Abstract

This study investigated possibilities to predict the presence of internal checks in thermally modified Norway spruce timber after 2.5 years of weathering based on the initial properties of the boards. Machine-learning classification enabled sorting the input parameters based on their relative importance for accurate predictions. The parameters of thermally modified timber with the highest relative importance were annual ring width followed by initial moisture content, density and dynamic stiffness. Whereas after kiln drying these were, density, annual ring width, initial moisture content and acoustic velocity. The results showed that predictions are possible, and an accuracy of 67% was achieved by using annual ring width combined with density and initial moisture content, or acoustic velocity that can be determined after either kiln drying or thermal treatment. (C) 2020 Published by Elsevier Ltd.

Keywords

Acoustic velocity; Decision tree; Non-destructive testing; Norway spruce; Outdoor above-ground exposure; Timber grading

Published in

Construction and Building Materials
2021, Volume: 281, article number: 122193
Publisher: ELSEVIER SCI LTD

SLU Authors

• Adamopoulos, Stergios

  • Department of Forest Biomaterials and Technology, Swedish University of Agricultural Sciences
    

Sustainable Development Goals

SDG12 Ensure sustainable consumption and production patterns


UKÄ Subject classification

Wood Science


Publication identifier

DOI: https://doi.org/10.1016/j.conbuildmat.2020.122193

Permanent link to this page (URI)

https://res.slu.se/id/publ/111566