Dynamic Coupling Analysis of Vehicle-Bridge System for Long-Span Suspension Bridge Based on Backpropagation Neural Network Method

Joint Authors

Niu, Xirong
Yuan, Haoyun
Luo, Zuolong
Zheng, Xiaobo

Source

Advances in Civil Engineering

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-09-25

Country of Publication

Egypt

No. of Pages

11

Main Subjects

Civil Engineering

Abstract EN

As the suspension bridge structures become more flexible and the forms of the vehicle load become more diverse, the dynamic coupling problem of the vehicle-bridge system has become gradually prominent in long-span suspension bridges, resulting in an increase in accuracy and efficiency requirements for dynamic coupling analysis of the vehicle-bridge system.

Conventional method such as finite element method (FEM) for dynamic coupling analysis of vehicle-bridge system often requires separate iteration of vehicle system and bridge system, and the contact and coupling interactions between them are used as the link for convergence inspection, which is too computationally intensive and time-consuming.

In addition, the dynamic response of the vehicle-bridge coupling system obtained by FEM cannot be expressed explicitly, which is not convenient for engineering application.

To overcome these drawbacks mentioned above, the backpropagation (BP) neural network technology is proposed to the dynamic coupling analysis of the vehicle-bridge system of long-span suspension bridges.

Firstly, the BP neural network was used to approximate the dynamic response of the suspension bridge in the vehicle-bridge coupling system, and the complex finite element analysis results were thus explicitly displayed in the form of a mathematical analytical expression.

And then the dynamic response of the suspension bridge under vehicle load was obtained by using a dynamic explicit analysis method.

It is shown through a numerical example that, compared with FEM, the proposed method is much more economical to achieve reasonable accuracy when dealing with the dynamic coupling problem of the vehicle-bridge system.

Finally, an engineering case involving a detailed finite element model of a long-span suspension bridge with a main span of 1688 m is presented to demonstrate the applicability and efficiency under the premise of ensuring the approximation accuracy, which indicates that the proposed method provides a new approach for dynamic coupling analysis of the vehicle-bridge system of long-span suspension bridges.

American Psychological Association (APA)

Luo, Zuolong& Zheng, Xiaobo& Yuan, Haoyun& Niu, Xirong. 2020. Dynamic Coupling Analysis of Vehicle-Bridge System for Long-Span Suspension Bridge Based on Backpropagation Neural Network Method. Advances in Civil Engineering،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1122053

Modern Language Association (MLA)

Luo, Zuolong…[et al.]. Dynamic Coupling Analysis of Vehicle-Bridge System for Long-Span Suspension Bridge Based on Backpropagation Neural Network Method. Advances in Civil Engineering No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1122053

American Medical Association (AMA)

Luo, Zuolong& Zheng, Xiaobo& Yuan, Haoyun& Niu, Xirong. Dynamic Coupling Analysis of Vehicle-Bridge System for Long-Span Suspension Bridge Based on Backpropagation Neural Network Method. Advances in Civil Engineering. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1122053

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1122053