Historical Perspective of the Development of Digital Twins

Grand challenges in mathematical biology: Integrating multi-scale modeling and data

“…A digital twin is a computer replica of a real-life system [e.g., cells [45], tissues [46], or even natural environment [47]], which allows us to integrate real-time and historical data and information about their functionality with the goal of making predictions about their future. This concept, which initially emerged in 1960's in the engineering field [48,49], is not always very clear, mainly due to the interpretation of the connection between the data and the mathematical model. In Figure 2 we summarize the three sub-categories proposed by Kritzinger et al [50] based on the level of data integration, while adapting them to biological systems [51]: (a) in a digital model, the data between the biological object and the digital object is exchanged manually; (b) in a digital shadow the data flow from the biological object to the digital object is automatic, while The diagram shows a caricature description of various cell-cell interactions (at cell/tissue levels) and a zoom-in on a single cell and protein dynamics inside this cell (at molecular-level), to emphasize the multi-scale aspect of some of these biological digital objects.…”

A Structure-Preserving Machine Learning Framework for Accurate Prediction of Structural Dynamics for Systems with Isolated Nonlinearities

“…Digital Twins represent advanced models with detailed physics that are augmented and updated by ongoing data obtained from sensor systems embedded in the physical systems [5,6]. As a result they offer an enhanced ability to monitor the evolving health of a system and predict the future response to both nominal operating conditions and unexpected excursions in loading environments [7][8][9][10].…”