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Physics-Informed Surrogate Modeling for Offshore Helical Pile Design Optimization

Project description

Open-source tool for offshore helical piles design

Larger and deeper offshore wind turbine (OWT) foundations pose challenges for traditional methods due to long installation times and environmental impacts. Helical piles (HP) offer faster installation and reduced environmental disturbance, but their load-bearing performance assessment methods remain insufficient, limiting their use. With the support of the Marie Skłodowska-Curie Actions programme, the PISMO project aims to create an open-source decision-making tool that optimises offshore HP design using data-driven techniques. By leveraging physics-informed machine learning algorithms (PIA), the tool will enable accurate predictions of HP systems’ static and dynamic performance, including installation effects. The results are expected to improve design processes, reduce costs, and promote sustainable offshore engineering. The project supports the European Green Deal and the UN Sustainable Development Goals (SDGs).

Objective

The development of offshore wind turbine (OWT) foundations toward larger sizes and deeper embedment presents challenges for traditional foundations, which have long installation times and cause significant environmental disturbances. Helical piles, with their distinct installation method, offer shorter installation times and reduced environmental impact, making them a strong candidate for OWT foundations. However, the lack of efficient methods to assess offshore HP load-bearing performance under various conditions limits their broader application.
This project aims to develop an open-source decision-making tool to optimize offshore HP design using data-driven techniques. By incorporating physics-informed machine learning algorithms (PIA), the tool will enable surrogate modeling to replace traditional numerical analyses, allowing accurate predictions of HP’s static and dynamic performance, including installation effects. This will improve design processes, reduce costs, and contribute to sustainable offshore engineering practices.
The fellowship has three key Research and Innovation Objectives (R&IO): (1) to establish a validated numerical model that simulates HP load-bearing performance, including installation effects, which will form a database for (2) developing PIA-based data-driven models to assess HP capacity. These models will then be integrated into (3) an open-source decision-making tool using reliability-based foundation design approach (RBFDA) to optimize HP design under various conditions.
The fellowship will be conducted at NGI, Norway, with a secondment at OsloMet, Norway. The skills gained will enable the researcher to become an expert in HP technology and support the pursuit of a tenure-track position. Furthermore, the project aligns with the European Green Deal and the UN Sustainable Development Goals (SDGs) by contributing to clean energy and sustainable engineering.

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Topic(s)

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2024-PF-01

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Coordinator

NORGES GEOTEKNISKE INSTITUTT AS
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 251 578,56
Address
SANDAKERVEIEN 140
0484 OSLO
Norway

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Region
Norge Oslo og Viken Oslo
Activity type
Research Organisations
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Total cost

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