Database Enabled Rapid Seismic Vulnerability Assessment of Bridges. Issue 12 (December 2021)

• Record Type: Journal Article
• Authors: Bonthron, Leslie; Beck, Corey; Lund, Alana; Zhang, Xin; Cao, Yenan; Dyke, Shirley J.; Ramirez, Julio; Mavroeidis, George P.; Baah, Prince; Hunter, Jeremy
• Is Part Of: Transportation research record. Volume 2675:Issue 12(2021)
• Page Start: 1106
• Page End: 1120
• Publication Date: 2021-12
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/03611981211032223
• Languages: English
• ISSNs: 0361-1981

Abstract

As the seismic hazard has been updated for the central U.S., state Departments of Transportation (DOTs) find an increasing need to assess the seismic vulnerability of their bridge network. Traditional methods to perform seismic assessment require developing dynamic models for each bridge. However, this approach requires specialized engineering knowledge and information from structural drawings, and is time-consuming. To streamline this important task, a simplified dynamic modeling procedure is described that leverages readily available information from DOTs' asset management databases. With a minimal amount of additional data items, the asset management database can be used to identify vulnerable bridges rapidly and with sufficient accuracy for the prioritization of retrofit decisions. A detailed analysis of a 100-bridge sample set identified typical vulnerabilities and established corresponding capacity thresholds. The rapid seismic vulnerability assessment methodology is implemented as an Excel macro-enabled tool for bridge owners and asset managers to rapidly assess the vulnerability of each individual bridge based on current information in the database, and then classify the vulnerability of each individual bridge as low, medium, or high. Current DOT databases used for asset management in regions of low-to-moderate seismicity do require some data items be added for a robust assessment. These data items are identified here and leveraged to demonstrate the method. The rapid assessment methodology presented can be implemented to effectively identify the most vulnerable bridges in a bridge network, thus facilitating a rapid state bridge inventory network assessment to prioritize and inform actions such as maintenance and rehabilitation.