Damage Evaluation of Bridge Hanger Based on Bayesian Inference: Analytical Model. (28th May 2021)
- Record Type:
- Journal Article
- Title:
- Damage Evaluation of Bridge Hanger Based on Bayesian Inference: Analytical Model. (28th May 2021)
- Main Title:
- Damage Evaluation of Bridge Hanger Based on Bayesian Inference: Analytical Model
- Authors:
- Ding, Yang
Dong, Jing-liang
Yang, Tong-lin
Wang, Zhong-ping
Zhou, Shuang-xi
Wei, Yong-qi
She, An-ming - Other Names:
- Xin Haohui Academic Editor.
- Abstract:
- Abstract : With the increase of the long-span bridge, the damage of the long-span bridge hanger has attracted more and more attention. Nowadays, the probability statistics method based on Bayes' theorem is widely used for evaluating the damage of bridge, that is, Bayesian inference. In this study, the damage evaluation model of bridge hanger is established based on Bayesian inference. For the damage evaluation model, the analytical expressions for calculating the weights by finite mixture (FM) method are derived. In order to solve the complex analytical expressions in damage evaluation model, the Metropolis-Hastings (MH) sampling of Markov chain Monte Carlo (MCMC) method was used. Three case studies are adopted to demonstrate the effect of the initial value and the applicability of the proposed model. The result suggests that the proposed model can evaluate the damage of the bridge hanger.
- Is Part Of:
- Advances in materials science and engineering. Volume 2021(2021)
- Journal:
- Advances in materials science and engineering
- Issue:
- Volume 2021(2021)
- Issue Display:
- Volume 2021, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 2021
- Issue:
- 2021
- Issue Sort Value:
- 2021-2021-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-05-28
- Subjects:
- Materials science -- Periodicals
Materials science
Periodicals
620.11 - Journal URLs:
- http://www.hindawi.com/journals/amse ↗
- DOI:
- 10.1155/2021/9947727 ↗
- Languages:
- English
- ISSNs:
- 1687-8434
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 17107.xml