Probabilistic evaluation of the final moisture content of kiln-dried lumber using the bootstrap method

This paper presents a probabilistic method of evaluating the final moisture content (MC) of lumber obtained at the end of the kiln-drying process. The final MC data of three different drying tests conducted in past studies were analyzed using the bootstrap method. Target MC was tentatively set below 20 % in the analysis. Two characteristic parameters representing the final MC were estimated with bootstrap confidence intervals. These parameters were the standard deviation (SD) and the percentage of the population that met the MC requirement of less than 20 % (P ₂₀). The histograms of the final MC and the subsequent goodness-of-fit tests revealed that the final MC data of two drying tests did not follow any classical probability distributions, including Normal, Log-Normal, Weibull, and Gamma distributions, thus indicating the need for nonparametric statistics. The uncertainty of the final MC could be evaluated with the estimated SD and P ₂₀. After deriving the relationships between P ₂₀ and the corresponding probability that P ₂₀ is not achieved, we demonstrated how such relationships could provide a kiln operator with information to facilitate better decision-making in optimizing a drying schedule.     

Acoustic evaluation of loblolly pine tree- and lumber-length logs allows for segregation of lumber modulus of elasticity,not for modulus of rupture

Key message

Loblolly pine ( Pinus taeda ) logs can be evaluated using acoustic velocity whereby threshold acoustic velocity values can be set to ensure lumber meets specified mechanical property design values for modulus of elasticity.

Context

There is a need to better sort logs according to lumber quality for improved decision making and wood utilization because merchantable logs are being harvested from different stand types including natural forests, conventional plantations, and intensively managed plantations, all with differences in rotation ages, growth rates, and wood quality traits.

Aims

This study aimed to link tree- and lumber-length log acoustic velocity with the resulting lumber properties as tested in static bending from five intensively managed loblolly pine stands in the Atlantic Coastal Plain of Georgia.

Methods

Acoustic velocity was measured using the resonance-based approach on 87 tree-length logs and 244 lumber-length logs. The logs were then processed into 797 pieces of 38 mm by 89 mm (2×4), 140 mm (2×6), 184 mm (2×8), and 235 mm (2×10) dimension lumber, dried, and tested in static bending.

Results

Mean MOE of the lumber had moderate relationships with acoustic velocity of the logs (R ² = 0.49) whereas MOR and acoustic velocity did not have a strong relationship (R ² = 0.20). Accounting for log position increased the performance of the mean lumber MOE model (R ² = 0.62) which was further increased by adding green density and small-end diameter (R ² = 0.67). Utilization of acoustics was effective for segregating logs based on lumber modulus of elasticity and did not depend on knowing tree or stand information such as age, site quality, and silviculture history.

Conclusion

Acoustic velocity evaluation of tree- and lumber-length logs could be employed to segregate logs within the supply chain to ensure that lumber would meet specified design values.