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; et al. (Data-Centric Engineering, 2024)
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.