Structural damage identification has received considerable attention during the past
decades. Although several reviews have been presented, some new developments have …

In structural engineering, model updating is often used for non-destructive damage
assessment: by calibrating stiffness parameters of finite element models based on …

Structural damage identification based on finite element (FE) model updating has been a
research direction of increasing interest over the last decade in the mechanical, civil …

This tutorial paper reviews the use of advanced Monte Carlo sampling methods in the
context of Bayesian model updating for engineering applications. Markov Chain Monte …

The problem of updating a structural model and its associated uncertainties by utilizing
dynamic response data is addressed using a Bayesian statistical framework that can handle …

This paper gives an overview of recent advances in the field of non-probabilistic uncertainty
quantification. Both techniques for the forward propagation and inverse quantification of …

Probability logic with Bayesian updating provides a rigorous framework to quantify modeling
uncertainty and perform system identification. It uses probability as a multi‐valued …

The current interest in the combustion chemistry of hydrocarbon fuels, including the various
alcohol and biodiesel compounds, motivates this review of the methods and application of …

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

In a full Bayesian probabilistic framework for “robust” system identification, structural
response predictions and performance reliability are updated using structural test data 𝒟 by …