The potential benefits of improving performance prediction through the integration of health monitoring systems with probabilistic predictive models, and their implications on the management of deterioration prone structures are presented in this paper. It is shown using case studies that the confidence in predicted performance can be considerably im-proved through the use of health monitoring methods and hence, the timing of manage-ment activities such as inspections, repair and maintenance can be refined to maintain tar-get safety or condition. A comparison of various models for the input parameters indicate that their effects on the performance prediction of deteriorating structures can be mini-mised through the additional information gained through in-service health monitoring sys-tems. It is also concluded for the scenarios considered that the life-cycle costs (LCC) for the management activities are considerably reduced when the decision support system is aided by structural health monitoring (SHM).
|Title of host publication||Advances in Bridge Maintenance, Safety Management, and Life-Cycle Performance|
|Subtitle of host publication||Proceedings of the Third International Conference on Bridge Maintenance, Safety and Management, 16-19 July 2006, Porto, Portugal - IABMAS '06|
|Editors||P. J. S. Cruz, Dan M. Frangopol, Luis C.C. Neves|
|Publisher||Taylor & Francis|
|Number of pages||9|
|Publication status||Published - 2006|
|Name||Bridge Maintenance, Safety and Management|
Rafiq, M. I., Chryssanthopoulos, M., & Onoufriou, T. (2006). Predictive SHM-supported deterioration modelling of reinforced concrete bridges. In P. J. S. Cruz, D. M. Frangopol, & L. C. C. Neves (Eds.), Advances in Bridge Maintenance, Safety Management, and Life-Cycle Performance: Proceedings of the Third International Conference on Bridge Maintenance, Safety and Management, 16-19 July 2006, Porto, Portugal - IABMAS '06 (Bridge Maintenance, Safety and Management). Taylor & Francis.