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A nondestructive guided wave propagation method for the characterization of moisture-dependent viscoelastic properties of wood materials
The in-situ monitoring and characterization of the mechanical properties of wood and timber materials is of great importance due to their broad structural applications. The purpose of this study was to propose a nondestructive method to assess the moisture-dependent viscoelastic behavior of structural wood using the guided Lamb wave propagation. Twelve green poplar wood specimens with different moisture content (MC) underwent the Lamb wave propagation tests and the wave characteristics were acquired. The viscoelastic properties of the wood specimens, including the shear storage and shear loss moduli and the loss factor, were then estimated through the solution of the corresponding inverse Lamb wave propagation problem using the experimentally measured Lamb wave characteristics. The structural stiffness and damping of wood specimens were affected by their MC, as the Lamb wave amplitude and velocity significantly decreased with MC. While the shear storage modulus decreased with MC, the shear loss modulus and loss factor increased with MC, resulting in a higher viscoelastic behavior. The loss factor of the wood specimens was estimated to be between 5.88% and 8.49% for different classes of MC, showing an increase of 44% with MC. The Lamb wave propagation method offers a strong tool for nondestructive characterization of the viscoelastic properties of wood materials and structures over a broad MC range. Wood materials show a significant viscoelastic behavior which is highly impacted by their MC. The loss factor can play an important role in the characterization and classification of structural wood and timber with different MC.
A nondestructive guided wave propagation method for the characterization of moisture-dependent viscoelastic properties of wood materials
The in-situ monitoring and characterization of the mechanical properties of wood and timber materials is of great importance due to their broad structural applications. The purpose of this study was to propose a nondestructive method to assess the moisture-dependent viscoelastic behavior of structural wood using the guided Lamb wave propagation. Twelve green poplar wood specimens with different moisture content (MC) underwent the Lamb wave propagation tests and the wave characteristics were acquired. The viscoelastic properties of the wood specimens, including the shear storage and shear loss moduli and the loss factor, were then estimated through the solution of the corresponding inverse Lamb wave propagation problem using the experimentally measured Lamb wave characteristics. The structural stiffness and damping of wood specimens were affected by their MC, as the Lamb wave amplitude and velocity significantly decreased with MC. While the shear storage modulus decreased with MC, the shear loss modulus and loss factor increased with MC, resulting in a higher viscoelastic behavior. The loss factor of the wood specimens was estimated to be between 5.88% and 8.49% for different classes of MC, showing an increase of 44% with MC. The Lamb wave propagation method offers a strong tool for nondestructive characterization of the viscoelastic properties of wood materials and structures over a broad MC range. Wood materials show a significant viscoelastic behavior which is highly impacted by their MC. The loss factor can play an important role in the characterization and classification of structural wood and timber with different MC.
A nondestructive guided wave propagation method for the characterization of moisture-dependent viscoelastic properties of wood materials
Mater Struct
Fathi, Hamidreza (Autor:in) / Kazemirad, Siavash (Autor:in) / Nasir, Vahid (Autor:in)
01.12.2020
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Viscoelastic properties , Natural materials , Materials characterization , Lamb wave , Nondestructive evaluation , Ultrasound Engineering , Solid Mechanics , Materials Science, general , Theoretical and Applied Mechanics , Manufacturing, Machines, Tools, Processes , Civil Engineering , Building Materials
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