The Horizon Europe Project, ReNEW, uses the digital twin concept to simulate and model the complexity and interdependencies of the Inland Waterway Transport (IWT) system. This concept is used to design novel strategies to ensure network functionality despite climate change impacts on IWT. A digital twin is an accurate copy of a real object/item/system with associated characteristics in the digital world. Digital twin models can be developed using physics or statistics or combining the two. They can be used for simulation, classification, prediction, optimization, and more. This work proposes probabilistic digital twin modelling of complex IWT networks using Bayesian networks. Bayesian networks are statistical models that can address the complexity and uncertainty of the physical world. The availability of new data/information facilitates model updates, resulting in more accurate estimates.

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Modelling Probabilistic Digital Twins of Complex Inland Waterway Transportation Systems Using Bayesian Networks

  • Alexandra Micu,
  • Lorcan Connolly,
  • Alan O’Connor,
  • Eugene O’Brien,
  • Caitriona de Paor

摘要

The Horizon Europe Project, ReNEW, uses the digital twin concept to simulate and model the complexity and interdependencies of the Inland Waterway Transport (IWT) system. This concept is used to design novel strategies to ensure network functionality despite climate change impacts on IWT. A digital twin is an accurate copy of a real object/item/system with associated characteristics in the digital world. Digital twin models can be developed using physics or statistics or combining the two. They can be used for simulation, classification, prediction, optimization, and more. This work proposes probabilistic digital twin modelling of complex IWT networks using Bayesian networks. Bayesian networks are statistical models that can address the complexity and uncertainty of the physical world. The availability of new data/information facilitates model updates, resulting in more accurate estimates.