The transition of WRRF models to digital twin applications

Elena Torfs, Niels Nicolai, Saba Daneshgar, John Copp, Henry Haimi, David Ikumi, Bruce Johnson, Benedek Plosz, Spencer Snowling, Lloyd Townley, Borja Valverde-Pérez, Peter A. Vanrolleghem, Luca Vezzaro, Ingmar Nopens

Research output: Contribution to journalArticlepeer-review

37 Citations (SciVal)

Abstract

Digital Twins (DTs) are on the rise as innovative, powerful technologies to harness the power of digitalisation in the WRRF sector. The lack of consensus and understanding when it comes to the definition, perceived benefits and technological needs of DTs is hampering their widespread development and application. Transitioning from traditional WRRF modelling practice into DT applications raises a number of important questions: When is a model's predictive power acceptable for a DT? Which modelling frameworks are most suited for DT applications? Which data structures are needed to efficiently feed data to a DT? How do we keep the DT up to date and relevant? Who will be the main users of DTs and how to get them involved? How do DTs push the water sector to evolve? This paper provides an overview of the state-of-the-art, challenges, good practices, development needs and transformative capacity of DTs for WRRF applications.
Original languageEnglish
JournalWater Science and Technology
Volume85
Issue number10
Early online date31 Mar 2022
DOIs
Publication statusPublished - 15 May 2022

Acknowledgements

This position paper gives an overview of the discussion that took place at the similarly titled workshop of the (virtual) 7th IWA/WEF Water Resource Recovery Modelling Seminar WRRmod2021. It is the result of a collective effort by industry practitioners and academics who are gratefully acknowledged for all their input. The work of Niels Nicolaï and Peter Vanrolleghem was supported by the Natural Sciences and Engineering Research Council of Canada Discovery Grant RGPIN-2021-04347 towards digital twin based control of water resource recovery facilities - Methods supporting the use of adaptive hybrid digital twins.

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