Applying digital twin technology to the modeling, monitoring, and optimization of railway infrastructure

This article examines how digital twin technology can be used to model, monitor, and optimize railway infrastructure. It describes the technological basis of railway digital twins, including how information models are built and how diagnostic data are used to assess the condition of infrastructure assets. The article reviews methods for fault prediction, repair planning, and improving maintenance efficiency, and analyzes experience with digital twins deployed for railway track, bridges, and stations. It identifies the main constraints on the technology: data integration, software interoperability, and information security. The review shows that digital twins expand the possibilities for modeling, monitoring, and managing the condition of railway infrastructure, and the international experience examined confirms that they are practically applicable to individual assets and infrastructure systems. Their effectiveness, however, depends on the reliability of input data, the interoperability of information platforms, and the quality of the computational models used. Finally, the article outlines promising directions for developing digital twins within railway infrastructure management systems.