Comparison of moisture-dependent orthotropic Young’s moduli of Chinese fir wood determined by ultrasonic wave method and static compression or tension tests

Jiang, Jiali; Bachtiar, Erik Valentine; Lu, Jianxiong; Niemz, Peter

doi:10.1007/s00107-017-1269-5

Cited by 13 publications

(8 citation statements)

References 23 publications

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“…With the increasing moisture content of 5%-30%, the compressive yield strength decreased. The same results were reported by Ozyhar et al [28] and Jiang et al [29] within the moisture of 0-16.3% and 10.3%-16.7%, respectively. Because water enters the amorphous region of the wood, making the percentage of cell walls per unit area decreases and the distance between the molecular chains expands, the connection between molecular chains is more likely to slip or break due to compressive stress, so the wood fibers are more prone to plastic deformation.…”

Section: Compressive Yield Strength Of Beech Wood With Different Mois...supporting

confidence: 88%

“…The moisture sensitivity of MOE of longitude (El) was smaller than that of transverse (Er and Et). Previous studies [12,28,29] also demonstrated that Er and Et were influenced by moisture to a higher degree than the El. Then, the results obtained from Table 9 supported the idea that the moisture sensitivity of compressive yield strength was higher than the compressive stiffness, overall.…”

Section: Moisture Sensitivity Of Different Elastic Constants Of Beech...mentioning

confidence: 81%

“…Güntekin and Aydın [34] reported that the ratio is 23.44:3.58:1 of Anatolian black pine wood. Data from the study of Jiang et al [29] suggested the ratio was 20.39:1.39:1 of Chinese fir wood. The ratio in the study of Güntekin et al [35] was 8.5:1.6:1 of sessile oak wood.…”

Section: Compressive Elastic Contents Of Beech Wood With Different Mo...mentioning

confidence: 98%

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Effects of Moisture Content and Grain Direction on the Elastic Properties of Beech Wood Based on Experiment and Finite Element Method

Guan

Kei

2021

Forests

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Beech wood (Fagus sylvatica L.) is used in a wide range of wood products. However, the influence of the wood’s moisture content on its mechanical functions will affect its structural strength. It would be complicated and time-consuming to experimentally measure wood’s mechanical functions under different moisture contents. Therefore, it is necessary to establish a prediction formula between the moisture content and elastic constants, and then verify whether its mechanical functions within a wide range of moisture content can be studied by using FEM (finite element method). In this study, which was based on experimentation, we studied the influence of a wide range of moisture contents and grain direction on the compressive yield strength, modulus of elasticity and shear modulus of beech wood. The relationship between the moisture content and elastic constants was established; the moisture sensitivities of different elastic parameters were obtained. Ultimately, compression curves under different moisture contents were plotted out, using both FEM and experimentation. According to the results, the interaction of moisture with the grain direction had a significant effect on the elastic constants of wood, with grain direction having a greater effect on the elastic properties than the moisture content. Moreover, the decay function can be used to fit these experimental results well. The elastic constants of beech wood responded differently to the moisture content, depending on whether it was in the longitude or transverse directions. Finally, this study proved the feasibility of using FEM to simulate wood’s compressive performance with a wide range of moisture contents.

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Section: Compressive Yield Strength Of Beech Wood With Different Mois...supporting

confidence: 88%

Section: Moisture Sensitivity Of Different Elastic Constants Of Beech...mentioning

confidence: 81%

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Effects of Moisture Content and Grain Direction on the Elastic Properties of Beech Wood Based on Experiment and Finite Element Method

Guan

Kei

2021

Forests

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“…The decrease in the wave velocity with the UV exposure time cannot be solely explained by the variation of the MC, as it is known that the acoustic wave velocity decreases with the MC level. [59][60][61] de Oliveira et al 62 reported a reduction in acoustic velocity with MC and mentioned that this reduction is more noticeable below the FSP. Nasir et al 22 reported that the crack formation in the wood cell-wall and higher pore size in the wood microstructure augment the wood porosity, which leads to a lower wood stiffness and higher dissipation of the energy of the propagated wave in wood.…”

Section: Effect Of Uv Radiation On the Extracted Featuresmentioning

confidence: 99%

Combined machine learning–wave propagation approach for monitoring timber mechanical properties under UV aging

Nasir

Fathi

Kazemirad

2021

Structural Health Monitoring

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This study proposes a combined machine learning–wave propagation approach for nondestructive prediction of the modulus of elasticity (MOE) and rupture (MOR) of timber subjected to ultraviolet (UV) radiation. Fir, poplar, alder, and oak wood specimens were subjected to artificial UV aging and assessed using the Lamb wave propagation. Different features including the wave characteristics and the viscoelastic properties of the specimens were obtained from the Lamb wave propagation tests. The extracted features trained a decision tree model for MOE and MOR prediction. The UV radiation caused a decrease in the elastic properties of wood but increased its viscoelasticity. The results also showed a decrease in the wave velocity and an increase in the wave amplitude decay with the UV exposure time. It was revealed that compared with the wave velocity, the wave amplitude decay was better correlated to the MOE of MOR of UV-degraded wood. The MOE and MOR of UV-degraded wood were accurately predicted by the machine learning models fed by the features extracted from the Lamb wave propagation tests, where the shear storage modulus was found as the most important feature for training the models. It was concluded that the proposed approach offers a great tool for in-situ monitoring of wood structures under weathering and photodegradation conditions.

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“…It would be of notable interest to be able to determine and to characterize, with no-destructive instrumental tests, one or more parameters able to define, qualitatively and quantitatively, its mechanical characteristics to better understanding the interaction tree -shaking machine during the mechanical harvest. Numerous studies on the mechanical characteristics of the olive tree wood have concerned the characterization of its anatomical structure and the determination, on specimens, of the principal elastic constants by the evaluation of the speed of propagation of ultrasonic wave [1][2][3]. Other studies have been based on the detecting of the vibration natural 2 of 10 frequencies both flexural and longitudinal, and of the corresponding inside damping, calculated with the method of the logarithmic decrement [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Vibration-Based Experimental Identification of the Elastic Moduli Using Plate Specimens of the Olive Tree

et al. 2019

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Mechanical parameters of the olive wood plate have been computed by data inversion of vibrational experimental tests. A numerical-experimental method has allowed the evaluation of the two transverse shear moduli and the four in-plane moduli of a thick orthotropic olive tree plate. Therefore, the natural flexural vibration frequencies of olive trees plates have been evaluated by the impulse technique. For our purposes, we define the objective function as the difference between the numerical computation data and the experimental ones. The Levenberg-Marquardt algorithm was chosen as optimization strategy in order to minimize the matching error: the evaluation of the objective function has required a complete finite element simulation by using the ANSYS code. As input, we have used the uniaxial test data results obtained from the olive plates. The converged elastic moduli with n = 10 natural modes were E 1 = 14.8 GPa, E 2 = 1.04 GPa, G 12 = 4.45 GPa, G 23 = 4.02 GPa, G 13 = 4.75 GPa, ν 12 = 0.42, and ν 13 = 0.42. The relative root mean square (RMS) errors between the experimental frequencies and the computed one is 9.40%. Then, it has been possible to obtain a good agreement between the measured and calculated frequencies. Therefore, it has been found that for plates of moderate thickness the reliability of the estimated values of the transverse shear moduli is good.

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Comparison of moisture-dependent orthotropic Young’s moduli of Chinese fir wood determined by ultrasonic wave method and static compression or tension tests

Cited by 13 publications

References 23 publications

Effects of Moisture Content and Grain Direction on the Elastic Properties of Beech Wood Based on Experiment and Finite Element Method

Effects of Moisture Content and Grain Direction on the Elastic Properties of Beech Wood Based on Experiment and Finite Element Method

Combined machine learning–wave propagation approach for monitoring timber mechanical properties under UV aging

Vibration-Based Experimental Identification of the Elastic Moduli Using Plate Specimens of the Olive Tree

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