Water Science and Technology (May 2022)

The transition of WRRF models to digital twin applications

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

DOI
https://doi.org/10.2166/wst.2022.107
Journal volume & issue
Vol. 85, no. 10
pp. 2840 – 2853

Abstract

Read online

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. HIGHLIGHTS A Digital Twin distinguishes itself from a simulation model by a continuous, automated data connection.; Current DT projects in WRRFs focus on operational support and control.; Combining mechanistic models and data-driven techniques into hybrid models can accelerate the adoption of DTs.; Data and information models are key for the implementation and upscaling of DTs.; WRRF staff should be included during the development stages of DTs.;

Keywords