PREDICTION OF PLASTIC HINGE LENGTH AT THE RC BRIDGE PIERS USING ARTIFICIAL NEURAL NETWORKS ALGORITHM

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KHALILI A.; AHMADI M.; EMAMI E.; KHEYRODDIN A.

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Journal: JOURNAL OF CONCRETE RESEARCH Year:2015 | Volume:8 | Issue:1 Page(s): 27-40

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Title

PREDICTION OF PLASTIC HINGE LENGTH AT THE RC BRIDGE PIERS USING ARTIFICIAL NEURAL NETWORKS ALGORITHM

Author(s)

KHALILI A. | AHMADI M. | EMAMI E. | KHEYRODDIN A. | Issue Writer Certificate

Keywords

PLASTIC HINGE LENGTHQ2

REINFORCED CONCRETE BRIDGE PIERSQ2

ARTIFICIAL NEURAL NETWORKS ALGORITHMQ2

INFRASTRUCTURESQ1

Abstract

According to significant of bridges as INFRASTRUCTURES, and need for serviceability after earthquakes, it is necessary to design this group of structures adequately. In this way the determination of the location of nonlinear response in these structural systems is an important step to predict the performance of the system under different loading conditions. In REINFORCED CONCRETE BRIDGE PIERS, these nonlinear deformations generally occur over a finite hinge length.A model of hinging behavior in reinforced concrete bridges pier will help guide, detailing and drift estimates for performance-based design. In this paper, by using experimental results that conducted on the reinforced concrete bridges piers and also applying ARTIFICIAL NEURAL NETWORKS ALGORITHM, predict the PLASTIC HINGE LENGTH of reinforced concrete bridges pier.The results show that the accuracy of ARTIFICIAL NEURAL NETWORKS ALGORITHM for predicting of this parameter in compare with other formulations that were proposed as for calculated error is appropriate.

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APA: Copy

KHALILI, A., AHMADI, M., EMAMI, E., & KHEYRODDIN, A.. (2015). PREDICTION OF PLASTIC HINGE LENGTH AT THE RC BRIDGE PIERS USING ARTIFICIAL NEURAL NETWORKS ALGORITHM. JOURNAL OF CONCRETE RESEARCH, 8(1), 27-40. SID. https://sid.ir/paper/197225/en

Vancouver: Copy

KHALILI A., AHMADI M., EMAMI E., KHEYRODDIN A.. PREDICTION OF PLASTIC HINGE LENGTH AT THE RC BRIDGE PIERS USING ARTIFICIAL NEURAL NETWORKS ALGORITHM. JOURNAL OF CONCRETE RESEARCH[Internet]. 2015;8(1):27-40. Available from: https://sid.ir/paper/197225/en

IEEE: Copy

A. KHALILI, M. AHMADI, E. EMAMI, and A. KHEYRODDIN, “PREDICTION OF PLASTIC HINGE LENGTH AT THE RC BRIDGE PIERS USING ARTIFICIAL NEURAL NETWORKS ALGORITHM,” JOURNAL OF CONCRETE RESEARCH, vol. 8, no. 1, pp. 27–40, 2015, [Online]. Available: https://sid.ir/paper/197225/en

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