Machine learning (ML) has evolved rapidly over recent years with the promise to
substantially alter and enhance the role of data science in a variety of disciplines. Compared …

Given the devastating losses incurred by past major earthquake events together with the
ever-increasing global seismic exposures due to population growth and urbanization …

Robust seismic vulnerability assessment for a building under expected earthquake ground
motions necessitates explicit consideration of all-important sources of uncertainty in …

Deriving the fragility curves is a key step in seismic risk assessment within the performance-
based earthquake engineering framework. The objective of this study is to implement …

Fragility functions and demand hazard curves are important metrics for assessing the
seismic damage and risk of an engineering system. This study aims at conducting seismic …

Risk assessment and mitigation programs have been carried out over the last decades in
the attempt to reduce transportation infrastructure downtime and post-disaster recovery …

Cloud Analysis is based on simple regression in the logarithmic space of structural response
versus seismic intensity for a set of registered records. A Bayesian take on the Cloud …

Incremental dynamic analysis (IDA) is presented as a powerful tool to evaluate the variability
in the seismic demand and capacity of non‐deterministic structural models, building upon …

This study applies nonlinear dynamic analyses to assess the risk of collapse of RC special
moment-frame (SMF) buildings to quantify the seismic safety implied by modern building …

The estimation of building fragility, ie, the probability function of seismic demand exceeding
a certain limit state capacity given the seismic intensity, is a common process inherent in any …