Tradeoffs For Federal Government Use of Digital Twins

 A digital twin is a digital representation of a physical object, system, or process that provides feedback and/or control to the physical system using simulation, artificial intelligence/machine learning (AI/ML), and optimization. It is designed to replicate real-world conditions and behaviors and is continuously updated with data from sensors on its physical counterpart.

While both a digital twin and a model can represent real-world entities, a model is typically a static or predefined representation of a system that does not provide direct feedback and control. In contrast, a digital twin is dynamic, continuously evolving based on real-time data feeds from its physical counterpart. It therefore offers a more holistic and up-to-date representation of its state and performance, enabling real-time feedback and control.