Description and objectives

Digital transition represents an opportunity to review and rationalize processes in order to increase their efficiency through replicability, scalability, integrability, and adaptability.

This proposal builds upon that opportunity and leverages the recent concept of a phenomenological twin, which is based on advanced hydraulics as a component of the digital twin of water supply systems, together with the equally recent “technology” of digital water services—that is, “engineering apps” integrating the key elements of digital transition (data and information, phenomenological twin, machine learning, complex network theory, evolutionary optimization for decision support, etc.).

The digital water services developed for predictive maintenance will be specifically designed to improve system reliability, which depends on the isolation valve network as well as on the level of real water losses—the latter being an indicator of the failure probability of the pipelines.

IDEA-RT already has strong know-how on the topics covered by the proposal, stemming from its academic partners who continuously transfer technical and scientific research to the non-academic world in real time.

Machine learning, possibly applied to data from the demonstrator, will be methodologically integrated with the advanced hydraulic modeling of the Parma water network, in order to develop or enhance digital water services supporting strategic planning for pipe replacement, the analysis and upgrading of the isolation valve system, the scheduling of field works, and more.
Finally, the new water loss indicator (Asset Management Support Indicator – AMSI) will be studied and integrated into the analyses.