Spectrum-compatible artificial accelerograms via conditional variational autoencoder with generative adversarial networks
The need for spectrum-compatible ground motions in structural seismic design has driven the development of artificial seismic waveform generation techniques. This study proposes a Conditional Variational Autoencoder with Generative Adversarial Networks (CVAE-GAN) framework to generate artificial acc...
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| Published in: | Engineering structures Vol. 348; p. 121766 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
01.02.2026
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| Subjects: | |
| ISSN: | 0141-0296 |
| Online Access: | Get full text |
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| Summary: | The need for spectrum-compatible ground motions in structural seismic design has driven the development of artificial seismic waveform generation techniques. This study proposes a Conditional Variational Autoencoder with Generative Adversarial Networks (CVAE-GAN) framework to generate artificial accelerograms conditioned on acceleration response spectra, addressing the demand for spectrum-compatible ground motions in earthquake engineering. Utilizing Japan’s K-NET and KiK-net seismic records, preprocessed with PhaseNet for P-wave detection, the model generates diverse accelerograms that preserve the temporal and spectral characteristics of real earthquakes. Validation on a test set (4.5 ≤ Mw ≤ 7.5) demonstrates that over 99 % of the generated spectra achieve an R² above 0.8 with an RMSE below 0.1 m/s2, confirming its high accuracy and realism. Furthermore, the model exhibits generalizability to out-of-range magnitudes (Mw < 4.5 or Mw > 7.5).
•Developed CVAEGAN to generate spectrum-compatible seismic accelerograms.•Over 99 % generated spectra with R² > 0.8, RMSE < 0.1 m/s2 for Mw 4.5–7.5.•Demonstrated generalizability to out-of-range magnitudes (Mw < 4.5 or Mw > 7.5).•Captured P/S-wave times, coda attenuation in generated accelerograms.•Matched real records' fourier spectra, phase, and phase differences. |
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| ISSN: | 0141-0296 |
| DOI: | 10.1016/j.engstruct.2025.121766 |