Knowledge Graphs underpinning ship digital twins for decarbonisation options assessment

Abstract

We propose the concept of a Knowledge Graph as a data management and inference machinery that underpins digital twins of ships. The Knowledge Graph is a directed graph connecting dependent and independent model variables of interest in the digital twin, where the correlations between variables are continuously updated based on data received from the physical ship. The paper outlines a methodology for constructing the Knowledge Graph and proposes metrics that help to calculate the effectiveness of decarbonization solutions based on changes to the strength of data correlations. The proposed methodology allows for the extrapolation of decarbonization technology potential across specific vessels, fleets, operational patterns, and lifecycle phases.