In the broad framework of the nuclear power plants (NPPs) industry, the dynamic probabilistic risk assessment could answer the time dependence deficiency of the event tree and fault tree analysis. The basic event tree approach relies on experts' pre-constructed accident sequences without exploring the time-dependent nature of an accident scenario, which could strongly affect the accident sequence. Conversely, the effects of events timing can be studied by adopting a dynamic event tree (DET) approach. Developing a DET methodology requires integrating a system code capable of replicating an accident scenario and a logic-driver code able to generate the event tree sequence, trigger plant safety systems, and manage other relevant events throughout the simulation. For this purpose, Methods for Estimation of Leakages and Consequences of Release (MELCOR) and reactor analysis and virtual control environment (RAVEN) have been coupled through a Python script developed by the Sapienza University of Rome, Rome, Italy, to perform DET studies during accident transients in fusion and fission reactors. RAVEN is a software tool developed at the Idaho National Laboratory (INL), Idaho Falls, ID, USA, to act as a control logic driver and post-processing tool for different applications. MELCOR for fusion is a fully integrated design basis and severe accident code that simulates thermal-hydraulic behavior and self-consistently accounting for aerosol transport in nuclear facilities and reactor cooling systems for the evaluation of the source term in fusion reactors. The coupling between these codes will provide a wide range of NPP risk assessment analyses, establishing new best practices. In this work, a preliminary DET study has been performed, selecting as initiating event an ex-vessel loss of coolant accident (LOCA) in the water-cooled lithium lead test blanket system (WCLL TBS) to be tested in International Thermonuclear Experimental Reactor (ITER). Time-dependent parameters such as the intervention of the plasma shutdown system and the closure of the main system isolation valves have been sampled to study evolving system scenarios.

Dynamic event tree analysis as a tool for risk assessment in nuclear fusion plants using RAVEN and MELCOR / D'Onorio, M.; Glingler, T.; Giannetti, F.; Caruso, G.. - In: IEEE TRANSACTIONS ON PLASMA SCIENCE. - ISSN 0093-3813. - (2022), pp. 1-7. [10.1109/TPS.2022.3165170]

Dynamic event tree analysis as a tool for risk assessment in nuclear fusion plants using RAVEN and MELCOR

D'Onorio M.
Primo
;
Glingler T.
Secondo
;
Giannetti F.
Penultimo
;
Caruso G.
Ultimo
2022

Abstract

In the broad framework of the nuclear power plants (NPPs) industry, the dynamic probabilistic risk assessment could answer the time dependence deficiency of the event tree and fault tree analysis. The basic event tree approach relies on experts' pre-constructed accident sequences without exploring the time-dependent nature of an accident scenario, which could strongly affect the accident sequence. Conversely, the effects of events timing can be studied by adopting a dynamic event tree (DET) approach. Developing a DET methodology requires integrating a system code capable of replicating an accident scenario and a logic-driver code able to generate the event tree sequence, trigger plant safety systems, and manage other relevant events throughout the simulation. For this purpose, Methods for Estimation of Leakages and Consequences of Release (MELCOR) and reactor analysis and virtual control environment (RAVEN) have been coupled through a Python script developed by the Sapienza University of Rome, Rome, Italy, to perform DET studies during accident transients in fusion and fission reactors. RAVEN is a software tool developed at the Idaho National Laboratory (INL), Idaho Falls, ID, USA, to act as a control logic driver and post-processing tool for different applications. MELCOR for fusion is a fully integrated design basis and severe accident code that simulates thermal-hydraulic behavior and self-consistently accounting for aerosol transport in nuclear facilities and reactor cooling systems for the evaluation of the source term in fusion reactors. The coupling between these codes will provide a wide range of NPP risk assessment analyses, establishing new best practices. In this work, a preliminary DET study has been performed, selecting as initiating event an ex-vessel loss of coolant accident (LOCA) in the water-cooled lithium lead test blanket system (WCLL TBS) to be tested in International Thermonuclear Experimental Reactor (ITER). Time-dependent parameters such as the intervention of the plasma shutdown system and the closure of the main system isolation valves have been sampled to study evolving system scenarios.
accidents; codes; dynamic probabilistic risk analysis (PRA); inductors; methods for estimation of leakages and consequences of release (MELCOR); nuclear safety; plasmas; probabilistic logic; probabilistic risk assessment; reactor analysis and virtual control environment (RAVEN).; Safety; TV
01 Pubblicazione su rivista::01a Articolo in rivista
Dynamic event tree analysis as a tool for risk assessment in nuclear fusion plants using RAVEN and MELCOR / D'Onorio, M.; Glingler, T.; Giannetti, F.; Caruso, G.. - In: IEEE TRANSACTIONS ON PLASMA SCIENCE. - ISSN 0093-3813. - (2022), pp. 1-7. [10.1109/TPS.2022.3165170]
File allegati a questo prodotto
File Dimensione Formato  
D’Onorio_Dynamic Event_2022.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 3.11 MB
Formato Adobe PDF
3.11 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
D’Onorio_Dynamic Event_Pre-print_2022.pdf

accesso aperto

Tipologia: Documento in Pre-print (manoscritto inviato all'editore, precedente alla peer review)
Licenza: Creative commons
Dimensione 1.08 MB
Formato Adobe PDF
1.08 MB Adobe PDF Visualizza/Apri PDF

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1632255
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact