The (Executable) Digital Twin: Merging the Digital and the Physical Worlds

While the Digital Twin has become an intrinsic part of the product creation process mostly based on physics models, its true power lies in the connectivity of the digital representation with its physical counterpart. Data acquired on the physical asset can validate, update and enrich the Digital Twin. Thus the Digital Twin itself integrates physics- and data-based models. The knowledge contained in the digital representation brings value to the physical asset itself. When a dedicated encapsulation is extracted from the Digital Twin to model a specific set of behaviors in a specific context, delivering a stand-alone executable representation, such instantiated and self-contained model is referred to as an Executable Digital Twin. In this contribution, key building blocks such as Model Order Reduction, real-time models, state estimation, and co-simulation are reviewed, and a number of characteristic industrial use cases based on our own experience are presented. These include virtual sensing, hybrid testing, hardware-in-the loop, model-based control and model-based diagnostics. While this chapter presents an overview on (Executable) Digital Twins, specific technologies and further use cases are reviewed in depth in the remainder of this book by the corresponding experts in the fields. (This chapter is based on a contribution to the conference proceeding of the 30th International Conference on Noise and Vibration engineering (ISMA2022).)