Explainable AI-based generation of offshore substructure designs
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
Historically the design of Offshore Wind Turbines (OWT) depends on various influence factors which are set by engineers. Typically, most parameters are determined during the initial design phase and have less consideration on the influences of the entire life-cycle of a structure, leading to the over-exploitation of a single design, like monopiles. In this work, we define the design process as a multi-objective optimization problem and use Artificial Intelligence (AI) to discover multiple optimal solutions, while providing feedback, in the form of feature importance explanations for generated structures. Our approach results in efficient designs, while explanations can improve engineers' understanding of alternative design possibilities.
Details
Original language | English |
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Title of host publication | Proceedings of the 33rd International Ocean and Polar Engineering Conference, 2023 |
Editors | Jin S. Chung, Decheng Wan, Satoru Yamaguchi, Shiqiang Yan, Igor Buzin, Hiroyasu Kawai, Hua Liu, Ivana Kubat, Bor-Feng Peng, Ali Reza, Venkatachalam Sriram, Suak Ho Van |
Publisher | International Society of Offshore and Polar Engineers |
Pages | 286-292 |
Number of pages | 7 |
ISBN (print) | 9781880653807 |
Publication status | Published - 2023 |
Peer-reviewed | Yes |
Publication series
Series | Proceedings of the International Offshore and Polar Engineering Conference |
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ISSN | 1098-6189 |
Conference
Title | 33rd International Ocean and Polar Engineering Conference |
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Abbreviated title | ISOPE 2023 |
Conference number | 33 |
Duration | 19 - 23 June 2023 |
Website | |
Degree of recognition | International event |
Location | The Westin |
City | Ottawa |
Country | Canada |
External IDs
ORCID | /0000-0001-8735-1345/work/160479751 |
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ORCID | /0000-0002-3578-3098/work/160479856 |
Keywords
ASJC Scopus subject areas
Keywords
- Artificial Intelligence, Evolutionary Algorithm, Industrial Design, Machine Learning, Multi-objective Optimization, Offshore Wind Turbines