Characterizing Mechanical Properties of Layered Engineered Wood Using Guided Waves and Genetic Algorithm.

Area of Science:

• Materials Science
• Structural Engineering
• Acoustics

Background:

• Engineered wood, or mass timber, is a sustainable construction material requiring robust nondestructive evaluation (NDE) and quality assurance (QA).
• Accurate material parameter determination is crucial for ensuring the structural integrity and performance of mass timber.
• Existing destructive testing methods for wood products exhibit significant variability.

Purpose of the Study:

• To develop a nondestructive framework for determining the material parameters of layered engineered wood.
• To enhance NDE and QA processes for mass timber construction.
• To establish a foundation for advanced studies on layered engineered wood structures.

Main Methods:

• Utilized static compression tests to derive initial elastic moduli and Poisson's ratios.
• Employed guided wave measurements to capture dynamic responses and dispersion relations.
• Applied a genetic algorithm (GA) coupled with COMSOL simulations to solve the inverse problem for material properties.

Main Results:

• The GA framework successfully estimated orthotropic elastic constants for laminated veneer lumber (LVL).
• The proposed method achieved estimation accuracy with less than 10% error for most elastic constants.
• Estimated elastic constants, particularly for vertical flexural modes, aligned well with reference values from destructive tests.

Conclusions:

• The developed framework offers a feasible approach for nondestructively gauging mechanical traits of LVL using guided waves and multi-variable optimization.
• This study represents a significant advancement in the NDE of layered engineered wood.
• The findings support the use of mass timber in sustainable and resilient civil infrastructure.