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Stiffness matrix method for defective phononic beams toward piezoelectric sensors and actuators under bending wavesopen access

Authors
Lee, MinsooBaek, JuheeBae, HanseongHwang, DohyeonJang, JinhyeokJo, Soo-HoYoon, Heonjun
Issue Date
Jun-2026
Publisher
ELSEVIER
Keywords
Phononic beams; Bending waves; Stiffness matrix method; Piezoelectric defect; Euler-Bernoulli beam theory; Numerical stability
Citation
Sensors and Actuators A: Physical, v.403, pp 1 - 19
Pages
19
Indexed
SCIE
SCOPUS
Journal Title
Sensors and Actuators A: Physical
Volume
403
Start Page
1
End Page
19
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/64046
DOI
10.1016/j.sna.2026.117683
ISSN
0924-4247
1873-3069
Abstract
Defective phononic beams (DPBs) allow for the strong spatial localization of elastic waves, providing the necessary energy amplification to achieve high-sensitivity actuation and sensing. This study presents an analytical framework based on stiffness matrices that can accurately and efficiently model the electromechanically coupled bending wave phenomena in piezoelectric DPBs. Conventional transfer-matrix methods (TMMs) often experience numerical instability and ill-conditioning, particularly in multi-cell or high-frequency configurations. The primary contribution of this study is the development of a numerically stable and computationally efficient stiffness matrix method (SMM). The proposed SMM can predict band structures, defect modes, and electromechanical actuation and sensing responses within a unified analytical framework. Comparisons with finite element methods (FEMs) demonstrate that the SMM achieves accuracy comparable to that of FEMs while producing smooth, physically consistent frequency responses without spurious oscillations. Furthermore, the SMM requires only a fraction of the computational time required for FEM analyses. The formulation is fully implemented in MATLAB, enabling reproducible simulations. Condition-number analyses confirm that, unlike TMMs, the SMM remains well-conditioned across the frequency domain. These findings establish the SMM as a robust, scalable, and time-efficient analytical framework to optimize ultrasonic transducers for nondestructive evaluation, structural health monitoring, and prognostics and health management.
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