The Frequency Selection of SH0 Waves for Total Transmission and Its Application in the Damage Detection of Aircrafts

Based on wave interference,a methodology to realize the total transmission phenomenon of SH0 waves is proposed in this paper.After a systematical theoretical investigation,an exact frequency of a flat plate consisting of another medium with finite length,is obtained,which is furthermore exemplified by the finite element method.This frequency is the same as the classical Fabry-Perot condition and dependent on the thickness of the material.It has been revealed that an SH0 wave,with its wavelength equal to twice of the length of another medium,can totally transmit across the medium without reflection.Especially when the impedance changes in a specific range,the energy of transmitted waves can keep in a high level,which is frequency-independent.Not limited by a flat plate,the Fabry-Perot condition is also suitable for a scraggy plate when the thickness variation is relatively small.Finally,using the transfer matrix method,the wave propagation in a plate with multiple layers is quantitatively investigated,and the frequency analysis for total transmission is carried out.The methodology,as well as the design scheme proposed,is achievable and artificially controllable,which opens a new prospect for the wave control and final applications in aeronautics and astronautics.

Total Transmission from Deep Learning Designs

Total transmission plays an important role in efficiency improvement and wavefront control,and has made great progress in many applications,such as the optical film and signal transmission.Therefore,many traditional physical methods represented by transformation optics have been studied to achieve total transmission.However,these methods have strict limitations on the size of the photonic structure,and the calculation is complex.Here,we exploit deep learning to achieve this goal.In deep learning,the data-driven prediction and design are carried out by artificial neural networks(ANNs),which provide a convenient architecture for large dataset problems.By taking the transmission characteristic of the multi-layer stacks as an example,we demonstrate how optical materials can be designed by using ANNs.The trained network directly establishes the mapping from optical materials to transmission spectra,and enables the forward spectral prediction and inverse material design of total transmission in the given parameter space.Our work paves the way for the optical material design with special properties based on deep learning.