Population growth, economic development, and rapid urbanization in many areas have led
to increased exposure and vulnerability of structural and infrastructure systems to hazards …

In an increasingly digital world, there are fast-paced developments in fields such as Artificial
Intelligence, Machine Learning, Data Mining, Digital Twins, Cyber-Physical Systems and the …

Many studies have been performed to put quantifying uncertainties into the seismic risk
assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment …

Decision‐makers and stakeholders require a rapid assessment of potential damage after
earthquake events in order to develop and implement disaster risk reduction strategies and …

Long-span cable-stayed bridges are prone to significant vibrations under strong wind events
such as typhoons, which pose a risk to the bridge functioning and the driving safety of …

The damage assessment of numerous buildings after the earthquake is still a challenge by
traditional methods as it requires a significant amount of time and resources for carrying out …

The extraordinary success of Machine Learning (ML) in many complex heuristic fields has
promoted its introduction in more analytical engineering fields, improving or substituting …

A deep learning-based rapid peak seismic response prediction model for the most common
two-story and three-span subway stations is proposed in this study. The established model …

Seismic vulnerability assessments are conventionally conducted by using sophisticated
nonlinear analytical models, leading to aggressive computational demands. Previous …

Southeastern Europe faces a significant earthquake threat, endangering lives, property, and
infrastructure thus jeopardizing sustainable development. The development of a Rapid …