The Water Network Tool for Resilience (WNTR) is a Python package widely used for the simulation and analysis of Water Distribution Networks (WDNs), providing tools such as network modification, pressure-dependent demand simulation, and resilience evaluation. Although it produces time-varying data reflecting WDN activity, it requires the complete parameter configuration at the beginning of the simulation and it requires a full restart when modifying network parameters such as pipe leaks or demand variations. Here, we present Dyn-WNTR, an extension that enables dynamic adaptation of network parameters during simulation. By integrating novel functions for real-time network updates, Dyn-WNTR allows modifications, such as the introduction of leaks or demand variations, without requiring a simulation restart. This significantly improves the flexibility of hydraulic simulations, allowing more efficient scenario testing, real-time optimization, and adaptive control strategies. We also release a dataset with dynamic simulations under diverse operating conditions and network events. To encourage a broad use and future developments, the source code of Dyn-WNTR and the dataset are publicly available. By reducing computational costs and improving flexibility, Dyn-WNTR extends the capabilities of WNTR towards more advanced and real-time frameworks, particularly suited for reinforcement learning applications and digital twin modeling, where continuous interaction with the simulation environment is essential.

Dyn-WNTR: dynamic network adaptive extension for hydraulic simulations with WNTR / Locatelli, P., Cattai, T., Palumbo, S., Cuomo, F.. - (2025). (IFIP Networking 2025 Limassol; Ciprus ).

Dyn-WNTR: dynamic network adaptive extension for hydraulic simulations with WNTR

Pierluigi Locatelli
;
Tiziana Cattai;Simone Palumbo;Francesca Cuomo
2025

Abstract

The Water Network Tool for Resilience (WNTR) is a Python package widely used for the simulation and analysis of Water Distribution Networks (WDNs), providing tools such as network modification, pressure-dependent demand simulation, and resilience evaluation. Although it produces time-varying data reflecting WDN activity, it requires the complete parameter configuration at the beginning of the simulation and it requires a full restart when modifying network parameters such as pipe leaks or demand variations. Here, we present Dyn-WNTR, an extension that enables dynamic adaptation of network parameters during simulation. By integrating novel functions for real-time network updates, Dyn-WNTR allows modifications, such as the introduction of leaks or demand variations, without requiring a simulation restart. This significantly improves the flexibility of hydraulic simulations, allowing more efficient scenario testing, real-time optimization, and adaptive control strategies. We also release a dataset with dynamic simulations under diverse operating conditions and network events. To encourage a broad use and future developments, the source code of Dyn-WNTR and the dataset are publicly available. By reducing computational costs and improving flexibility, Dyn-WNTR extends the capabilities of WNTR towards more advanced and real-time frameworks, particularly suited for reinforcement learning applications and digital twin modeling, where continuous interaction with the simulation environment is essential.
2025
IFIP Networking 2025
water network, Internet of Things, simulation, real-time
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Dyn-WNTR: dynamic network adaptive extension for hydraulic simulations with WNTR / Locatelli, P., Cattai, T., Palumbo, S., Cuomo, F.. - (2025). (IFIP Networking 2025 Limassol; Ciprus ).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1775017
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