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Centre for Digital Twins

The overall goal of the Aarhus University Centre for Digital Twins is to understand how to leverage existing engineering multi-models for the construction of digital twins. This entails improving the SoTA in co-simulation algorithms, understanding which multi-models are adequate for digital twin construction, and what kind of faults can be detected/diagnosed.

Attaining this goal implies tackling traditional tradeoffs, such as how detailed we need the cosimulation predicting the behaviour of the digital twin to be, versus how fast? But also new challenges, such as when can one declare that there is a mismatch between the observed behaviour of the original twin, and the simulated behaviour of the digital twin? Can we trust the co-simulation results enough to declare that the original system is faulty when there is a mismatch? What kind of decision support can be provided in analysing the consequences of alternative interventions?

The Aarhus University Centre for Digital Twins has seven overall tasks:

Getting data

Getting data about the physical CPSs from the physical sensors and actuators corresponding to the different constituent models from the multi-model of the CPS.

Semantic foundation

The semantic foundation of the INTO-CPS co-simulation will be expanded to cope with uncertainties.

Industrial cases

Industrial cases are used to test the limits of the research.


The Maestro co-simulation capability takes the time-series of data as input to the FMUs representing the multi-models or the digital version of the CPS.


We will produce a service enabling calibration/adaptation of a CPS, in particular in relation to its environment, in particular for applications such as the mobile robots.


The monitoring of the difference between how the physical CPS performs compared to what the co-simulation of the corresponding multi-model predicts will be added as a new service.

What-if analysis

Human operators need a capability to experiment with potential interactions in the control of the real CPS such that what-if analysis can be achieved.