Machine learning-based prediction of internal checks in weathered thermally modified timber-Reference-Cited by-同舟云学术

Machine learning-based prediction of internal checks in weathered thermally modified timber

Published:2021-04 Issue: Volume:281 Page:122193
ISSN:0950-0618
Container-title:Construction and Building Materials
language:en
Short-container-title:Construction and Building Materials

Author:

van Blokland Joran,Nasir Vahid^ORCID,Cool Julie,Avramidis Stavros,Adamopoulos Stergios^ORCID

Publisher

Elsevier BV

Subject

General Materials Science,Building and Construction,Civil and Structural Engineering

Reference67 articles.

1. Evolution of thermally modified wood properties exposed to natural and artificial weathering and its potential as an element for façades systems;Herrera;Constr. Build. Mater.,2018

2. Performance of thermally modified spruce timber in outdoor above-ground conditions: checking, dynamic stiffness and static bending properties;van Blokland;Appl. Sci.,2020

3. R.M. Rowell, R.E. Ibach, J. McSweeny, T. Nilsson, Understanding decay resistance, dimensional stability and strength changes in heat treated and acetylated wood, the 4th European Conference on Wood Modification, Stockholm, Sweden, 2009, pp. 489-502.

4. H. Militz, Thermal treatment of wood: European processes and their background, the International Reserach Group on Wood Protection, Doument No. IRG/WP/02-40241, Stockholm, Sweden, 2002.

5. Wood modification by heat treatment: a review;Esteves;Bioresources,2009

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