A digital twin model within the framework of a digital healthcare engineering system for aging containership hull structures

Digital Healthcare Engineering (DHE) offers a proactive approach to improving the safety, longevity, and sustainability of aging ships and offshore structures operating in harsh and remote environments. The DHE framework is composed of five interconnected modules: (1) on-site monitoring and digitalization of structural health parameters, (2) transmission of collected data to land-based analytics centers via low Earth orbit (LEO) satellites, (3) advanced analytics and simulations through digital twin technology, (4) AI-driven diagnostics with automated maintenance recommendations, and (5) predictive health analysis for future maintenance planning. This paper focuses on the development of a digital twin model used for data analytics and simulations within the DHE system, specifically for aging containership hull structures. A case study involving an as-built 22,000 TEU containership is presented to demonstrate the digital twin's effectiveness, where on-site monitoring of parameters such as ocean wave profiles and in-service damage (e.g. corrosion wastage) is integrated with the land-based analytics system.