Prediction of tensile strength of sawn timber: definitions and performance of indicating properties based on surface laser scanning and dynamic excitation

Briggert, Andreas; Olsson, Anders; Oscarsson, Jan

doi:10.1617/s11527-020-01460-5

Cited by 17 publications

(34 citation statements)

References 8 publications

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“…The results presented in this series of two papers are based on a full-scale investigation aiming at deriving IPs and determining settings and yield for T-classes using a grading method similar to the one presented in [11]. The aims of the first paper [3] (Part 1) were to evaluate the statistical relationship between suggested IPs and GDPs for a sample including a total number of 967 boards and to evaluate if it was possible to utilise in-plane fibre directions obtained when laser scanning sawn rather than planed board surfaces for accurate grading. The aims of the current paper are to • present two different, applicable procedures for determination of settings for grading methods based on IPs reflecting local board properties, • determine settings for T-classes using IP E,b for strength, E dyn,12% for MOE and q s,12% for density and show how the yield in different strength classes depend on the procedure used for determination of settings and • discuss implications of the results presented on machine strength grading standards.…”

Section: Purpose and Aimsmentioning

confidence: 99%

“…The timber used in this investigation were divided into five sub-samples: Finland, Norway, south Sweden, mid Sweden and north Sweden. A thorough description of sampling procedure, origin of boards, board dimensions, number of boards in each sub-sample and number of boards of each dimension is given in [3].…”

Section: Calculation Of Settings and Yieldmentioning

confidence: 99%

“…Bending strength and tensile strength, the former a GDP for C-and D-classes and the latter, as mentioned previously, a GDP for T-classes, are the GDPs most difficult to predict [4], and are as shown in [5,6] decisive for the yield of strength classes. For the sample used in this investigation, the best predictions of f t,0,h were achieved using IP E,b for which coefficients of determination of 0.65 and 0.66 (linear regression) were reached using data from measurements obtained before and after planing of boards, respectively [3]. For prediction of E t,0,12% , application of the three IPs E dyn,12% , IP E,a and IP E,b resulted in similar coefficients of determination, just above 0.8 both before and after planing.…”

Section: Introductionmentioning

confidence: 99%

“…The second part consists of determining thresholds for the IPs, or settings as it is referred to in the standards, such that all the minimum requirements of characteristic values of a graded class are fulfilled, if boards with IPs that exceed the determined settings are assigned to the class. In Prediction of tensile strength of sawn timber: Definitions and performance of indicating properties based on surface laser scanning and dynamic excitation [3] the GDPs for T-classes, i.e. tensile strength (f t,0,h ), density (q 12% ) and tensile MOE (E t,0,12% ), and several IPs were defined.…”

Section: Introductionmentioning

confidence: 99%

“…As regards suggested IPs, [3] includes a detailed description of the non-destructive measurements carried out in this investigation. The machine measurements consisted of surface laser scanning, X-ray scanning and dynamic excitation for determination of boards' in-plane fibre directions at longitudinal surfaces and dimensions, local densities and first axial resonance frequency, respectively.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of tensile strength of sawn timber: models for calculation of yield in strength classes

2020

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In Europe, strength classes for structural timber and glulam lamellae are defined by minimum requirements of characteristic values of the grade determining properties (GDPs). To fulfill these minimum requirements of characteristic values in the daily production at sawmills, indicating properties (IPs) to GDPs are calculated for each board and based on predetermined limits of the IPs (settings) boards are assigned to the graded class, or rejected. The aims of this paper is to address and discuss two different grading procedures/models that can be applied when settings for IPs that reflects a local board property are derived and to show how the yield in different T-classes depend on the model applied. It is not always that a board's weakest cross-section is evaluated in a destructive test. An IP representing a local board property can therefore be determined either as the lowest property of the tested part of the board or as the lowest property along the whole board when applied to derive settings. Results presented in this paper show that too low settings and too large yields are obtained when the latter IP is employed. Similarly, IPs reflecting a global board property, like axial dynamic MOE, also give too low settings and too high yield in strength classes. This paper is the second and closing part of a series of two paper on prediction of GDPs and procedures for grading sawn timber into T-classes. Keywords Grading of timber Á Laser scanning Á Fibre direction Á Dynamic modulus of elasticity Á Norway spruce List of symbols E a,90,nom Lowest local axial modulus of elasticity (MOE) of the destructivly tested part of the board, calculated on the basis of observed fibre directions E a,90,nom,test Lowest local axial MOE of the destructivly tested part of the board, calculated on the basis of observed fibre directions, i.e. E a,90,nom,test = E a,90,nom E a,90,nom,whole Lowest local axial MOE of the whole board, calculated on the basis of observed fiber directions E b,90,nom Lowest local bending MOE of the destructivly tested part of the board, calculated on the basis of observed fibre directions

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Section: Purpose and Aimsmentioning

confidence: 99%

Section: Calculation Of Settings and Yieldmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Prediction of tensile strength of sawn timber: models for calculation of yield in strength classes

2020

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The relationship between bending and tension strength of Irish and UK spruce and pine

et al. 2022

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The correct characterisation of wood properties is fundamental for the best utilisation of resources. In Europe, grading is defined by strength classes that are determined based on either bending or tension tests. The European standards give equations to estimate characteristic strength in tension from characteristic strength in bending, and vice versa depending on which was tested. These equations are applied to all softwoods. The aim of this paper is to empirically determine the relationship between bending and tension strength properties using two conifer species grown in Ireland and the UK. The results show that the relationships change with species. The standard conversion underestimates, importantly, the performance of spruce for tension loads calculated for the most common bending strength class for Ireland and the UK, C16. The opposite occurs on the reverse conversion. Additionally, the study includes published data from continental Europe, to establish a new conversion that uses timber from a broader range of grades, and that adjusts the tension performance of Irish and UK spruce obtained from bending strength classes, ensuring safe values for design.

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Relationships between stiffness of material, lamellas and CLT elements with respect to out of plane bending and rolling shear

et al. 2023

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The use of cross laminated timber (CLT) for construction has increased greatly in recent years and the large volumes of wood used for CLT means that it is important to optimize the use of the material. This requires relevant grading of lamellas and knowledge of relationships between lamella and CLT properties. In the present study, the relationship between dynamic axial modulus of elasticity (MoE) of lamellas and the quasi-static out of plane bending stiffness of CLT is investigated. By means of four-point bending test, it is shown that the effective quasi-static MoE of lamellas in CLT is only 2–6% lower than the average axial dynamic MoE of the individual lamellas. With this knowledge, producers of CLT can easily predict and control the important out of plane bending stiffness of the produced CLT. Moreover, it is shown that effective rolling shear stiffness of layers in CLT can be accurately determined by means of digital image correlation performed in connection to four-point bending of CLT, even for long test spans. For layers of lamellas of Scots pine of size 40 × 190 mm2 the average apparent or effective rolling shear modulus was determined to be 159 MPa. The average rolling shear modulus of the same material was determined to be 56 MPa.

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Prediction of tensile strength of sawn timber: definitions and performance of indicating properties based on surface laser scanning and dynamic excitation

Cited by 17 publications

References 8 publications

Prediction of tensile strength of sawn timber: models for calculation of yield in strength classes

Prediction of tensile strength of sawn timber: models for calculation of yield in strength classes

The relationship between bending and tension strength of Irish and UK spruce and pine

Relationships between stiffness of material, lamellas and CLT elements with respect to out of plane bending and rolling shear

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