Speaker
Description
Seismic and geophysical observations are becoming increasingly important in interdisciplinary research connecting Earth sciences, engineering, and fundamental physics. From a civil and structural engineering perspective, buildings and infrastructure can also provide useful information through their response to ground motion. This contribution presents a conceptual framework for linking structural seismic response, local site effects, and data-driven analysis within the broader scope of COST Action CA24101 – FuSe.
The proposed framework is based on the combination of ground-motion parameters, site amplification effects, structural response indicators, and simplified numerical modelling. Machine learning and artificial intelligence methods could support this process by helping to identify patterns, classify response behaviour, and explore possible relationships between seismic input, site conditions, and structural performance.
Although the topic comes mainly from earthquake engineering, it fits the interdisciplinary aims of FuSe by showing how engineering-based seismic observations may complement classical seismological and geophysical data. The main goal is to open a discussion on how civil engineers, seismologists, geophysicists, physicists, and data scientists can work together in the interpretation of complex seismic phenomena.
Keywords: structural seismic response; earthquake engineering; site effects; data-driven modelling; machine learning; FuSe CA24101.