What is it about?
In this work, we introduce a novel dataset of completed and under-construction jacket designs for offshore wind turbines worldwide, capturing essential structural parameters and environmental conditions. Additionally, we conduct a data-driven conceptual design of jacket structures using Random Forests and XGBoost, identifying key features that provide meaningful, domain-specific insights for subsequent engineering design.
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Why is it important?
We are experiencing a paradigm shift toward AI-assisted design, with data as a necessary enabler. AI can optimize complex structures like offshore wind jackets, improving design quality, cost efficiency, and sustainability. Data-driven insights enable engineers to make better-informed decisions.
Read the Original
This page is a summary of: A novel dataset and feature selection for data-driven conceptual design of offshore jacket substructures, Ocean Engineering, July 2024, Elsevier,
DOI: 10.1016/j.oceaneng.2024.117679.
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