A digital twin for ship structures—R&D project in Japan

Masahiko Fujikubo, Tetsuo Okada, Hideaki Murayama, Hidetaka Houtani, Naoki Osawa, Kazuhiro Iijima, Kunihiro Hamada, Kimihiro Toh, Masayoshi Oka, Shinichi Hirakawa, Kenichi Shibata, Tetsuro Ashida, Toshiro Arima, Yoshiteru Tanaka, Akira Tatsumi, Takaaki Takeuchi, Taiga Mitsuyuki, Kohei Mikami, Makito Kobayashi, Yusuke KomoriyamaChong Ma, Xi Chen, Hiroshi Ochi, Rei Miratsu

研究成果: ジャーナルへの寄稿学術誌査読

7 被引用数 (Scopus)

抄録

In order to clarify and visualize the real state of the structural performances of ships in operation and establish a more optimal, data-driven framework for ship design, construction and operation, an industry-academia joint R&D project on the digital twin for ship structures (DTSS) was conducted in Japan. This paper presents the major achievements of the project. The DTSS aims to grasp the stress responses over the whole ship structure in waves by data assimilation that merges hull monitoring and numerical simulation. Three data assimilation methods, namely, the wave spectrum method, Kalman filter method, and inverse finite element method were used, and their effectiveness was examined through model and full-scale ship measurements. Methods for predicting short-term extreme responses and long-term cumulative fatigue damage were developed for navigation and maintenance support using statistical approaches. In comparison with conventional approaches, response predictions were significantly improved by DTSS using real response data in encountered waves. Utilization scenarios for DTSS in the maritime industry were presented from the viewpoints of navigation support, maintenance support, rule improvement, and product value improvement, together with future research needs for implementation in the maritime industry.

本文言語英語
ジャーナルData-Centric Engineering
5
DOI
出版ステータス出版済み - 3月 27 2024

!!!All Science Journal Classification (ASJC) codes

  • 統計学および確率
  • 工学一般
  • コンピュータ サイエンスの応用
  • 応用数学

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