Fully Coupled Electromechanical Elastodynamic Model for Guided Wave Propagation Analysis

TL;DR

This paper introduces a comprehensive 3D electromechanical elastodynamic model for guided wave propagation in complex materials, enabling detailed analysis of wave behavior and sensor responses for structural health monitoring.

Contribution

The paper presents a fully coupled 3D model that accurately simulates wave propagation and sensor interactions in heterogeneous, anisotropic materials, advancing computational tools for SHM.

Findings

Model validated theoretically and computationally efficient

Demonstrated mode tuning of Lamb waves across frequencies

Analyzed relationship between surface displacement and sensor voltage

Abstract

Physics-based computational models play a key role in the study of wave propagation for structural health monitoring (SHM) and the development of improved damage detection methodologies. Due to the complex nature of guided waves, accurate and efficient computation tools are necessary to investigate the mechanisms responsible for dispersion, coupling, and interaction with damage. In this paper, a fully coupled electromechanical elastodynamic model for wave propagation in a heterogeneous, anisotropic material system is developed. The final framework provides the full three dimensional displacement and electrical potential fields for arbitrary plate and transducer geometries and excitation waveform and frequency. The model is validated theoretically and proven computationally efficient. Studies are performed with surface bonded piezoelectric sensors to gain insight into the physics of experimental techniques used for SHM. Collocated actuation of the fundamental Lamb wave modes is modeled over a range of frequencies to demonstrate mode tuning capabilities. The displacement of the sensing surface is compared to the piezoelectric sensor electric potential to investigate the relationship between plate displacement and sensor voltage output. Since many studies, including the ones investigated in this paper, are difficult to perform experimentally, the developed model provides a valuable tool for the improvement of SHM techniques.