Virtual, Digital and Hybrid Twins: A New Paradigm in Data-Based Engineering and Engineered Data

作者: Francisco Chinesta , Elias Cueto , Emmanuelle Abisset-Chavanne , Jean Louis Duval , Fouad El Khaldi

DOI: 10.1007/S11831-018-9301-4

关键词:

摘要: Engineering is evolving in the same way than society doing. Nowadays, data acquiring a prominence never imagined. In past, domain of materials, processes and structures, testing machines allowed extract that served turn to calibrate state-of-the-art models. Some calibration procedures were even integrated within these machines. Thus, once model had been calibrated, computer simulation takes place. However, can offer much more simple calibration, not only from its statistical analysis, but modeling viewpoints. This gives rise family so-called twins: virtual, digital hybrid twins. Moreover, as discussed present paper, serve enrich physically-based These could allow us perform tremendous leap forward, by replacing big-data-based habits incipient smart-data paradigm.

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