Technical Papers
Jan 3, 2024

The Steady-State Response Spectrum of Bridge Structures under Statistical Steady Traffic Flow Loads

Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10, Issue 1

Abstract

The study of the statistical law of the response spectrum of bridge structures under the action of random traffic flow loads can not only evaluate the service performance of bridge structures, but also verify the rationality of the design load taking and provide a reference basis for the control of bridge traffic flow. In this paper, the moving vehicle loads are simplified to moving constant forces, and the statistical characteristics of displacement response spectra and acceleration response spectra of an assembled hollow-slab girder bridge under the action of statistical steady-state traffic flow loads, as well as their spatial distribution laws over the whole bridge, are investigated based on the existing statistical distribution model of traffic flow parameters, which are obtained by Monte Carlo simulation for random traffic flow loads. The results show that with the increase of statistical samples, the mean, standard deviation, and probability density of the steady-state response spectrum estimator of each monitoring point gradually converge, and its convergence value is only related to the random traffic flow load model and the bridge structure characteristics; the convergence values of the mean and standard deviation of the response spectra are parabolically distributed along the longitudinal direction of the bridge; the response spectrum estimator of different precast beams at the same cross section are different due to the different loads transferred laterally. The statistical properties of the response spectrum estimates are not affected by accidental external factors, and can be used as indicators to determine the operating conditions of the bridge structure and the magnitude of the traffic flow on the bridge deck, providing a reference basis for the health monitoring of the bridge structure.

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Data Availability Statement

All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

This study is funded by the Research Start-up Fund for Special Professors of “Tianshan Scholars,” Xinjiang University (Grant No. 620312327). It is further noted that the contribution of Prof. Rui Zhao to the paper is equivalent to that of the corresponding author, Prof. Danhui Dan.

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Information & Authors

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Published In

Go to ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10Issue 1March 2024

History

Received: May 10, 2023
Accepted: Sep 11, 2023
Published online: Jan 3, 2024
Published in print: Mar 1, 2024
Discussion open until: Jun 3, 2024

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Authors

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Yabiao Jing [email protected]
College of Architectural Engineering, Xinjiang Univ., Urumqi, Xinjiang 830017, China. Email: [email protected]
Professor, Dept. of Bridge Engineering, College of Civil Engineering, Tongji Univ., Shanghai 200092, China (corresponding author). Email: [email protected]
Associate Professor, College of Architectural Engineering, Xinjiang Univ., Urumqi, Xinjiang 830017, China. Email: [email protected]
Shengqiang Ma [email protected]
Associate Professor, College of Architectural Engineering, Xinjiang Univ., Urumqi, Xinjiang 830017, China. Email: [email protected]

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