Understanding bridge performance and detecting structurally deficient components are of increasing concern to modern infrastructure owners and managers. Concerns over possible effects of increased truck weights led to the opportunity to monitor a highway bridge, regularly subjected to heavy traffic due to logging activities typical of its locale. A weigh-in-motion and a structural health monitoring system were installed to collect long-term data on both traffic and bridge response. This thesis aims to tackle different aspects of the analysis of the data generated by these systems, to promote a gauge of bridge performance. After assessing the conditions of the bridge at the moment of the data collection, the first goal is to develop new metrics for bridge response based on strain, the second goal is to model and predict bridge response based on traffic and finally, the third goal is to classify the most common bridge responses and categorize the trucks which cause them. By achieving these tasks, this thesis aims to provide data-driven decision-making support for policymakers, bridge managers, and owners, to assure timely and effective interventions, to improve long-term durability and extended serviceability, to increase safety, and eventually to save money.

Last modified

• 10/14/2019

Creator

• Fiorella Mete

DOI

• https://doi.org/10.21985/n2-8100-s153

Subject

• Civil and Environmental Engineering

Keyword

• Bridge monitoring
• structural health monitoring
• weigh in motion
• data mining

Resource type

• Dissertation

Rights statement

• In Copyright