Implementing a Long-Term Bridge Monitoring Strategy for a Composite Steel Girder Bridge

<p>The University of Connecticut and the Connecticut Department of Transportation have established a long-term bridge health monitoring system to monitor critical vulnerabilities in a group of bridges throughout the state. This research focuses on a three-span, simply supported composite steel girder bridge carrying three lanes of highway traffic. It has been a part of the University of Connecticut and Connecticut Department of Transportation monitoring network since 2004 and is fitted with 20 strain gauges located at midspan at the top and bottom of the web of each girder.</p> <p>To monitor the critical vulnerabilities of the bridge, it is important to quantify anticipated<em><strong> </strong></em>changes in measurements resulting from different types and levels of damage. Four damage measures including natural frequency, peak strain, strain distribution, and neutral axis location, will be presented and the changes in these damage measures for five different damage scenarios will be examined to identify the specific damage measures best suited to identify each particular type of damage.</p> <p>In order to incorporate these damage measures into the automated bridge monitoring system of this bridge, the anticipated changes in the damage measures must be compared to the inherent variability of actual bridge measurements to determine the minimum level of damage that can be detected by the system. The uncertainty of each damage measure is evaluated and its sensitivity to damage compared with the anticipated changes identified by the finite element model. Based on these comparisons, the minimum vulnerability that can be identified by the monitoring system can be determined.</p>

Name thesis:degree_name

Master of Science

Discipline thesis:degree_discipline

Civil Engineering

Year dc:date.available

2011

Author dc:creator

• Plude, Shelley

Contributors dc:contributor

• John T. DeWolf; Jeong-ho Kim
• Richard Christenson

• bridge monitoring
• damage detection
• finite element modeling
• structural health monitoring
• steel girder

Repository record dc:identifier

https://digitalcommons.lib.uconn.edu/gs_theses/154

OAI identifier oai:identifier

oai:digitalcommons.lib.uconn.edu:gs_theses-1197