Accelerating the optimisation of water-tube boiler performance using a digital twin: a case study using simulated datasets

A case study is presented on the development of a digital twin for an industrial water-tube boiler using simulated datasets derived from operational scenarios to model the system behaviour. The twin was built upon a theoretical thermodynamic and heat transfer model that was refined and calibrated using operational data representing key operational states. By leveraging these datasets, the digital twin can provide a snapshot of the current operation of the boiler. This cost-effective approach is particularly useful for retrofitting older plants where operational data may be limited. The integration of the digital twin with live operational data allows operators to compare predicted outcomes with real-time performance, helping to schedule maintenance activities and visual inspections more effectively. By offering a real-time evaluation of boiler health, this methodology enables operators to prioritize tasks and improve overall system efficiency.