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Modulus of elasticity prediction through transversal vibration in cantilever beams and ultrasound technique of different wood species.
- Source :
-
Construction & Building Materials . Mar2023, Vol. 371, pN.PAG-N.PAG. 1p. - Publication Year :
- 2023
-
Abstract
- • Transversal vibrations in cantilever beams are a good predictor of MOE of wood. • MOE prediction by transversal vibrations was more accurate than ultrasound method. • Five wood species with a wide density range (243 kg/m3 to 766 kg/m3) were tested. • This method could be further developed into a useful tool for timber grading. The prediction of the modulus of elasticity (MOE) of five species of different spectrum density woods, namely, Populus × euramericana I-214 (Poplar), Fagus sylvatica L. (Beech), Quercus pyrenaica L. (Oak), Paulownia elongata S.Y.Hu (Paulownia) and Pinus sylvestris L. (Scots pine) were examined through the natural frequency of vibration on cantilevered beams (transverse direction) and ultrasound (longitudinal direction). Cantilever beams are commonly used for other materials but limited information is available for wood materials tested in this manner. A total of 60 specimens with nominal dimensions of 40 × 60 × 1200 mm3 were tested, which were visually graded according to UNE 56544:2022 and UNE 56546:2022 as first class, and finally the global bending stiffness was obtained from a four-point bending test. Utilising this data, a regression model was presented to predict the MOE. Also, Picea sitchensis Trautv. & G.Mey (Sitka spruce) has been chosen as a blind species in order to validate the regression model of prediction of the MOE as a function of the dynamic MOE by ultrasound. Bending strength, modulus of elasticity and density were obtained according to the EN 408. In the prediction model using the dynamic MOE with vibrations, an r2 of 95.9% was achieved for the induced vibration technique which was found to be slightly higher than the model for the ultrasound prediction which had an r2 of 93.7%. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09500618
- Volume :
- 371
- Database :
- Academic Search Index
- Journal :
- Construction & Building Materials
- Publication Type :
- Academic Journal
- Accession number :
- 162256039
- Full Text :
- https://doi.org/10.1016/j.conbuildmat.2023.130750