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

Abstract

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.

Application of Finite Element Method for Mechanical Characterization of Wood and Reconstituted Lignocellulosic-Based Composites – A Review

“…The authors employed an advanced moisture transport model and multi-surface failure criterion to simulate the moisture-related and brittle failure mechanisms, respectively. Fu et al [66] established the feasibility of evaluating the compressive performance of beech wood at various moisture levels ranging from 5% to 60% using FEM. The use of FEM enabled the authors to overcome complications that would otherwise be associated with the experimental determination of mechanical functions of the beech wood at different moisture loadings.…”

Vibrational characteristics of four wood species commonly used in wood products

“…Wood moisture content and density also are the basic wood physical parameters which directly relate to the wood mechanical properties (Yin and Liu 2021). However, wood moisture content and density varies from one wood species to another one, even though in the same condition (Fu et al 2021b;Yin and Liu 2021). Thus, finding another indicator to reflect the mechanical properties of wood is important.…”

“…(Lv et al 2018;Xu et al 2020;Fu et al 2021a;Yang and Liu 2021). The scale of tested wood samples can range from non-defective small samples to full-sized wood panels (Ilic 2003;Jiang et al 2008;Katalin et al 2014;Turkot et al 2020;Tu et al 2020;Fu et al 2021b;Zhang et al 2021). Studies researching the relationship between the dynamic modulus of elastic (MOEd) and the static modulus of elastic (MOEs) have primarily used the transverse vibration method, the vertical vibration method, the ultrasonic wave method, the stress wave method, etc.…”

Effects of Moisture and Direction of Grain on the Thermal Conductivity and Mechanical Properties of Black Alder and Scots Pine

“…In particular, in the longitude direction, the yield mechanism of wood is mostly dependent on the yield and fold of the wood fiber itself, whereas in the transverse direction, the principal reason is slippage damage between wood fibers. Previous research has also revealed that the mechanical properties of a transverse surface vary depending on whether it is examined in the radial or tangential directions (Fu et al, 2021;Li et al, 2018;Y. Aydın and Ozveren, 2019;Yang and Zhang, 2018).…”