Machine Learning–Based Seismic Reliability Assessment of Bridge Networks
Publication: Journal of Structural Engineering
Volume 148, Issue 7
Abstract
Transportation networks are critical components of lifeline systems. They can experience disruptions due to seismic hazards that could lead to severe emergency response and recovery problems. Finding an efficient and effective method to evaluate the seismic reliability of bridge networks is crucial for risk managers. This study proposes a method that can compute the seismic reliability of bridge networks using machine learning techniques. The proposed method is computationally less expensive than existing methods and can be implemented easily in emergency risk management systems. Moreover, it includes information on ranking bridges and prioritizing retrofit plans.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2019R1C1C1007780).
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Published In
Journal of Structural Engineering
Volume 148 • Issue 7 • July 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Oct 11, 2021
Accepted: Feb 18, 2022
Published online: Apr 19, 2022
Published in print: Jul 1, 2022
Discussion open until: Sep 19, 2022
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