Adaptive digital twins for energy-intensive industries and their local communities

Adaptive digital twins for energy-intensive industries and their local communities

Digital Twins (DTs) are high-fidelity virtual models that behave-like, look-like and connect-to a physical system. In this work, the physical systems are operations and processes from energy-intensive industrial plants and their local communities. The creation of DTs demands expertise not just in en...

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Bibliographic Details
Main Authors: Timothy Gordon Walmsley, Panos Patros, Wei Yu, Brent R. Young, Stephen Burroughs, Mark Apperley, James K. Carson, Isuru A. Udugama, Hattachai Aeowjaroenlap, Martin J. Atkins, Michael R. W. Walmsley
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:Digital Chemical Engineering
Subjects:
Digital twin
Process simulation
Machine learning
Self-adative systems
Process control
Process integration
Online Access:http://www.sciencedirect.com/science/article/pii/S2772508124000012

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http://www.sciencedirect.com/science/article/pii/S2772508124000012

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