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:10.2166/wst.2022.107

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

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › Research › peer-review

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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 language	English
Journal	Water Science and Technology
Volume	85
Issue number	10
Pages (from-to)	2840-2853
Number of pages	14
ISSN	0273-1223
DOIs	https://doi.org/10.2166/wst.2022.107
Publication status	Published - 2022

Keywords

Data management
Hybrid models
Interoperability
Model predictive control
Online optimisation
Proactive management

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title = "The transition of WRRF models to digital twin applications",

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.",

keywords = "Data management, Hybrid models, Interoperability, Model predictive control, Online optimisation, Proactive management",

author = "Elena Torfs and Niels Nicola{\"i} and Saba Daneshgar and Copp, {John B.} and Henri Haimi and David Ikumi and Bruce Johnson and Plosz, {Benedek B.} and Spencer Snowling and Townley, {Lloyd R.} and Borja Valverde-P{\'e}rez and Vanrolleghem, {Peter A.} and Luca Vezzaro and Ingmar Nopens",

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AU - Torfs, Elena

AU - Nicolaï, Niels

AU - Daneshgar, Saba

AU - Copp, John B.

AU - Haimi, Henri

AU - Ikumi, David

AU - Johnson, Bruce

AU - Plosz, Benedek B.

AU - Snowling, Spencer

AU - Townley, Lloyd R.

AU - Valverde-Pérez, Borja

AU - Vanrolleghem, Peter A.

AU - Vezzaro, Luca

AU - Nopens, Ingmar

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - Data management

KW - Hybrid models

KW - Interoperability

KW - Model predictive control

KW - Online optimisation

KW - Proactive management

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DO - 10.2166/wst.2022.107

M3 - Journal article

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SN - 0273-1223

VL - 85

SP - 2840

EP - 2853

JO - Water Science and Technology

JF - Water Science and Technology

IS - 10

ER -

The transition of WRRF models to digital twin applications

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Keywords

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