RT info:eu-repo/semantics/article
T1 Modulus of elasticity prediction through transversal vibration in cantilever beams and ultrasound technique of different wood species
A1 Acuña Rello, Luis
A1 Martínez López, Roberto Diego
A1 Spavento, Eleana
A1 Casado Sanz, María Milagrosa
A1 Álvarez Martínez, Javier
A1 O'Ceallaigh, Conan
A1 M. Harte, Annette
A1 Balmori Roiz, José Antonio
A2 Elsevier
K1 Madera
K1 Timber
K1 Non-destructive testing techniques
K1 Ultrasounds Transversal vibration
K1 Dynamic modulus of elasticity
K1 Madera
K1 Técnicas de ensayos no destructivos
K1 Ultrasonidos vibraciones transversales
K1 Módulo dinámico de elasticidad
K1 3106 Ciencia Forestal
AB 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%.
SN 0950-0618
YR 2023
FD 2023
LK https://uvadoc.uva.es/handle/10324/58806
UL https://uvadoc.uva.es/handle/10324/58806
LA eng
NO Construction and Building Materials, Volume 371, 2023, 130750
NO Producción Científica
DS UVaDOC
RD 24-nov-2024