This tutorial paper reviews the use of advanced Monte Carlo sampling methods in the
context of Bayesian model updating for engineering applications. Markov Chain Monte …

This study investigated operational and structural health monitoring (SHM) as well as
damage evaluations for building structures. The study involved damage detection and the …

Quantifying the value of the information extracted from a structural health monitoring (SHM)
system is an important step towards convincing decision makers to implement these …

Structural health monitoring (SHM) is developing rapidly to fulfill the world's need for resilient
and sustainable communities. Due to the current advancements in machine learning and …

Synthetic Aperture Radar Interferometry (InSAR) using satellite data is revealing a promising
tool for monitoring long-term deformation phenomena in critical infrastructural systems …

Bayesian inference is a popular approach towards parameter identification in engineering
problems. Such technique would involve iterative sampling methods which are often robust …

A critical aspect in structural health monitoring (SHM) applied to civil engineering structures
is the lack of diagnostic labels able to assign a damage class to the measured data. In this …

With the increased availability of timber materials, such as cross-laminated timber, the
number of buildings using timber as a structural material has been rapidly increasing. As …

Abstract Model updating techniques are often applied to calibrate the numerical models of
bridges using structural health monitoring data. The updated models can facilitate damage …

Tests on infill masonry walls have been widely performed by many researchers and for a
long time with the main purpose of characterising the infill performance under earthquake …