Tesi etd-05202025-111139 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
SAINATI, GIACOMO
URN
etd-05202025-111139
Titolo
Toward High-Fidelity multi-physics solutions – set up of APOLLO3® et TrioCFD coupling
Dipartimento
INGEGNERIA CIVILE E INDUSTRIALE
Corso di studi
INGEGNERIA NUCLEARE
Relatori
relatore Prof. Forgione, Nicola
tutor Dott. Lenain, Roland
correlatore Prof. Giusti, Valerio
tutor Dott. Lenain, Roland
correlatore Prof. Giusti, Valerio
Parole chiave
- apollo3®
- c3po
- external loose coupling
- icoco
- multi-physics coupling
- multi-scale
- neutronics
- pwr
- thedi
- thermal-hydraulics
- triocfd
Data inizio appello
04/06/2025
Consultabilità
Non consultabile
Data di rilascio
04/06/2095
Riassunto
The work carried out in collaboration with CEA presents the development and implementation of a high-fidelity multi-physics simulation framework designed for advanced nuclear reactor analysis through the coupling of the new generation deterministic neutronic code APOLLO3® and the computational fluid dynamics solver, TrioCFD. The coupling is built on a modular and flexible architecture based on the ICoCo and C3PO frameworks that manage the data exchange between the solvers. The core-level thermal-hydraulic solver THEDI has been implemented in the coupling framework as a first step toward enabling core-level multi-scale simulations.
To evaluate the proposed methodology, several simulations were performed, including nominal up to perturbed scenarios. The results confirmed the framework's ability to make accurate, reliable, and high-resolution predictions of key core parameters.
In addition, this work places strong emphasis on the automation of the entire workflow to significantly reduce the barrier to future applications, making high-fidelity analyses more accessible and reproducible. Thanks to its modular architecture, the framework can be extended beyond pressurized water reactor applications by adapting or replacing individual components.
To evaluate the proposed methodology, several simulations were performed, including nominal up to perturbed scenarios. The results confirmed the framework's ability to make accurate, reliable, and high-resolution predictions of key core parameters.
In addition, this work places strong emphasis on the automation of the entire workflow to significantly reduce the barrier to future applications, making high-fidelity analyses more accessible and reproducible. Thanks to its modular architecture, the framework can be extended beyond pressurized water reactor applications by adapting or replacing individual components.
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