Abstract
Capturing the spatial variability in soil is crucial for ground response analyses in the context of seismic hazard mitigation. The lateral variability in thickness and properties of the different soil layers is one of the main factors that determines the variability of the ground motion spectrum from one location to another. The absence of such lateral variability information in the subsoil in between the locations of Cone Penetration Tests (CPTs) may be compensated by the use of more densely sampled seismic data. In this research we aim to derive a shear-wave velocity field through seismic full-waveform inversion that yields a model resolution approaching that of high-resolution seismic CPT surveys. Following this, a datadriven correlation between geophysical and geotechnical information is attempted through the application of new machine-learning-based approaches.
Original language | English |
---|---|
Title of host publication | Proceedings of the 7th International Conference on Geotechnical and Geophysical Site Characterization |
Editors | Marcos Arroyo, Antonio Gens |
Publisher | International Center for Numerical Methods in Engineering (CIMNE) |
Pages | 808-812 |
Number of pages | 5 |
DOIs | |
Publication status | Published - 2024 |
Event | 7th International Conference on Geotechnical and Geophysical Site Characterization - UPC BarcelonaTech Campus Nord, Barcelona, Spain Duration: 18 Jun 2024 → 21 Jun 2024 https://www.issmge.org/events/isc7 |
Conference
Conference | 7th International Conference on Geotechnical and Geophysical Site Characterization |
---|---|
Abbreviated title | ISC'7 |
Country/Territory | Spain |
City | Barcelona |
Period | 18/06/24 → 21/06/24 |
Internet address |
Keywords
- Full-waveform inversion
- Machine learning
- Shear-wave velocity