At the time of designing structures up to date, the density and magnitude of the load have
increased, and the requirements for regulation have also become more stringent. To ensure …

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 work presents a surrogate model-based Bayesian model updating (BMU) approach for
automated damage identification of large-scale structures, which outperforms methods …

Bearings usually play numerous important functionalities such as deformation regulation,
load transfer, and seismic isolation in bridges. A better mastery of their service performance …

Abstract Model updating procedures based on experimental data are commonly used in
case of historic buildings to identify numerical models that are subsequently employed to …

Bayesian inference methods usually require numerous forward model simulations to
generate converged samples. When the forward model is expensive to evaluate, it becomes …

Numerical modeling is a very useful tool in different fields of bridge engineering, such as
load-carrying capacity assessment or structural health monitoring. Developing a reliable …

Abstract Model updating procedures are commonly used to identify numerical models of a
structure to be subsequently used for reliable assessment of its behaviour under …

This paper presents a surrogate modelling technique based on domain partitioning for
Bayesian parameter inference of highly nonlinear engineering models. In order to alleviate …

Identifying modal parameters and updating finite element models (FEMs) of real structures
through ambient tests is essential in Structural Health Monitoring (SHM). However, efficiently …