Strength grading of structural timber

Fortuna, Barbara; Plos, Mitja; Šuligoj, Tamara; Turk, Goran

doi:10.31534/co/zt.2018.09

Cited by 4 publications

(7 citation statements)

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“…Both studies are thus in the range of the entire dataset with 13.0 GPa and dataset KH with 13.8 GPa. The study of Ehrhart et al (2016) exhibited a tensile MoE of 14.5 GPa and Fortuna et al (2018) observed a mean tensile MoE of 15.5 GPa, which is similar to dataset SP with 15.1 GPa.…”

Section: Visual Physical and Mechanical Properties Of Beech Lamellassupporting

confidence: 56%

“…Ehrhart et al ( 2016) described a mean tensile strength of 66.7 MPa, which can be explained by higher material quality than in dataset CB, KH and SP. Fortuna et al (2018) found a mean tensile strength of 72.1 MPa that could not be compared with the tensile strengths of datasets CB, KH and SP as distributions of material parameters were not given in the study. The higher mean tensile strength in the study of Frühwald and Schickhofer (2005) of 62.2 MPa compared to datasets CB, KH and SP could not be clarified with the given data but may result from better material quality.…”

Section: Visual Physical and Mechanical Properties Of Beech Lamellasmentioning

confidence: 89%

“…Ehrhart et al (2016) defined new grading rules for Swiss beech lamellas of T-class T22 or higher based on a combined grading approach with knot parameter tKAR and MoE dyn . Fortuna et al (2018) observed tensile strength and MoE as well as non-destructive properties of a representative sample of Slovenian beech lamellas from mainly C and D log-quality according to EN 1316-1:2012(CEN 2012b. The lamellas were graded into T-classes by means of MoE dyn .…”

Section: Introductionmentioning

confidence: 99%

“…The lamellas were graded into T-classes by means of MoE dyn . Plos et al (2018) graded the lamellas from Fortuna et al (2018) visually according to DIN 4074-5:2008(DIN 2008 and found high reject rates as well as inefficient strength class allocation. Schlotzhauer et al (2018) observed visual and machine strength grading characteristics for beech lamellas cut from C and D quality logs.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Tensile strength grading of beech (Fagus sylvatica L.) lamellas from multiple origins, cross sections and qualities

et al. 2022

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The market share of European beech (Fagus sylvatica L.) wood in the construction sector is low despite an increase in beech stock in Central European Forests in recent years. More efficient sawing techniques, higher lamella grading yields and solving of adhesion challenges may increase the competitiveness of beech glulam and promote its use. The aim of this paper is to revise the lamella grading system in the current German technical approval for beech glulam Z-9.1-679:2019 (DIBt (2019). BS-Holz aus Buche und BS-Holz Buche Hybridträger und zugehörige Bauarten. Allgemeine bauaufsichtliche Zulassung Z-9.1-679:2019. Deutsches Institut für Bautechnik) and to suggest modifications in the lamella grading rules for glulam production allowing higher yields and reliable tensile strength values at the same time. The unique dataset in this study combined different origins of lamellas and covered a wide range of visual, physical and mechanical wood characteristics including a high amount of low quality material. Indicating properties (IPs) for tensile strength, such as knot parameters and dynamic modulus of elasticity, were contrasted with tensile strength and static modulus of elasticity. Beech lamellas, graded by means of Z-9.1-679:2019 (DIBt (2019). BS-Holz aus Buche und BS-Holz Buche Hybridträger und zugehörige Bauarten. Allgemeine bauaufsichtliche Zulassung Z-9.1-679:2019. Deutsches Institut für Bautechnik), did not achieve the tensile strengths required for glulam production in many grading classes and the yield was low. A machine grading approach with dynamic modulus of elasticity as a single grading criterion gave higher yields than the current grading procedure and high reliability for tensile strength prediction with a prediction accuracy of R 2 = 0.67.

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Section: Visual Physical and Mechanical Properties Of Beech Lamellassupporting

confidence: 56%

Section: Visual Physical and Mechanical Properties Of Beech Lamellasmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Tensile strength grading of beech (Fagus sylvatica L.) lamellas from multiple origins, cross sections and qualities

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Therefore, the MOE can be calculated by using the stress wave velocity measurement (Steiger 1996;Bucur 2003;Baillères et al 2009). Some commercial NTD methods such as Hitman ST300 (Fibre-gen, Christchurch, New Zealand), Metriguard 7200 High Capacity Lumber Tester (HCLT, Metriguard Inc., Pullman, WA), E-computer Model 340 (Metriguard Inc.), portable Timber Grader MTG (Brookhuis Micro-Electronics), portable Lumber Grader PLG (Fakopp, Sopron, Hungary), and STIG grading machine (Slovenia) are already available for measuring mechanical properties of timber (Baltrušaitis et al 2009;Baillères et al 2012;Paradis et al 2013;Yang et al 2015;Fortuna et al 2018;Llana et al 2020). However, the most convenient method for measuring MOE non-destructively with high precision is the vibration method by measuring natural frequencies in different modes (longitudinal, flexion, or torsional) and the geometry and boundary conditions (Brancheriau and Baillères 2002;Arriaga et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Assessment of the application of a SMART THUMPER™ as a low-cost and portable device used for stiffness estimation of timber products

Kumar

Redman²,

Leggate³

et al. 2021

BioRes

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Non-destructive evaluation methods for timber stiffness are gaining increased interest as an alternative to static testing since they can be fast, cost-effective, and transportable, as well as non-destructive. The objective of this study was to evaluate the accuracy and limitations of a newly developed smartphone application (SMART THUMPER™) for the non-destructive evaluation of timber stiffness properties. The study determined the effect of the length, density (species), and cross-section sizes of the timber samples on the stiffness results. The results were compared to beam identification by non-destructive grading (BING©), an existing commercial non-destructive testing technology for evaluating the mechanical quality of wood and other materials. It was found that the application can be used to reliably estimate the stiffness of various timber products with a resonance frequency value below 2000 Hz. Frequencies greater than 2000 Hz were found to induce errors due to the smartphone microphone, which is engineered to acquire a lower frequency range. A reliability matrix providing an indication of the accuracy of SMART THUMPER™ estimation was presented, which may also prove useful in selecting appropriate sample lengths prior to testing. The sample length or dimensions can be manipulated to lower the frequency, and hence, to improve the results.

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Visual grading criteria for Japanese larch (Larix kaempferi) structural timber from Spain

Barriola¹,

Aira

Lafuente³

2019

J. For. Res.

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Strength grading of structural timber

Cited by 4 publications

References 0 publications

Tensile strength grading of beech (Fagus sylvatica L.) lamellas from multiple origins, cross sections and qualities

Tensile strength grading of beech (Fagus sylvatica L.) lamellas from multiple origins, cross sections and qualities

Assessment of the application of a SMART THUMPER™ as a low-cost and portable device used for stiffness estimation of timber products

Visual grading criteria for Japanese larch (Larix kaempferi) structural timber from Spain

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