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Erschienen in: Neural Computing and Applications 9/2019

21.03.2018 | S.I.: Emergence in Human-like Intelligence towards Cyber-Physical Systems

Seismic performance evaluation of existing RC structures based on hybrid sensing method

verfasst von: Jintao Cui, Haotao Xie, Peng Cui, Dookie Kim

Erschienen in: Neural Computing and Applications | Ausgabe 9/2019

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Abstract

The properties of structures such as stiffness and damping ratio are not a constant but varying in time due to material deterioration such as strength degradation, corrosion, crack and fatigue. The seismic performance of an existing structure is generally evaluated based on design drawings and visual inspection data without consideration of the effects of material deterioration. This paper introduces the process of material deterioration of existing reinforced concrete structures and evaluates its effects on their seismic performance by proposing the three-dimensional fragility curve based on hybrid sensing method. The curve shows the probability of failure of structures with respect to load and time. A bridge under the marine environment in service is utilized to demonstrate the changes of seismic performance because of chloride-induced corrosion of steel bars, which is the main cause of deterioration of existing reinforced concrete near-shore structures. The engineers can make their decisions more wisely for design and maintenance of RC structures based on the proposed method.

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Metadaten
Titel
Seismic performance evaluation of existing RC structures based on hybrid sensing method
verfasst von
Jintao Cui
Haotao Xie
Peng Cui
Dookie Kim
Publikationsdatum
21.03.2018
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 9/2019
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3448-7

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