SOURCE-LINKED INTELLIGENCE

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

CORDIS · observation · Publication date unknown

metric 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. Floating offshore wind; anchor piles; vibratory driving; centrifuge tests; machine learning

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recordType

award

status

SIGNED

region

EU

value

232916.16

unit

EUR