Durability Assessment of Reinforced Concrete Bridge Based on Fuzzy Neural Networks

Yong Chun Cheng; Hong Bin Guo; Xian Qiang Wang; Yu Bo Jiao

doi:10.4028/www.scientific.net/AMR.838-841.1069

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The Influence of Pile-Pier Reinforcement Ratio on the Development of Plastic Zone of Bridge Structure
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Research on Longitudinal Seismic Response of Continuous Welded Rail on Bridge with High-Pier and Long-Span
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Overload Safety Analysis of the North Anchor Foundation of the Run Yang Suspension Bridge
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Application of Displacement Back Analysis in Geometry Monitoring of Segmental Construction of Prestressed Concrete Continuous Girder Bridge
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Design and Test Analysis of Mid-and-Long Term Monitoring System for External Prestressed Continuous Rigid Frame Bridge
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 838-841Durability Assessment of Reinforced Concrete...

Durability Assessment of Reinforced Concrete Bridge Based on Fuzzy Neural Networks

Abstract:

In the operation process of bridge structures, some bridges appear early failure without reaching design reference period due to the influences of external environment, vehicle load and other factors. Therefore, the problem of structure durability is very obvious. In this paper, a new durability assessment method is proposed based on fuzzy neural networks, which can take account of the defects and deficiencies of existing durability assessment methods. The simulation for learning and testing samples indicates that the proposed method possesses good learning ability and predictive analysis ability. Actual project verifies the effectiveness of the method

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Periodical:

Advanced Materials Research (Volumes 838-841)

Pages:

1069-1072

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.838-841.1069

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Online since:

November 2013

Authors:

Yong Chun Cheng, Hong Bin Guo, Xian Qiang Wang, Yu Bo Jiao*

Keywords:

Bridge Structure, Condition Assessment, Fuzzy Logic, Neural Network (NN)

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* - Corresponding Author

References

[1] Wenxue Han. Fuzzy Comprehensive Assessment in Reinforced Concrete Bridge State Based on AHP [D]. Nanning: Guangxi University, (2007).

Google Scholar

[2] Technical Code of Maintenance for Highway》 (JTG H10-2009) [S], Ministry of Communications, (2009).

Google Scholar

[3] Baoshuang Ren, Jiaru Qian, etal. The Comprehensive Evaluation Method of Existing Reinforced Concrete Beam Bridge Structure [J]. China Civil Engineering Journal, 2002.

Google Scholar

[4] Dajian Han, Bingrao Yang, Quansheng Yan. Bridge Defect Condition Assessment Based on Artificial Neural Networks [J]. Journal of South China University of Technology ( Natural Science Edition), 2004.

Google Scholar

[5] Pinghua Zhu, Weiliang Jin, etal. Method for Evaluating Durability of Existing Concrete Bridges Structures[J]. Journal of Zhejiang University (Engineering Science), (2006).

Google Scholar

[6] Zhixing Zhang, Chunzai Sun. Neural - Fuzzy and Soft Computing[M]. Xi'an: Xi'an Jiaotong University Press, (2000).

Google Scholar

[7] Guoyong Li. Neural-Fuzzy Control Theory and Application [M]. Beijing: Electronic Industry Press, (2009).

Google Scholar