SOURCE-LINKED INTELLIGENCE

Probabilistic decision framework for Resilience assessment of Offshore energy infrastructures subjected to seismic Submarine landsLIDE hazard (PRO-SLIDE)

CORDIS · observation · Publication date unknown

s and features as well as trends. The findings will be based on a database produced via advanced numerical analyses of the OEI-SSL mechanism using the DEM-FEM, a catalog of near-fault ground motions, machine learning technic, and probabilistic/fragility analyses. A two-way transfer of knowledge is guaranteed since I have a solid background in the development of earthquake-induced sliding models and ground motions databank and also my supervisor at AAU has vast experience in the resilience assessment of OEIs and data-driven models. Moreover, my supervisors at secondments (RMIT&HKUST) have great experience in the fields of OEI numerical simulation and physical modeling. Accordingly, this will ensure the achievement of this timely and innovative project as well as the dissemination and exploitation of the expected results. The acquired skills will allow me to embrace an academic/non-academic career path in the EU. Offshore energy infrastructure, Earthquake, Landslide, Deformation predictive model, Fragility function, Resilience assessment

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recordType

award

status

SIGNED

region

EU

value

214934.4

unit

EUR