Information plays a pivotal role in the resilient management of bridge systems, connecting and supporting decisions at the different hierarchical levels and across the several domains involved in the decision process. However, the increasing interconnectedness and interdependence that information enables also leads to the emergence of safety and reliability problems related to the quality of the information. In this project, emphasis will be on information from Structural Health Monitoring. Resilience metrics and models for information quality will be developed and integrated into a Bayesian Probabilistic Network that will be the base of a decision support tool (DST) for the optimization of monitoring systems for the resilience management of bridges.
CYBERES is a Polimi Seal of Excellence project.
On 14 August 2018, 43 people died in the collapse of the so-called Morandi bridge in Genova; beyond the human tragedy, this event reminded us of the decadent state of critical transport infrastructure in the EU. Bridges built in the last century are ageing all over the world and need continuous maintenance. This will be a growing challenge in the next decades due to population growth, projected effects of climatic changes, and not least to the scarcity of resources available for maintenance. Research efforts on bridge integrity management in the last decades have been devoted to risk-based approaches that do not account for the indirect consequences associated with long recovery times.
Structural Health Monitoring data and information plays a pivotal role in the management of bridge systems. However, the increasing interconnectedness and interdependence that information enables also leads to the emergence of safety and reliability problems related to the quality of the information. In this project, emphasis will be on information from Structural Health Monitoring.
Data and information quality metrics will be developed and integrated into a Bayesian Probabilistic Network, BPN. This BPN will be the base of a decision support framework and model for the optimization of monitoring systems for the resilience management of bridges.