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 …

Efficiency of a Bayesian model updating algorithm is greatly affected by the choice of
variance of prediction error models of different data points (evidence) used for model …

In general, for a structure it is quite difficult to get information about all of its modes through
its dynamic response under ambient or external excitation. Therefore, it is vital to …

A novel approach is presented in this work to localize simultaneously multiple damaged
elements in a structure along with the estimation of damage severity for each of the …

Most of the developed sensitivity-based damage detection methods are based on the
application of external excitations which could be prohibitive due to infeasible excitation of …

When only a few lower modes data are available to evaluate a large number of unknown
parameters, it is difficult to acquire information about all unknown parameters. The challenge …

In general, for a structure it is quite difficult to get information about all of its modes through
its dynamic response under ambient or external excitation. Therefore, it is vital to …

This chapter implements Bayesian neural networks for finite-element-model updating. This
method was tested on a simple beam and an unsymmetrical H-shaped structure and …

Damage identification is an important topic in structural assessment and structural health
monitoring (SHM). Vibration-based identification techniques use modal data to identify the …

This book dealt with the use of computational intelligence methods for finite-element-model
updating. Finite-element-model updating is a process through which finite-element models …