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

PRO-SLIDE · Horizon Europe grant · 2023-12-01–2025-11-30

EC contribution

€214,934

Total cost

€0

Beneficiaries

3
About the data

Source: CORDIS (official EU open data), Horizon Europe. Framework HORIZON · call HORIZON-MSCA-2022-PF-01 · scheme HORIZON-TMA-MSCA-PF-EF · topic HORIZON-MSCA-2022-PF-01-01. CORDIS record →

Objective

The offshore energy infrastructure (OEI)-soil interaction has been studied by numerical analyses in the literature. However, these studies are rarely focused on the performance of OEIs during the seismic submarine landslide (SSL). Moreover, the pseudo-static approach employed for stability assessment of OEI is generally conservative for deep water conditions. The dynamic approach needs a wide range of input parameters and spends a lot of time and money on analyses. Accordingly, predictive models are needed to fill the gap between these approaches for a simple prediction of OEI deformations during SSL. The overall objective of PRO-SLIDE is to develop a reliable and low computational cost solution for simplified resilience assessment of OEIs damage due to SSLs. Answering this concern is not trivial, but it can guide future analyses and contribute to gaining insights from a calibration effort using numerical models that will be undertaken using a benchmark centrifuge model that can successfully capture key mechanisms 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.

Beneficiaries (3)

OrganisationCountryRoleEC contributionSME
AALBORG UNIVERSITET DK coordinator €214,934
HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY HK associatedPartner
ROYAL MELBOURNE INSTITUTE OF TECHNOLOGY*RMIT UNIVERSITY AU associatedPartner

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