Leveraging digital twins for data-driven operation for the Chuo Shinkansen

In recent years, the use of digital twins, which reproduce physical systems in a virtual space, has spread rapidly in various industries. This study focuses on the concept of digital twin and investigates how to leverage data and models for the superconducting Maglev system for the Chuo Shinkansen. Using an architectural diagram that organizes the data and model management/utilization framework, this paper explains the concept of the digital twins to achieve data-driven, efficient operation of the Chuo Shinkansen and present the idea of 'integrated models,' which are key to generating a wide range of use cases of digital twins. As a proof-of-concept (PoC) test of "future prediction," a representative use case by the integrated models, a ground coil temperature prediction test was conducted on the Yamanashi Maglev Line. The results of the study provide valuable insights into the potential and challenges of the digital twin, offering a valuable perspective on its practical implementation.