A Framework for Evaluating the Impact of Structural Health Monitoring on Bridge Management
Although structural monitoring has been recognized as a powerful information tool, bridge managers often make decisions based on their experience or on common sense, somehow regardless of the action suggested by instrumental damage detection algorithms. In fact, managers weight differently the outcomes of the detection based on his/her príor perception of the state of the structure and decide keeping in mind the possible effects of the action he/she can undertake. In this paper we propose a rational framework to include the impact of the mentioned issues on decision making. The methodology is applied to the Bill Emerson Memorial Bridge, a new 1206 meter long cable-stayed structure across the Mississippi River, instrumented with an 84-channel seismic instrumentation system. Using a finite element model, we estimate the probability distributions of the response of the bridge for a possible damage scenarío involving formation of plastic hinges at the intersection of tower columns and cap beams. The example shows how it is possible to estimate the economic benefit of a monitoring system for any event which requires a damage assessment.
M. Pozzi et al., "A Framework for Evaluating the Impact of Structural Health Monitoring on Bridge Management," Proceedings of the 5th International Conference on Bridge Maintenance, Safety and Management (2010, Philadelphia, PA), pp. 646-653, CRC Press, Jul 2010.
5th International Conference on Bridge Maintenance, Safety and Management (2010: Jul. 11-15, Philadelphia, PA)
Civil, Architectural and Environmental Engineering
Keywords and Phrases
Artificial Neural Network; Bridge Management; Condition Assessment; Decision-Making; Cap Beams; Common Sense; Damage Assessments; Detection Algorithm; Economic Benefits; Emerson; Finite Element Models; Information Tools; Mississippi River; Monitoring System; Plastic Hinges; Seismic Instrumentation; Structural Monitoring; Tower Column; Damage Detection; Maintenance; Managers; Neural Networks; Probability Distributions
International Standard Book Number (ISBN)
Article - Conference proceedings
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01 Jul 2010