Towards multi-fidelity digital twins for dynamic adaption and efficient distributed simulation

Digital twin (DT) platforms are limited by resource requirements. While scaling such platforms would be possible, the associated cost could be rather expensive. Furthermore, the number of DT-enabled systems is increasing, ranging from individual DTs to fleets of DTs and composite DTs. To handle the complexity, we propose in this paper four modes of operation for DTs, including individual DT execution, fleets, composites, and multi-fidelity DTs. For each, we present a resource profile in order to characterize their operation. We showcase our framework and the resource profiling through a case-study, covering the case of individual DT execution.