Bayesian Model Updating Using Hybrid Monte Carlo Simulation with Application to Structural Dynamic Models with Many Uncertain Parameters
Citations
497 citations
Cites methods from "Bayesian Model Updating Using Hybri..."
...Various applications of Markov Chain Monte Carlo methods have been published recently for robust analysis, identification and health monitoring of structural dynamic systems; for example, calculating robust reliability [21,27], Bayesian updating of linear structural models for structural health monitoring using changes in modal parameter estimates [7,23], Bayesian updating and model class assessment of unidentifiable hysteretic structural models [8] and of dynamic structural models with a large number of uncertain parameters [25]....
[...]
...Samples are generated from the posterior PDF pðhjD;MiÞ by using an MCMC (Markov chain Monte Carlo) method which is a hybrid algorithm based on TMCMC [22] and Hybrid MC [24,25]....
[...]
338 citations
233 citations
186 citations
Cites methods from "Bayesian Model Updating Using Hybri..."
...Many authors have applied and adopted MCMC to Bayesian updating of mechanical models, including (Beck and Au 2002; Cheung and Beck 2009; Sundar and Manohar 2013)....
[...]
...In the applications presented in this paper, the number of model evaluations required for Bayesian updating is on the order of 10(3) − 10(4), which is similar to existing state-of-the-art methods such as transitional MCMC proposed in (Ching and Chen 2007) or the hybrid MCMC approach of (Cheung and Beck 2009)....
[...]
...…applications presented in this paper, the number of model evaluations required for Bayesian updating is on the order of 103 − 104, which is similar to existing state-of-the-art methods such as transitional MCMC proposed in (Ching and Chen 2007) or the hybrid MCMC approach of (Cheung and Beck 2009)....
[...]
156 citations
Cites methods from "Bayesian Model Updating Using Hybri..."
...Many works have been published in the literature (see for instance textbooks on the Bayesian method such as [59, 60, 61, 62] and papers devoted to the use of the Bayesian method in the context of uncertain mechanical and dynamical systems such as [12, 128, 129, 130, 131, 132, 133]....
[...]
References
35,161 citations
18,761 citations
14,965 citations
6,884 citations
4,641 citations