine lumber. Static modulus of elasticity (MOE) and bending strength (F b) were measured via destructive testing. The probability of meeting design values was compared using (1) normal distribution linear and power regression models and (2) binomial distribution logistic regression models; the parameters of both models were fit using maximum likelihood estimation. For the normal distribution models, the standard error of the estimate, which ranged from 1.28 to 1.82 GPa for MOE and 4.47 to 5.07 MPa for F b, was incorporated into predictions in order to calculate the probability of meeting design values. At 50 per cent probability, transverse vibration MOE dyn values of 10.9 (normal) and 11.0 (binomial) GPa would meet the No. 2 MOE design value (9.7 GPa). At probabilities of 75 per cent and 95 per cent, the required values were 12.1 and 13.8 (normal) GPa and 12.0 and 13.5 (binomial) GPa, respectively. The normal and binomial approaches required similar NDT values to meet thresholds, although the advantage of the normal approach is that the regression parameters do not need to be recalculated for each threshold value, but at the expense of increased model complexity.

KW - Intensively managed plantations

KW - mechanical properties

KW - nondestructive testing

KW - southern pine

KW - uncertainty measures

KW - wood quality

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U2 - 10.1093/forestry/cpy001

DO - 10.1093/forestry/cpy001

M3 - Article

AN - SCOPUS:85047489810

SN - 0015-752X

VL - 91

SP - 295

EP - 306

JO - Forestry

JF - Forestry

IS - 3

ER -