This article proposes an unsupervised deep learning–based approach to detect structural
damage. Supervised deep learning methods have been proposed in recent years, but they …

This paper presents a predictive model for the settlement of shallow-founded structures on
liquefiable ground during earthquakes. The model is based on the results of an extensive …

We updated our Next Generation Attenuation (NGA)-West1 ground motion models (GMMs)
for the horizontal components of Arias intensity (AI) and cumulative absolute velocity (CAV) …

Excessive building settlement and tilt on liquefiable soils has led to significant damage in
previous earthquakes. The state-of-practice for evaluating liquefaction-induced building …

This paper characterizes the ability of natural ground motions to induce rocking demands on
rigid structures. In particular, focusing on rocking blocks of different size and slenderness …

A new attenuation model is proposed to estimate the cumulative absolute velocity (CAV) of
strong ground motions based on an updated earthquake database of the earthquakes …

Conditional ground‐motion models (CGMMs) for estimating Arias intensity (⁠ IA⁠) for
earthquakes in subduction zones are developed. The estimate of IA is conditioned in these …

This paper presents probabilistic models for predicting the residual and peak transient tilt of
mat-founded structures on liquefiable ground. First, the study presents a completely …

ABSTRACT The Pacific Earthquake Engineering Research Center Next Generation
Attenuation‐West2 database is used to derive a new conditional ground‐motion model …

This study proposes the capacity cumulative absolute velocity (CAV c) as a novel measure
for the resistance of granular soils to earthquake-induced liquefaction. The CAV c is defined …