In civil engineering structures, modal changes produced by environmental conditions,
especially temperature, can be equivalent to or greater than the ones produced by damage …

As the finite element (FE) model has become increasingly important in engineering, the
model updating method has also received much attention as a means of improving the …

Damage detection is one important target in structural health monitoring (SHM). Vibration‐
based damage detection has attracted more attention in the past decades by tracking the …

The fundamental problem of Bayesian model updating is identifying the posterior probability
density function (PDF) of uncertain model parameters. Markov chain Monte Carlo (MCMC) …

The Bayesian model updating approach has attracted much attention by providing the most
probable values (MPVs) of physical parameters and their uncertainties. However, the …

Bayesian inference plays a vital role in Structural Health Monitoring (SHM) by assessing
structural integrity through probabilistic model updating using monitoring data. A crucial …

In this paper, an improved nonlinear model of railway ballast is proposed based on the
modified Ludwik model. The accuracy of model-based structural damage detection relies on …

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

Wind speed forecasting can serve a wide spectrum of purposes, including scheduling of a
power system and dynamic control of structures. A lot of models are widely used to forecast …

Existing studies on sparse Bayesian learning for structural damage detection usually
assume that the posterior probability density functions follow standard distributions which …