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Cubic Function-Based Bayesian Dynamic Linear Prediction Approach of Bridge Extreme Stress
Joint Authors
Fan, Xueping
Liu, Yuefei
Xiao, Qingkai
Source
Advances in Materials Science and Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-24
Country of Publication
Egypt
No. of Pages
10
Abstract EN
In structural health monitoring (SHM) field, the structural stress prediction and assessment are the research bottleneck.
To reasonably and dynamically predict structural extreme stress based on the time-variant monitored data, the objectives of this paper are to present (a) cubic function-based Bayesian dynamic linear models (BDLM) about monitored extreme stress, (b) choosing method of optimum probability distribution functions about initial stress state, (c) monitoring mechanism of the optimum BDLM, and (d) an effective way of taking advantage of BDLM to incorporate the time-variant monitored data into structural extreme stress prediction.
The monitored data of an existing bridge is adopted to illustrate the feasibility and application of the proposed models and procedures.
American Psychological Association (APA)
Liu, Yuefei& Xiao, Qingkai& Fan, Xueping. 2017. Cubic Function-Based Bayesian Dynamic Linear Prediction Approach of Bridge Extreme Stress. Advances in Materials Science and Engineering،Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1124689
Modern Language Association (MLA)
Liu, Yuefei…[et al.]. Cubic Function-Based Bayesian Dynamic Linear Prediction Approach of Bridge Extreme Stress. Advances in Materials Science and Engineering No. 2017 (2017), pp.1-10.
https://search.emarefa.net/detail/BIM-1124689
American Medical Association (AMA)
Liu, Yuefei& Xiao, Qingkai& Fan, Xueping. Cubic Function-Based Bayesian Dynamic Linear Prediction Approach of Bridge Extreme Stress. Advances in Materials Science and Engineering. 2017. Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1124689
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1124689