Bayesian model updating of a 250 m super-tall building utilizing an enhanced Markov chain Monte Carlo simulation algorithm

Bayesian model updating of a 250 m super-tall building utilizing an enhanced Markov chain Monte Carlo simulation algorithm

Finite element models (FEMs) are effective for predicting structural behaviors subjected to various excitations. However, modeling errors in FEMs always exist, especially for complex structural systems, and these affect the accuracy of FEMs. Model updating using measured data can significantly impro...

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Bibliographic Details
Main Authors: Yu-Xia Dong, Feng-Liang Zhang, Yan-Ping Yang, Jia-Hua Yang
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Case Studies in Construction Materials
Subjects:
Model updating
Markov chain Monte Carlo
Multi-level sampling
Bayesian inference
Super-tall building
Online Access:http://www.sciencedirect.com/science/article/pii/S2214509524008015

Internet

http://www.sciencedirect.com/science/article/pii/S2214509524008015

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