This project was concluded in January 2019.
Project information
Project manager
Anders Olsson
Other project members
Jan Oscarsson, Andreas Briggert, Bertil Enquist
Participating organizations
Linnaeus University, KK-stiftelsen (The Knowledge Foundation), Derome Timber AB, L.O.A.B., Microtec Brixen, Moelven Töreboda AB, Rörvik Timber Myresjö AB, Södra Innovation, Vida Wood AB, WoodEye AB
Financier
KK-stiftelsen (The Knowledge Foundation), the participating companies and Linnaeus University
Timetable
Febr 2016-Jan 2019
Subject
Building Technology (Department of Building Technology, Faculty of Technology)
More about the project
This research, aiming at development of accurate methods for machine strength grading of glulam lamellae, is based on a previous project in which an efficient, reliable method of strength grading of structural timber has been developed in collaboration between researchers and companies. In both cases, the grading is based on knowledge of fibre orientation on the surfaces of the timber, on knowledge of axial resonance frequency and mass, as well as on calculations and algorithms by which strength is predicted on the basis of measures of local stiffness. A difference between structural timber and glulam laminations is that for structural timber it is more important to predict bending strength, whereas for glulam lamellae it is more important to predict tensile strength.
The aim of the project is also to contribute to the development of more advanced models of timber than those available today. Future timber models to be used in grading and production should include details of how the individual member is sawn out from the log, the annual ring pattern and density locally in the board, spiral grain, occurrence of top rupture and compression wood, the location and geometry of the knots in 3D, and the local fibre orientation inside the board.
The strategy of the research is to utilize more and more of the detailed information that can be obtained through laser scanning, color scanning, X-ray and dynamic excitation, and combine this information with knowledge of the anatomy of the wood material and its connection with the timber's structural-mechanical properties. Models for individual boards that can be developed and analyzed in real time, already during the production at sawmills, will in the end help to make wood an even more competitive construction material than it is today.
The project is part of the research in the Wood Building Technology research group.
Staff
