Evaluating the Performance of Protection Beams Subject to Overheight Vehicular Impacts Using Analytical and Machine Learning–Based Methods
Publication: Journal of Bridge Engineering
Volume 28, Issue 12
Abstract
Overheight truck collision with a bridge superstructure can cause extensive structural damage and result in severe traffic congestion. Placing protection beams in front of the fascia girder is one of the common countermeasures to guard against such events. However, little research has been done on this topic in the past and there are no standard guidelines for designing these protection beams. High-fidelity numerical simulations are conducted to formulate a demand model for protection beams subjected to overheight truck impact scenarios involving three different trailer models (representing soft, semirigid, and rigid impactors), a range of truck weights and velocities, and a number of beam sections and lengths. A validated demand model is proposed to represent the loading pulses caused by the different types of impactors. Two performance levels for the protection beam are suggested. Simulation data are used to propose a reliable machine-learning (ML) model for the classification of beam performance as a function of the parameters of the impacting truck and protection beam. The ML model and demand function are complementary to each other and enable rapid and accurate assessments, respectively, of the performance of protection beams during impact scenarios.
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Data Availability Statement
All data shown in the paper are available from the corresponding author by request. The training model is available on Github: https://github.com/RanC-research/ML.git.
Acknowledgments
This research was supported by the National Science Foundation of China Grants 52108136 and the Fundamental Research Funds for the Central Universities. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the National Science Foundation of China.
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Information & Authors
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Published In
Journal of Bridge Engineering
Volume 28 • Issue 12 • December 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Aug 3, 2022
Accepted: Jun 22, 2023
Published online: Sep 22, 2023
Published in print: Dec 1, 2023
Discussion open until: Feb 22, 2024
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