HEИндивидуална стипендия2026–2028

SIINSTALL · Sustainable and Intelligent Installation of Anchor Piles for Floating Offshore Wind Energy

„Хоризонт Европа“ — Действия „Мария Склодовска-Кюри“

Период
2026-04-01 → 2028-03-31
Финансиране от ЕС
232 916 €
Участници
2
Схема
HORIZON-TMA-MSCA-PF-EF

Линиите свързват координатора с партньорите.

Накратко на български

Интелигентна система за прогнозиране на съпротивлението на почвата ще помогне за по-ефективно забиване на котва-колони за плаващи вятърни турбини. Това ще намали разходите и вредния подводен шум, който влияе на морските бозайници.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Цел на проекта

The European Strategic Energy Technology Plan prioritizes research and innovation in offshore wind energy to achieve climate neutrality by 2050. With shallow offshore sites nearly developed, attention is now shifting to deeper waters (>60 m depth), where floating offshore wind (FOW) turbines are more viable. Anchor piles, which are hollow steel pipes, are widely used to secure FOW turbines to the seabed. Currently, the installation of anchor piles relies on large hydraulic hammers that deliver strike blows to the pile head. However, this method is inefficient, expensive, and generates harmful underwater noise, which can negatively affect marine mammals. In this context, an innovative method is urgently needed to improve installation efficiency, and reduce environmental harm, thereby making FOW more viable.SIINSTALL aims to promote the wide adoption of vibratory driving method by developing an intelligent forecasting system to predict pile driveability and soil resistance to driving. To achieve this, the researcher will: (i) create a unique database of physical modelling tests using the cutting-edge centrifuge facilities at TU Delft, simulating the vibro-driving of anchor piles; (ii) perform numerical simulations and parametric studies to gain deeper insights into soil behaviour during vibro-driving; and (iii) develop a neural network-based surrogate model, integrating data from numerical and physical modelling. This machine learning model will form the core of the intelligent forecasting system.SIINSTALL takes a strong interdisciplinary approach, bridging offshore geotechnics, computer science, and physics while addressing industry needs. To ensure the project’s success, the researcher will conduct research within TU Delft’s Geo-Engineering group, including a three-month secondment at the University of Western Australia. This project will enhance the researcher’s academic career, fostering independent leadership skills and expertise in floating offshore wind.

Оригинален текст от CORDIS (на английски).

Участници

Връзки

Данни: CORDIS, © Европейски съюз