In this paper, we present a new Bayesian model updating method that could overcome the
problem of low sampling efficiency and over-reliance on single-chain proposal distribution of …

This paper proposes a Markov Chain Monte Carlo (MCMC)-based Bayesian method for
nonlinear stochastic model updating by using the instantaneous characteristics of the …

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

Stochastic model updating techniques are used to update an FE model of a structure so that
the updated model can predict the mean as well as the variability of the structure's dynamic …

A new variant of damage detection algorithm is proposed based on Sparse Bayesian
Learning (SBL) and model reduction for probabilistic structural damage detection. By …

The Bayesian model updating approach (BMUA) has been widely used to update structural
parameters using modal measurements because of its powerful ability to handle …

In this study, a Modified Frequency and Spatial Domain Decomposition (MFSDD) technique
is developed for modal parameter identification, using output-only response measurements …

In this work, the systematic validation of a deterministic finite element (FE) model updating
procedure for damage assessment is presented using a self-developed modular laboratory …

Each operational modal analysis (OMA) technique may produce significant errors during the
identification procedure due to the applied methodology, environmental/operational …

Structural damage identification is often recast as the procedure to find the damage
parameters from the measured data and the prescribed structural model. However, noises …