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TWIN - Real-time digital twins for thermofluid mechanics

36 mesi (2023 - 2026)
Responsabile scientifico:
Tipo di progetto:
PNRR – Missione 4
Ente finanziatore:
Codice identificativo progetto:
Ruolo PoliTo:
Contraente Unico


My research vision is to create a multi-disciplinary framework and toolbox to seamlessly combine high- performance computing, machine learning and quantum computing to revolutionise understanding and modelling of thermofluid mechanics. This will culminate in the creation of real-time digital twins to optimise and control engineering systems. The multi-disciplinary project (TWIN) will cross-pollinate the fundamental computational methods developed in the ERC Starting Grant PhyCo into new real-world applications in multi-physics thermofluid mechanics. From an engineering design point of view, TWIN will transfer the physics-constrained machine learning technology of the ERC Starting Grant PhyCo to large-scale problems for the optimal engineering design of thermofluids for sustainable aviation and sustainable energy. The overarching objective of TWIN is to create engineering systems’ real-time digital twins that are (i) consistent with the physics of the problem, such as the laws of mechanics and thermodynamics; (ii) adaptive, i.e., they self-correct and adapt by learning from data from sensors; (iii) real-time, i.e., the adaptivity occurs on- the-fly anytime that new data from sensors become available; and (iv) able to manipulate the engineering system to control it and make it operate in safe conditions. To achieve this, the project will assimilate experimental and high-fidelity data on-the-fly into digital twins, with a computational speed up provided by quantum algorithms. The pioneering research of this project is two-fold. First, the real-time digital twins will practically address key design questions in sustainable aviation and energy with fast, scalable, and accurate models: (i) the real-time optimisation of wind farms to maximise the power output; and (ii) the real-time modelling and control of hydrogen-based gas-turbine acoustic instabilities for aircraft propulsion and energy conversion. Second, the real-time digital twins will be converted with quantum algorithms to exploit the exponential computational speed-up from the quantum advantage. The outcome of TWIN will directly contribute to the EU goals towards a net-zero society, and the computational revolution with artificial intelligence and quantum computing.

Persone coinvolte

Dipartimenti coinvolti

Parole chiave

Settori ERC

PE8_5 - Fluid mechanics, hydraulic-, turbo-, and piston engines


Costo totale progetto: € 1.000.000,00
Contributo totale progetto: € 1.000.000,00
Costo totale PoliTo: € 1.000.000,00
Contributo PoliTo: € 1.000.000,00