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Dr Maria Nogal

Research Fellow
Dept. of Civil, Structural & Environmental Engineering


Risk Analysis of Infrastructure Networks in Response to Extreme Weather (RAIN)

Keywords: Extreme weather events; Critical infrastructure; Risk analysis; Resilience; Transport modelling.


Training in Reducing Uncertainty in Structural Safety (TRUSS)

Keywords: Probabilistic analysis; Extreme Theory; Reliability; Structural design.


Realising European ReSILiencE for Critical INfraStructure (RESILENS)

Keywords: Resilience, Critical Infrastructure, Crises and Disaster Management, Recovery, CI protection.


System to help decision making during the infrastructures life cycle: Smart-Infrastructure

Keywords: Risk management; Help decision making tool; Life cycle; Structural System Identification; Bridges; Buildings; Tunnels.

To prevent accidents and failures in transport infrastructure preventive or corrective actions are required. During the life cycle of infrastructure, both in construction and in service phase, the builder or the property might measure some physical parameters (displacements, rotations, forces) in order to know if a given infrastructure (tunnel, bridge, building) behaves as expected.

Nevertheless, the obtained data rarely substantiate the identification of the actual state of the structure or are associated with a certain probability of failure. In most cases, technicians decide to implement (or not) maintenance or repair works on infrastructure without knowing their actual state based on monitoring information (if any), visual inspections and their own intuition/experience. This maintenance procedure causes security and functionality problems (as demonstrated by the collapse of the I-35W Bridge) with the consequent social problem involved. Furthermore, an inefficient maintenance is associated with a higher cost for the administration for severe repairs.

The aim of this project is to develop a system to help decision-making during the life cycle of major infrastructure (smart-infrastructure such as bridges, buildings and tunnels).

The integral system to help decision-making will consist of a structural identification tool, which will identify damage in structure associated with certain reliability. This tool will enable to locate and quantify damages in infrastructure from their static or dynamic responses in non-destructive tests by a totally new methodology: the observability. The main advantage of this method with respect to most of the methods presented in the literature is the fact that it is based on equations with a physical meaning (parametric method) so that the results are easily interpretable.

Undoubtedly, the system to help decision-making will improve the safety and quality during the construction and maintenance of the infrastructure.


Project Mentor: Associate Prof. Alan O'Connor