Potential benefits of improving performance prediction using structural health monitoring (SHM), and their implications on integrity management of deterioration prone structures, is discussed in this paper. Key challenges in the use of SHM in performance prediction are highlighted. A methodology is presented, using Bayesian Event Updating, to rationally reduce epistemic uncertainty in predictive models by virtue of SHM data. An example of a reinforced concrete member under chloride attack is used to demonstrate the methodology. The updated structural performance is compared with the results from predictive model alone. The confidence in predicted performance is considerably improved, hence the management activities such as inspections, repair and maintenance etc can be delayed keeping consistent target reliability levels.
|Title of host publication||Bridge Maintenance, Safety, Management and Life-Cycle Optimization|
|Subtitle of host publication||Proceedings of the Fifth International IABMAS Conference, Philadelphia, USA, 11-15|
|Editors||Richard Sause, Dan M. Frangopol, Chad Kusko|
|Number of pages||8|
|Publication status||Published - 2010|
|Name||Bridge Maintenance, Safety and Management|