Doctoral student in Hybrid AI for Sustainable Management of Water Distribution SystemsW/M

Descrizione

Doctoral student in Hybrid AI for Sustainable Management of Water Distribution SystemsW/M Sintesi in italiano (traduzione automatica): L'organizzazione i3WaterS, composta da università, centri di ricerca e aziende del settore idrico in Europa, offre un'opportunità per 15 Dottorandi nel campo dell'AI ibrida per la gestione sostenibile dei sistemi di distribuzione dell'acqua. Il progetto mira a sviluppare soluzioni innovative per ottimizzare la gestione delle risorse idriche, affrontando le sfide legate alla scarsità d'acqua e ai cambiamenti climatici. I candidati parteciperanno a un programma di formazione specifico, acquisendo competenze in monitoraggio delle reti, gestione dei dati e tecniche di intelligenza artificiale. È richiesta una laurea in ingegneria ambientale o un campo correlato. Le principali mansioni includono lo sviluppo di modelli idraulici avanzati e tecniche di simulazione per migliorare la gestione operativa dei sistemi di distribuzione dell'acqua, garantendo qualità e riducendo le perdite. Hybrid AI for Sustainable Management of Water Distribution Systems (WP3) + i3WaterS i3WaterS brings together leading universities, research centres, technology developers and water utilities across Europe. The project will train 15 Doctoral Candidates to develop innovative AI-driven solutions for intelligent, resilient and sustainable water systems, contributing to the digital transformation of one of the most critical infrastructures for society. The risk of water scarcity due to climate change and human activities is real. i3WaterS stands for Intelligent, Innovative, Integrative Water Systems and addresses the urgent need to optimize water resources management by providing a comprehensive solution to upgrade, optimally operate and maintain water distribution systems (WDSs). For the first time, a unique holistic approach will find the key interrelationships between external, day-to-day and extreme, factors and WDS failures, to advise actions and protocols to make WDSs robust and reliable. At research level, i3WaterS project focuses on the integration of data, specific expert knowledge and computational simulations tools, introducing the most advanced data-driven and artificial intelligent techniques beyond the State of the Art, that plugged in a newly developed intelligent decision support system (IDSSs), working as an umbrella for a set of 14 independent solutions that enables assisting the WDSs management into scientifically driven decision-making. The incorporation of artificial intelligence (AI) will help to increase the autonomy of some parts of the WDS, those suitable under a paradigm of maximum security, safety and robustness, and the project will take care to frame this autonomy in a global and general concept of intelligent assistance, including human validation in each steps where it makes sense 15 Doctorate Candidates will learn from a network of experts on network monitoring, data management, algorithms, AI, modeling, microbiology, ethics and industrial partners, and by participating in a specifically designed training programme, they will develop the required cross competencies to find, test and innovate over a solution that will be fundamental to meet the sustainable development goals on water. Just as important, i3WaterS provide a new generation of internationally connected professionals with unique skills for the development of thriving careers in the critical infrastructures. Research Objectives The objective of the project is the protection of drinking water distribution systems (WDSs) and their consumers from the adverse impacts of climate change and human activities. For the first time, a unique holistic approach will identify the key interrelationships between external, day-to-day, and extreme factors and WDS failures, advising actions and protocols to make WDSs robust and reliable. The purpose of this PhD research is to develop tools and methods for sustainable management of water distribution networks. Specifically, operational management will aim to regulate pressure and velocity within the distribution system. This will help to achieve two primary objectives: ensuring water quality and minimizing leakage. The specific research objective of this offer is To develop advanced hydraulic and numerical modelling techniques that improve the simulation, calibration and operational management of drinking water distribution systems under complex and dynamic conditions. The candidate will contribute with the following subobjectives: Objectives: 1) Increase the detection threshold and location of leakage flows for real case studies, using only pressure data;. 2) Sustainable operation of a WDS network (with pressure and flow regulation) to reduce background leakage, sedimentation, and pipe fatigue. 3) Adapt a WDN to extreme events and mitigate degraded service levels. Exp. Results: 1) New hybrid AI algorithms for a better detection and localization of leakage. 2) Gain measurements for addit