Maccari, Pietro
(2022)
Modelling and Uncertainty Quantification
application to SA simulation codes in advanced SMR, [Dissertation thesis], Alma Mater Studiorum Università di Bologna.
Dottorato di ricerca in
Meccanica e scienze avanzate dell'ingegneria, 34 Ciclo. DOI 10.48676/unibo/amsdottorato/10122.
Documenti full-text disponibili:
Abstract
In the framework of a global transition to a low-carbon energy mix, the interest in advanced nuclear Small Modular Reactors (SMRs) has been growing at the international level. Due to the high level of maturity reached by Severe Accident Codes for currently operating rectors, their applicability to advanced SMRs is starting to be studied. Within the present work of thesis and in the framework of a collaboration between ENEA, UNIBO and IRSN, an ASTEC code model of a generic IRIS reactor has been developed. The simulation of a DBA sequence involving the operation of all the passive safety systems of the generic IRIS has been carried out to investigate the code model capability in the prediction of the thermal-hydraulics characterizing an integral SMR adopting a passive mitigation strategy. The following simulation of 4 BDBAs sequences explores the applicability of Severe Accident Codes to advance SMRs in beyond-design and core-degradation conditions.
The uncertainty affecting a code simulation can be estimated by using the method of Input Uncertainty Propagation, whose application has been realized through the RAVEN-ASTEC coupling and implementation on an HPC platform. This probabilistic methodology has been employed in a study of the uncertainty affecting the passive safety system operation in the DBA simulation of ASTEC, providing a further characterization of the thermal-hydraulics of this sequence. The application of the Uncertainty Quantification method to early core-melt phenomena has been investigated in the framework of a BEPU analysis of the ASTEC simulation of the QUENCH test-6 experiment. A possible solution to the encountered challenges has been proposed through the application of a Limit Surface search algorithm.
Abstract
In the framework of a global transition to a low-carbon energy mix, the interest in advanced nuclear Small Modular Reactors (SMRs) has been growing at the international level. Due to the high level of maturity reached by Severe Accident Codes for currently operating rectors, their applicability to advanced SMRs is starting to be studied. Within the present work of thesis and in the framework of a collaboration between ENEA, UNIBO and IRSN, an ASTEC code model of a generic IRIS reactor has been developed. The simulation of a DBA sequence involving the operation of all the passive safety systems of the generic IRIS has been carried out to investigate the code model capability in the prediction of the thermal-hydraulics characterizing an integral SMR adopting a passive mitigation strategy. The following simulation of 4 BDBAs sequences explores the applicability of Severe Accident Codes to advance SMRs in beyond-design and core-degradation conditions.
The uncertainty affecting a code simulation can be estimated by using the method of Input Uncertainty Propagation, whose application has been realized through the RAVEN-ASTEC coupling and implementation on an HPC platform. This probabilistic methodology has been employed in a study of the uncertainty affecting the passive safety system operation in the DBA simulation of ASTEC, providing a further characterization of the thermal-hydraulics of this sequence. The application of the Uncertainty Quantification method to early core-melt phenomena has been investigated in the framework of a BEPU analysis of the ASTEC simulation of the QUENCH test-6 experiment. A possible solution to the encountered challenges has been proposed through the application of a Limit Surface search algorithm.
Tipologia del documento
Tesi di dottorato
Autore
Maccari, Pietro
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
34
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Small Modular Reactor, Nuclear Power Plant, Severe Accident, Safety, Thermal-hydraulics, Simulation, Uncertainty Quantification, Simulation Code, Automatic Algorithm, High Performance Computing
URN:NBN
DOI
10.48676/unibo/amsdottorato/10122
Data di discussione
11 Aprile 2022
URI
Altri metadati
Tipologia del documento
Tesi di dottorato
Autore
Maccari, Pietro
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
34
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Small Modular Reactor, Nuclear Power Plant, Severe Accident, Safety, Thermal-hydraulics, Simulation, Uncertainty Quantification, Simulation Code, Automatic Algorithm, High Performance Computing
URN:NBN
DOI
10.48676/unibo/amsdottorato/10122
Data di discussione
11 Aprile 2022
URI
Statistica sui download
Gestione del documento: