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Local variation of modulus of elasticity in timber determined on the basis of non-contact deformation  measurement and scanned fibre orientation
Linnaeus University, Faculty of Technology, Department of Building Technology.
Linnaeus University, Faculty of Technology, Department of Building Technology.ORCID iD: 0000-0001-5319-4855
Linnaeus University, Faculty of Technology, Department of Building Technology.ORCID iD: 0000-0002-6410-1017
SP Tech Res Inst Sweden, SP Wood Technol, Växjö.ORCID iD: 0000-0002-8513-0394
Show others and affiliations
2015 (English)In: European Journal of Wood and Wood Products, ISSN 0018-3768, E-ISSN 1436-736X, Vol. 73, no 1, p. 17-27Article in journal (Refereed) Published
Abstract [en]

During the last decade, the utilization of non-contact deformation measurement systems based on digital image correlation (DIC) has increased in wood related research. By measuring deformations with DIC systems, surface strain fields can be calculated. The first aim of this study concerns the possibility to detect detailed strain fields along the entire length of a wooden board subjected to pure bending and the potential of using such strain fields to determine a bending modulus of elasticity (MOE) profile along a board. Displacements were measured over 12 subareas along a flat surface of the board. For each such area, a separate local coordinate system was defined. After the transformation of locally measured coordinates to a global system, high resolution strain fields and a corresponding bending MOE profile were calculated. A second method in establishing bending MOE profiles is to use fibre angle information obtained from laser scanning and a calculation model based on integration of bending stiffness over board cross sections. Such profiles have recently been utilized for accurate strength grading. A second aim of this study was to investigate the accuracy of the bending MOE profiles determined using the latter method involving fibre angle information. Bending MOE profiles determined using the two described methods agree rather well. However, for some patterns of knot clusters, the local bending MOE, calculated on the basis of fibre angles and integration of bending stiffness, is overestimated. Hence, this research adds knowledge that may be utilized to improve the newly suggested strength grading method.

Place, publisher, year, edition, pages
Springer, 2015. Vol. 73, no 1, p. 17-27
National Category
Construction Management
Research subject
Technology (byts ev till Engineering), Civil engineering
Identifiers
URN: urn:nbn:se:lnu:diva-38089DOI: 10.1007/s00107-014-0851-3ISI: 000347688100002Scopus ID: 2-s2.0-84920552031OAI: oai:DiVA.org:lnu-38089DiVA, id: diva2:761725
Available from: 2014-11-07 Created: 2014-11-07 Last updated: 2019-10-17Bibliographically approved
In thesis
1. Local variation in bending stiffness in structural timber of Norway spruce: for the purpose of strength grading
Open this publication in new window or tab >>Local variation in bending stiffness in structural timber of Norway spruce: for the purpose of strength grading
2014 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Most strength grading machines on the European market use an averagemodulus of elasticity (MOE), estimated on a relatively large distance along awood member, as the indicating property (IP) to bending strength. Theaccuracy of such grading machines in terms of coefficient of determination israther low at R2 ≈ 0.5. This research is motivated by a desire to increase theaccuracy of the strength grading in the industry today. The aim of the presentstudy is to contribute knowledge of local variation in bending stiffness/MOEwith high resolution and thus locate weak sections due to stiffness reducingfeatures (the most important is knots) for structural timber.The present study introduces three methods that involve structural dynamics,classical beam theory and optical measurement to assess local wood stiffness.Specifically:

  • The dynamic method, in which a wood member is treated as an ordinaryphysical structure and the local stiffness is studied by exploring itsdynamic properties.
  • In Method II, a bending MOE profile is established based on local fibre angle information. The local fibre orientation is detected through highresolution laser scanning based on the tracheid effect.
  •  For Method III, a bending MOE profile is established using surfacestrain information under four-point bending. A high resolution strainfield is obtained using the digital image correlation (DIC) technique.

From the present study, the two latter methods are more favourable inevaluating the local stiffness within a piece of structural timber. Moreover, thestudy reveals that the established bending MOE profiles using the two lattermethods, i.e. based on information of the local fibre angle and surface strain,agree reasonably well. However, for some patterns of knot clusters, the localbending MOE, calculated on the basis of fibre angles, is significantly higherthan the local bending MOE estimated on the basis of surface strain.

Abstract [sv]

De flesta av de utrustningar för hållfasthetssortering som utnyttjas på deneuropeiska marknaden använder ett medelvärde på elasticitetsmodulen(MOE), beräknat på en relativt stor längd av en sågad planka, som indikativparameter (IP). Sådan hållfasthetssortering ger en noggrannhet i termer avförklaringsgrad på R2 ≈ 0.5, vilket är ganska lågt. Arbetet i denna studiemotiveras av en önskan att öka noggrannheten i hållfasthetssorteringen. Syftetmed denna studie är att bidra med kunskap om lokala variationer iböjstyvhet/MOE med hög upplösning och att lokalisera veka snitt (där kvistarär den viktigaste försvagande faktorn) för konstruktionsvirke.Den aktuella studien introducerar tre metoder som omfattar strukturdynamik,klassisk balkteori och optisk mätning vid bedömningen av lokal styvhet imaterialet. Specifikt:

  •  Metod I, där den lokala böjstyvheten studerades genom de dynamiskaegenskaperna såsom egenfrekvens och modform.
  •  Metod II, där en MOE profil beräknas på basis av information om lokalafibervinklar på ett virkesstyckes ytor. Den lokala fiberorienteringen mätsmed högupplöst laserskanning baserad på den så kallade trakeideffekten.
  •  Metod III, där en MOE-profil fastställdes med hjälp avtöjningsinformation för en hel flatsida av en planka belastad med konstantböjmoment. Det högupplösta töjningsfältet erhölls med hjälp av teknikför Digital Image Correlation (DIC).

Studien visar att de två sistnämnda metoderna är mycket lämpade för attutvärdera den lokala styvheten i ett virkesstycke. Dessutom visar studien att deMOE-profiler som togs fram med hjälp av de två sistnämnda metoderna,vilka baseras på information om lokala fibervinklar och töjningsfältet på ytan,stämde överens för större delen av virkesstycket. För visa kvistgrupper kan dock den lokala böjstyvheten högre med metoden baserad på fibervinklar.

Place, publisher, year, edition, pages
Linnaeus University, Department of Building Technology, 2014. p. 67
Keywords
digital image correlation, fibre angle, high resolution, laser scanning, local stiffness, MOE profile, mode shape curvature, strain field, strength grading, structural timber, tracheid effect, Digital image correlation, fibervinkel, laserskanning, lokal styvhet, MOE-profil, töjningsfält, hållfasthetssortering, konstruktionsvirke, trakeideffekt
National Category
Wood Science Construction Management
Research subject
Technology (byts ev till Engineering), Forestry and Wood Technology
Identifiers
urn:nbn:se:lnu:diva-38119 (URN)
Supervisors
Available from: 2014-12-02 Created: 2014-11-11 Last updated: 2014-12-02Bibliographically approved
2. Studies of the fibre direction and local bending stiffness of Norway spruce timber: for application on machine strength grading
Open this publication in new window or tab >>Studies of the fibre direction and local bending stiffness of Norway spruce timber: for application on machine strength grading
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Machine strength grading is a production process in the sawmill industry used to grade sawn timber boards into different strength classes with specific characteristic values of the bending strength, modulus of elasticity (MOE) and density. These properties are called grade determining properties. Each of these is predicted on the basis of a statistical relationship between the property and a so-called indicating property (IP), which is based on non-destructively assessed board properties. In most cases, the prediction of strength is crucial for the grading. The majority of commercial grading machines rely on a statistical relationship of strength to an IP, which is either a global dynamic MOE or an averaged flatwise bending MOE measured over a board length of about one meter. The problem of today’s machine strength grading is that the accuracy of the strength prediction is rather poor with a coefficient of determination of about R2 ≈ 0.5 − 0.6. One consequence of this is that much of the strength potential of timber is unused.

The intention of this research is to contribute to a long-term goal, which is development of a method for prediction of bending strength that is more accurate than the methods available today. The research relies on three hypotheses. First, accurate prediction of bending strength can be achieved using an IP that is a localized MOE value (determined over a short length) that represents the lowest local bending stiffness of a board. Second, knowledge of the local bending stiffness with high resolution along a board’s longitudinal direction can be established on the basis of fibre direction within the board in combination with dynamic MOE. Third, fibre directions in the interior of a board can be determined by application of fibre angle models utilizing data of fibre directions on the board’s surfaces obtained from tracheid effect scanning. Following these hypotheses, this work has included laboratory investigations of local material directions, and development of models for fibre directions of the interior of boards. The work also included application of one-dimensional (1D) analytical models and three-dimensional (3D) finite element models of individual boards for the mechanical behaviour, analysis of mechanical response of boards based on experiments and based on the suggested models. Lastly, the suggested models were evaluated by comparisons of calculated and experimentally determined local bending stiffness along boards, and of predicted and experimentally determined bending strength.

The research contributes with in-depth knowledge on local fibre directions close to knots, and detailed information on variation of the local bending stiffness in boards. Moreover, fibre angle models for fibre directions in the interior of boards are presented. By application of the fibre angle models in the 3D model of the whole board, the local bending stiffness along timber boards can be determined over a very short length (l < 50 mm). A comparison with results determined on an experimental basis show a very close similarity implying that the applied models are sufficient to capture the variation of local bending stiffness, caused by knots and fibre distortions, with very high accuracy. Furthermore, it is found that by means of IPs derived using the suggested models, bending strength can be predicted with high accuracy. For a timber sample comprising 402 boards, such IPs results in coefficient of determination as high as R2 = 0.73. However, using IPs based on the 3D finite element model did not improve the R2 value achieved when using the IPs based on the 1D model.

Place, publisher, year, edition, pages
Växjö: Linnaeus University Press, 2018
Series
Linnaeus University Dissertations ; 307/2018
Keywords
digital image correlation, diving angle, fibre angle, grain angle, indicating property, laser scanning, modulus of elasticity, tracheid effect
National Category
Wood Science
Research subject
Technology (byts ev till Engineering), Forestry and Wood Technology
Identifiers
urn:nbn:se:lnu:diva-69636 (URN)978-91-88761-13-2 (ISBN)978-91-88761-14-9 (ISBN)
Public defence
2018-02-01, N1017, Hus N, Växjö, 10:00
Opponent
Supervisors
Available from: 2018-01-10 Created: 2018-01-09 Last updated: 2018-01-17Bibliographically approved

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Hu, MinJohansson, MarieOlsson, AndersOscarsson, JanEnquist, Bertil

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