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Three-dimensional modelling of knots and pith location in Norway spruce boards using tracheid-effect scanning
Linnaeus University, Faculty of Technology, Department of Building Technology.ORCID iD: 0000-0003-4518-570X
Linnaeus University, Faculty of Technology, Department of Building Technology.ORCID iD: 0000-0002-6410-1017
Linnaeus University, Faculty of Technology, Department of Building Technology.ORCID iD: 0000-0002-8513-0394
2016 (English)In: European Journal of Wood and Wood Products, ISSN 0018-3768, E-ISSN 1436-736X, Vol. 74, no 5, p. 725-739Article in journal (Refereed) Published
Abstract [en]

Knots and the orientation of fibres in timber are decisive for the stiffness and strength of boards. Due to large property variations between members, strength grading is necessary. High resolution information of the orientation of fibres, both on surfaces and within members, would enable development of more accurate grading methods than those available today. A step towards three-dimensional (3D) models of the fibre orientation of the entire board volume is the establishment of 3D knot models based on scanning. The light from a dot laser illuminating the surface of a softwood board will, due to the tracheid effect, spread more along the fibres than across resulting in the dot entering an elliptical shape. In this investigation both the shape of the ellipse and the direction of its major axis were used to estimate the 3D fibre orientation on board surfaces. Knot surfaces were identified where the angle between the estimated 3D fibre direction and an approximated direction of the board’s pith exceeded a threshold value. By means of algorithms based on polar coordinates, knot surfaces which belonged to the same physical knot visible on different sides of the board were identified and as a result the position, orientation and volume of each knot were determined. Based on this information, a more accurate position of the board’s pith along the board was calculated. The established models showed good agreement with physical boards. The models constitute a promising starting point for further development of strength grading methods based on tracheid-effect scanning.

Place, publisher, year, edition, pages
2016. Vol. 74, no 5, p. 725-739
National Category
Wood Science Paper, Pulp and Fiber Technology Building Technologies
Research subject
Technology (byts ev till Engineering), Civil engineering; Technology (byts ev till Engineering), Forestry and Wood Technology
Identifiers
URN: urn:nbn:se:lnu:diva-56067DOI: 10.1007/s00107-016-1049-7ISI: 000380689900010Scopus ID: 2-s2.0-84982063018OAI: oai:DiVA.org:lnu-56067DiVA, id: diva2:971467
Available from: 2016-09-16 Created: 2016-08-31 Last updated: 2020-05-04Bibliographically approved
In thesis
1. Modelling and strength grading of structural timber and glulam lamellae on the basis of optical scanning and dynamic excitation
Open this publication in new window or tab >>Modelling and strength grading of structural timber and glulam lamellae on the basis of optical scanning and dynamic excitation
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Machine strength grading of sawn timber is a sawmill process in which density, modulus of elasticity (MOE) and bending or tensile strength are predicted such that the timber can be assigned to strength classes. The predictions of these properties are performed using one or several so-called indicating properties (IPs), which represent a board property, or combination of board properties, measured non-destructively. A limitation of today’s strength grading is that the IPs applied in the industry for prediction of strength, in general, are based on rather weak statistical relationships between IPs and strength properties, which in turn results in poor material utilisation. It is well known that the strength of sawn timber is associated with the presence of knots and their surrounding fibre disorientations. Local fibre direction at surfaces of softwood can be determined by means of the light scattering that occur when a wood surface is illuminated by a dot-laser, i.e. by application of the so-called tracheid effect. Lately, IPs based on such measurements have been developed, and some of the suggested IPs have a strong statistical relationship to bending strength. The purposes of the research presented in this thesis are to contribute with knowledge of possibilities and limitations of the tracheid effect and of data of fibre directions in the vicinity of knots, to evaluate if information of fibre directions at surfaces of Norway spruce sawn timber can be used to achieve a better material utilisation of glulam lamellae and finger-jointed timber, and to provide insight regarding the grading regulations in Europe. Results presented herein show that knots and fibre direction within the interior of boards can be modelled on the basis of data obtained by means of the tracheid effect, but also that a previously proposed method to determine out-of-plane fibre angles gives poor accuracy. As regards grading of glulam lamellae, an IP based on fibre directions and dynamic MOE is proposed for prediction of tensile strength. The latter is used when grading glulam lamellae. Application of the proposed IP resulted in substantially increased yield in strength classes. It is also shown that this IP is applicable for boards with sawn as well as with planed surface finish. Regarding current regulations for machine strength grading in Europe, results indicate that grading based on global board properties give higher yield than what is appropriate.

Place, publisher, year, edition, pages
Växjö: Linnaeus University Press, 2020. p. 68
Series
Linnaeus University Dissertations ; 380/2020
Keywords
Fibre direction, finger joint, machine strength grading, knots, tracheid effect, Norway spruce
National Category
Other Civil Engineering
Research subject
Technology (byts ev till Engineering), Civil engineering
Identifiers
urn:nbn:se:lnu:diva-94126 (URN)978-91-89081-47-5 (ISBN)978-91-89081-48-2 (ISBN)
Public defence
2020-04-29, N1017, P G Vejdes väg, Växjö, 10:00 (English)
Opponent
Supervisors
Available from: 2020-05-04 Created: 2020-05-04 Last updated: 2025-02-25Bibliographically approved

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Briggert, AndreasOlsson, AndersOscarsson, Jan

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