In structural engineering, model updating is often used for non-destructive damage
assessment: by calibrating stiffness parameters of finite element models based on …

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 …

Bayesian methods are a powerful tool in many areas of science and engineering, especially
statistical physics, medical sciences, electrical engineering, and information sciences. They …

A new probabilistic finite element (FE) model updating technique based on Hierarchical
Bayesian modeling is proposed for identification of civil structural systems under changing …

Bayesian inference provides a powerful approach to system identification and damage
assessment for structures. The application of Bayesian method is motivated by the fact that …

Abstract Markov chain Monte Carlo (MCMC) simulation is applied for model updating of the
coupled-slab system of a building structure based on field test data following the Bayesian …

This paper presents a recursive Bayesian inference framework for digital twinning of an
offshore wind turbine (OWT) in the Block Island Wind Farm (BIWF), the first commercial …

In Bayesian model updating, probability density functions of model parameters are updated
accounting both for the information contained in the data and for uncertainties present in the …

This paper presents a probabilistic damage identification study on a full‐scale structure, the
Dowling Hall footbridge, through a Bayesian finite element (FE) model updating. The …

A methodology is presented for Bayesian structural model updating using noisy incomplete
modal data corresponding to natural frequencies and partial mode shapes of some of the …