An integrated simulator towards a digital twin for MW-class Gyrotrons for fusion reactors

In magnetic-confinement fusion reactor technology, gyrotrons are foreseen to deliver power to the plasma through mm-microwaves at a pre-determined frequency within the range of 80−200GHz and power of 1−2MW. Today, only specific models focusing on specific components or specific physics of the gyrotron are available, but an overall simulator is missing. The development of a comprehensive simulator capable of describing the entire gyrotron behaviour, including its inherent nonlinearities, is crucial for accurate simulations, sensitivity analyses, operational optimization, and control purposes and represents an essential part for the definition of a new digital twin. The gyrotron is a complex device governed by multi-physics phenomena, thus the development of a simulator capable to simulate its complex dynamics requires the knowledge of the fundamental physics that describes the behaviour of all components. The goal is to develop a complete simulator of gyrotron, based on a fixed geometry and materials already selected, describing the components as objects which elaborate parameter inputs to get outputs. It is shown that in this way, the components can be seen as different boxes, the interconnections of which allow to build the simulator for the entire device. By adopting a state–space formulation, the interconnection between input and output of different blocks can be effectively managed, and through system linearization, an efficient stability analysis can be performed. In this work, each component is presented, together with its physics. The input and output parameters are then identified in order to understand how they influence the coupling between the component models and their connection. This procedure will help to build in future works the simulator of the gyrotron, aiming at developing a digital twin for it. The latter, articulated from the aggregation of simpler component models, could become a useful tool to perform complex simulations, stability analysis, optimization and control.