Development of methods for the control and safety demonstration of Molten Salt Fast Reactors (MSFRs)
Riferimenti esterni - Nicolò Abrate (Politecnico di Torino)
- Dr. Stefano Lorenzi (Politecnico di Milano)
Gruppi di ricerca Nemo
The SAMOSAFER project, supported by the European Community through an H2020 grant, recently started (Oct 2019) with a 4-years program aiming at “develop and demonstrate new safety barriers for more controlled behavior of Molten Salt Reactors in severe accidents to ensure that the MSR can comply with all expected regulations in 30 years’ time” .
In SAMOSAFER WP6 “Reactor operation, Reactor control and Safety demonstration”, a specific task is devoted to the development of predictive control strategy and incident detection methods. This activity, involving the use of a simulator of the whole reactor plant (already developed by colleagues from Politecnico di Milano), aims at identifying the most important parameters affecting the system behavior, in order to develop monitoring strategy useful to timely detect behavior deviations that could lead to accidental sequences.
AIM OF THE WORK
In the general framework of the activities foreseen in the SAMOSAFER project, a thesis project can be devised with the following objectives :
- identification of possible initiators of accidents and abnormal reactor behaviors (e.g., components failures, plant parameters variations, …). This activity will rely on work already performed within a previous project on MSFRs (namely, SAMOFAR): in particular, the student will be provided with reports  and  (along with other documents) to this aim.
- exploration of the MSFR power plant state space: i) generation of several possible combinations of components failures and plant parameters variations (i.e., different possible accident initiators); ii) simulation of the corresponding time-varying (transient) behavior of the MSFR. This activity will entail the use of a reactor plant simulator and will require a (short) training in collaboration with Politecnico di Milano.
- detailed analysis of the time evolution of the main plant parameters (i.e., those parameters characterizing the state of the plant) and comparison with acceptability ranges (to identify safe and failed system configurations).
Prof. Nicola Pedroni (email@example.com), Prof. Sandra Dulla (firstname.lastname@example.org), Nicolò Abrate (email@example.com).
 SAMOSAFER Website, https://samosafer.eu/.
 E. Zio, P. Baraldi, N. Pedroni, Selecting Features for Nuclear Transients Classification by Means of Genetic Algorithms, IEEE Transactions on Nuclear Science, 53(3), 1479-1493, 2006.
 A. Cammi, S. Lorenzi, C. Tripodo, A. Laureau, E. Merle, D. Gerardin, D. Heuer, K. Mikityuk, D. Le Carpentier, SAMOFAR Deliverable 1.4 - Safety issues of normal operation conditions, Revision of May 2019.
 A. Uggenti, D. Gérardin, S. Beils, A. Carpignano, S. Dulla, D. Heuer, A. Laureau, J. Martinet, E. Merle, Identification of risks and phenomena involved, identification of accident initiators and accident scenarios. SAMOFAR Deliverable D1.6, 2018.
Note The thesis work will be developed in collaboration with the "Nuclear Reactors Group (NRG)" of the Politecnico di Milano.
Scadenza validita proposta 30/03/2023 PROPONI LA TUA CANDIDATURA