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 technique, and probabilistic/fragility analyses.
What is the PROSLIDE modeling?
WP2: Two centrifuge model tests are planned at the secondment host at HKUST to compensate for the lack of experimental data to identify the underlying mechanism of landslide-monopile interaction. This stage includes the setup of submarine slope and OEI, instrumentation, and similitude law. It delivers robust physical models that can identify the mechanism of a landslide-monopile interaction.
WP3: A database of OEI (especially MSOWT) deformation during the SSL is developed from numerical analyses by considering the structure, earthquake, geotechnical and geological parameters of the slope. An in-depth theoretical background regarding the coupled DEM-FEM modeling will be acquired during the secondment at RMIT. This step includes numerical modeling using a database of NFGMs, and the development of a database.
WP3: Machine learning technique and statistical analysis are applied to the database to propose a data-driven model for the prediction of OEI deformation triggered by the SSL.
WPs4-5: Probabilistic analyses are performed on the produced database and proposed predictive model to present the fragility surfaces of OEI. This step includes the probabilistic and fragility analyses in scalar and vector forms and specifies the performance levels and resilience assessments of OEIs subjected to seismic landslides. Moreover, an application example is carried out for a specific region to show how to use the outcomes of the project.
Situated in Northern Denmark, Aalborg University (AAU) is one of the DK’s leading research-intensive universities and a dynamic university of more than 20,000 students and 3,000 staff., AAU is ranked no. 25 in the top 100 universities established within the past 50 years. The Department of the Built Environment (DBE) which includes the Civil Engineering Stream is ranked top 51-100th in the world by the 2021 QS Rankings.
Royal Melbourne Institute of Technology (RMIT) is a global university of technology, design, and enterprise with more than 96,000 students and 9,000 staff globally. RMIT ranking is 190th globally (11th in Australia) in QS Rankings 2023. RMIT's research income was $74.2 M in 2020 (63% from industry and other sources).
Hong Kong University of Science and Technology (HKUST) is ranked as the world's second-best young university in QS Top 50 2022 and it is ranked #40 in QS Rankings 2023. The Geotechnical Centrifuge Facility (GCF) at HKUST is a powerful and advanced laboratory for physical modeling of various engineering-related problems earthquake-induced deformations, and SSI problems.
The PRO-SLIDE project has received funding from the European Union under the Marie Skłodowska-Curie Postdoctoral Fellowships grant agreement No 101106129.
Project Reference: 101106129
DOI: 10.3030/101106129
Call: HORIZON-MSCA-2022-PF-01
EU Contribution: 214 934.40 €
Period: 12/2023 -> 12/2025