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TitleAcoustic segregation of Australian-grown Pinus radiata logs for structural board production
Publication TypeJournal Article
Year of Publication2004
AuthorsDickson, R.L., Joe B., Harris P.D., Holtorf S., and Wilkinson C.
JournalAustralian Forestry
Pagination261 - 266
Date Published2004
ISSN00049158 (ISSN)
KeywordsAcoustic properties, Elastic moduli, Elastic Strength, elasticity, Forestry, Log grade, Outturn, Pinus Radiata, Stiffness, Stress grading, velocity, Wood, Wood products, Wood strength
AbstractThe wood quality of sawlogs is highly variable and poorly reflected by log physical dimensions. Current log grading rules for structural timber, based purely on physical appearance, result in a significant loss of value to growers and processors. Growers and processors both require tools that are able to rapidly sort logs to yield timber of a uniform quality. Ninety-two radiata pine (Pinus radiata) logs harvested from Green Hills State Forest, NSW, were measured at the Hyne and Son sawmill at Tumbarumba, NSW. Two non-destructive longitudinal stress wave acoustic devices, a FAKOPP single-pass transit-time tool and a WoodSpec resonance tool, were used to characterise the logs. The sampled logs were sorted into three sound speed classes: slow (<3.5 km s -1), medium (3.5-3.7 km s-1) and fast (>3.7 km s -1). The relationship between measurements of acoustic velocity in logs and the stiffness of the boards milled from the tested logs was established. The boards recovered from logs sorted into the fast sound class had a mean stiffness of 10.5 GPa. The boards recovered from the logs segregated in the medium and slow sound classes had mean stiffnesses of 9.3 GPa and 8.9 GPa, respectively. The acoustic segregation patterns were similar for each of the acoustic tools tested, with the coefficient of variation of repeated measurements with WoodSpec being 2.2% lower than with the FAKOPP, suggesting that the WoodSpec tool was more precise. This study indicates that acoustic measurement of wood stiffness in the field and in the mill may improve value recovery.

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