Structural Health monitoring of RC bridges

The scope of this study is the development and verification of a system for the long-term monitoring of bridge structures with emphasis on reinforced concrete and prestressed concrete bridges. Digital twin technology has recently gathered a lot of attention in the engineering communities as it is used for the health monitoring and detection of the current state of the vital structures of the transport infrastructure system such as bridges. The state of the bridges is constantly changing by environmental changes, service loads, chemical actions and human-induced factors. The evaluation process of the state of bridges becomes a complicated issue, when significant uncertainties regarding their structural performance especially for old bridges that they were designed by old standards and practices. Therefore, a monitoring system which can assess the condition and state of the bridges is a key factor to contribute to the extension of their service life by enhancing their resilience and reliability. The monitoring system will consist of two components: (a) a data-based system incorporating artificial intelligence to learn and evaluate data based on the bridge's behavioural history, and (b) a numerical system utilizing 3D numerical models capable of accurately simulating the bridge's behaviour.

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