Structural health monitoring (SHM) techniques have been studied for several years. An
effective approach for SHM is to choose the parameters that are sensitive to the damage …

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 …

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

This paper presents a newly developed simulation-based approach for Bayesian model
updating, model class selection, and model averaging called the transitional Markov chain …

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

The quantification of probabilistic uncertainties in the outputs of physical, biological, and
social systems governed by partial differential equations with random inputs require, in …

Structural health monitoring (SHM) is the subject of a great deal of ongoing research leading
to the capability that reliable remote monitoring of civil infrastructure would allow a shift from …

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 …

This paper presents a Hierarchical Bayesian model updating framework to account for the
effects of ambient temperature and excitation amplitude. The proposed approach is applied …

Most of the existing damage detection methods focused on damage along members of the
structure without considering possible damage at its connections. Under the Bayesian …