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CFD analysis of coolant mixing in VVER-1000/V320 reactor pressure vessel

Böttcher, M. 1; Bernard, O.; Mas, A.; Sanchez, V. ORCID iD icon 1; Nop, R.; Belaunde, F.; Bourcier, C.; Ruban, D.; Hashymov, A.; Halim, O. ; Pucciarelli, A.; Forgione, N.
1 Institut für Neutronenphysik und Reaktortechnik (INR), Karlsruher Institut für Technologie (KIT)

Abstract:

This study presents a code-to-code and model-to-model comparison of coolant mixing in the VVER-1000/V320 Kozloduy Unit 6 nuclear power plant using Computational Fluid Dynamics (CFD). Four different CFD codes were used to simulate coolant mixing in the reactor vessel, namely ANSYS Fluent, ANSYS CFX, TrioCFD, and STAR-CCM+. Two different approaches were used to model the upper plenum, while a single simplified model was
used for the reactor pressure vessel. The simulations were performed for VVER-1000 coolant transient benchmark (V1000CT-2) mixing exercise. The results were compared between the different CFD codes and models to assess the accuracy and consistency of the simulations with the available experimental data. Overall, the results showed good agreement between the different CFD codes and models, with minor differences observed in some cases. The simplified models were found to be sufficient for predicting the overall coolant mixing patterns observed in the reactor vessel, provided additional insights into the local flow structures and mixing characteristics. This study demonstrates the applicability and reliability of CFD simulations for coolant mixing analysis in VVER-1000/V320 nuclear power plants.


Verlagsausgabe §
DOI: 10.5445/IR/1000166011
Veröffentlicht am 04.01.2024
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Neutronenphysik und Reaktortechnik (INR)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 03.2024
Sprache Englisch
Identifikator ISSN: 0306-4549, 1873-2100
KITopen-ID: 1000166011
HGF-Programm 32.12.01 (POF IV, LK 01) Design Basis Accidents and Materials Research
Erschienen in Annals of Nuclear Energy
Verlag Elsevier
Band 197
Seiten Art.-Nr.: 110274
Vorab online veröffentlicht am 06.12.2023
Nachgewiesen in Web of Science
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Scopus
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