Abstract
Structural deterioration is induced by multiple mechanisms due to progressive degradation, such as aging, corrosion, and fatigue, and sudden events, such as earthquakes, tsunamis, and hurricanes. These mechanisms may significantly affect the performance indicators of structural components and systems during their life cycles. Many studies on the effects of structural deterioration on structural performance indicators have been reported in the literature. However, most of them study the effect of a single deterioration mechanism on structural performance indicators in a deterministic context. Therefore, further research is needed to capture the joint effects of multiple deterioration mechanisms on structural performance indicators in a probabilistic context. Moreover, in order to achieve the main goal of infrastructure management by maximizing the life-cycle performance at a minimum cost, an optimal risk-based life-cycle strategy has to be provided. This paper presents a life-cycle risk-based optimal management strategy for bridge networks subjected to corrosion and seismic hazards. The proposed strategy is illustrated with an existing bridge network. Girder replacement is considered for the bridge superstructure, which is prone to corrosion hazard, while seismic retrofit measures are considered for the bridge bearings and substructures to improve their seismic performance. A709-50CR steel girders are used to replace the corroded steel girders herein (A709-50CR is a novel corrosion-resistant steel with a chromium content similar to that of martensitic stainless steel). Parametric analysis is conducted to investigate the effects of both target service life and correlation of the safety margins among the superstructures of the bridge network on the Pareto fronts associated with life-cycle risk-based optimal maintenance solutions. Comparison is also made between Pareto fronts associated with both hazards and those associated with corrosion hazard only.
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Acknowledgments
The authors are grateful for the support provided by (1) the Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems (CIAMTIS), a US Department of Transportation University Transportation Center, under federal rant number 69A3551847103, and (2) the Commonwealth of Pennsylvania Department of Community and Economic Development through the Pennsylvania Infrastructure Technology (PITA). The authors would like to thank Mr. Thomas P. Macioce, PE, from the Pennsylvania Department of Transportation for providing the bridge drawings used in the case study. The authors would also like to thank Dr. Thomas P. Murphy from Modjeski and Masters, Inc., for his support. The opinions and conclusions presented this paper are those of the authors and do not necessarily reflect the views of the sponsoring organizations.
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Information & Authors
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Published In
Journal of Bridge Engineering
Volume 28 • Issue 1 • January 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Apr 15, 2022
Accepted: Sep 13, 2022
Published online: Oct 31, 2022
Published in print: Jan 1, 2023
Discussion open until: Mar 31, 2023
ASCE Technical Topics:
- Architectural engineering
- Bridge engineering
- Bridge management
- Building management
- Business management
- Corrosion
- Deterioration
- Earthquake engineering
- Engineering fundamentals
- Geohazards
- Geotechnical engineering
- Life cycles
- Maintenance and operation
- Materials characterization
- Materials engineering
- Practice and Profession
- Seismic effects
- Seismic tests
- Structural engineering
- Tests (by type)
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Cited by
- Xu Han, Dan M. Frangopol, Impact of Climate Change on Risk Assessment and Effective Maintenance Strategies for Bridge Networks Subjected to Corrosion, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10.1061/AJRUA6.RUENG-1059, 10, 1, (2024).
- Xiaoming Lei, You Dong, Dan M. Frangopol, Sustainable Life-Cycle Maintenance Policymaking for Network-Level Deteriorating Bridges with a Convolutional Autoencoder–Structured Reinforcement Learning Agent, Journal of Bridge Engineering, 10.1061/JBENF2.BEENG-6159, 28, 9, (2023).