Journal of Computational Design and Engineering, Год журнала: 2024, Номер 11(3), С. 56 - 71

Опубликована: Апрель 16, 2024

Abstract Metasurfaces can effectively attenuate Rayleigh waves propagating in soil, safeguarding structures from ambient vibrations or earthquakes. However, there remains a lack of efficient approaches for designing metasurfaces that isolate within desired frequency ranges under different site conditions. This study presents deep learning (DL)-based topology optimization method isolating target range, which has potential applications surface wave control. The proposed DL model employs variational autoencoder to transform high-dimensional and discrete topologies into low-dimensional continuous latent vectors, reducing the design difficulty. On this basis, conditional tandem neural network is constructed optimize vectors soil conditions, improving efficiency verifying universality method. reliability validated through 100 tests with determination coefficients more than 0.99. In addition, generations same are explored, providing designers choices. insulation capabilities designed against Metro-induced demonstrated time- frequency-domain responses. presented DL-aided provides novel insight customization manipulating waves.

Язык: Английский