This paper presents an innovative fully-probabilistic Performance-Based Hurricane
Engineering (PBHE) framework for risk assessment of structural systems located in …

Over the past few decades, structural system identification based on vibration
measurements has attracted much attention in the structural dynamics field. The well‐known …

The focus of this paper is Bayesian state and parameter estimation using nonlinear models.
A recently developed method, the particle filter, is studied that is based on stochastic …

In this article, a novel Bayesian real‐time system identification algorithm using response
measurement is proposed for dynamical systems. In contrast to most existing structural …

This paper presents a novel nonlinear finite element (FE) model updating framework, in
which advanced nonlinear structural FE modeling and analysis techniques are used jointly …

A hybrid optimization methodology is presented for the probabilistic finite element model
updating of structural systems. The model updating process is formulated as an inverse …

This paper addresses the issue of system identification for linear structural systems using
earthquake induced time histories of the structural response. The proposed methodology is …

In this paper, an adaptive on‐line parametric identification algorithm based on the variable
trace approach is presented for the identification of non‐linear hysteretic structures. At each …

A modified version of the Artificial Bee Colony (ABC) algorithm is presented to identify
structural systems. ABC is a heuristic algorithm with simple structure, ease of implementation …

Extended Kalman filter (EKF) is widely adopted for state estimation and parametric
identification of dynamical systems. In this algorithm, it is required to specify the covariance …