Abstract
Shear-wave (S-wave) excitation in elastic solids typically relies on tangential actuation to achieve high modal purity, thereby limiting flexibility and efficiency in practical applications. In this work, a surface-normal encoding paradigm is proposed to enable directional S-wave generation using only normal surface excitation. By spatially encoding the phase (0 and π) of an array of normally oriented point sources, a directional shear wavefield can be synthesized without introducing tangential displacement or traction, thereby transforming the excitation mechanism from conventional tangential driving to phase-controlled wavefield construction based on normal actuation. To efficiently predict three-dimensional elastic wavefields, a machine learning-assisted semi-analytical framework is developed, allowing rapid evaluation under both single- and multi-source excitations. Based on this framework, square and circular meta-exciters are designed and optimized. The square configuration generates highly directional S-waves concentrated at horizontal angles of 0° and 180°, with dominant radiation in the vertical range of 25°–50°, whereas the circular configuration enables S-wave excitation over the entire horizontal plane (0°–360°). These results provide an efficient and flexible strategy for controllable S-wave excitation, with strong potential for high-throughput, couplant-free nondestructive testing (NDT) applications.
| Original language | English |
|---|---|
| Article number | 114727 |
| Journal | Mechanical Systems and Signal Processing |
| Volume | 258 |
| DOIs | |
| State | Published - 15 Aug 2026 |
| Externally published | Yes |
Keywords
- Machine learning
- Metamaterial
- Normal encoding
- Shear wave
- Wave excitation
- Wavefield synthesis
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