The paper presents a systematic review about the use of artificial intelligence (AI) in the field
of structural health management of existing bridges. Using the PRISMA protocol, 81 journal …

The paper presents a machine learning (ML) based framework to predict the prestressing
force reduction in prestressed reinforced concrete (PSC) box-girder bridges with unbonded …

The prediction of the seismic risk and vulnerability of bridge clusters can contribute positively
to the development of large-scale regional earthquake resilience and loss models. Using …

Many seismic damage field observations of masonry structures indicate that buildings
constructed in different eras differ in terms of seismic risk and vulnerability under time …

In multi-risk assessment frameworks involving road infrastructures, measures of exposure to
natural hazards include traffic volumes. However, traffic counts are usually collected through …

To explore the actual seismic vulnerability and failure modes of typical building portfolios,
this paper innovatively reports the actual damage characteristics and failure mechanisms of …

This study presents a novel framework for integrating corrosion effects into critical
infrastructure seismic risk assessment, focusing on reinforced concrete (RC) structures …

Featured Application This work can be applied to estimate acceleration using measured
inclination, without partially measuring the target acceleration. Moreover, this is a finite …

To address the issue of insufficient transverse connectivity in prestressed concrete box
girder (PCB) bridges, this study investigates two transverse strengthening methods …

This study investigates the probabilistic seismic damage characteristics of a five-span RC
simply supported girder bridge with double-column piers designed for a high-speed railway …