The developments in structural health monitoring techniques have led to the invention of
various sensors that can be effective damage indicator. Due to environmental or …

Bayesian model class selection has attracted substantial interest in recent years for
selecting the most plausible/suitable class of models based on system input–output data …

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 Bayesian probabilistic approach is presented for selecting the most plausible class of
models for a structural or mechanical system within some specified set of model classes …

A Bayesian probabilistic methodology for structural health monitoring is presented. The
method uses a sequence of identified modal parameter data sets to compute the probability …

The spatial variation of seismic ground motions denotes the differences in the seismic time
histories at various locations on the ground surface. This text focuses on the spatial …

The problem of identification of the modal parameters of a structural model using measured
ambient response time histories is addressed. A Bayesian Fast Fourier Transform approach …

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 …

The dynamic characterization of structures is essential for assessing their response when
subjected to dynamic loads in structural health monitoring. It mainly comprises the modal …

Modal identification methodologies are used to determine the dynamic characteristics of sys-
tems. In structural engineering, these dynamic parameters play an important role in the …