Validating Kraken for VVER-1000 fuel cycle simulations using the X2 benchmark

Ville Valtavirta; Antti Rintala

doi:10.1016/j.anucene.2023.109878

Validating Kraken for VVER-1000 fuel cycle simulations using the X2 benchmark

Ville Valtavirta (Corresponding Author), Antti Rintala

BA4501 Reactor analysis

Research output: Contribution to journal › Article › Scientific › peer-review

Abstract

This article contributes to the validation of the Kraken framework for VVER-1000 fuel cycle modelling. Four fuel cycles from the X2 VVER-1000 benchmark are simulated along with the start-up tests at the beginning of each cycle. Predicted boron letdown curves, power distributions and start-up test results for the four fuel cycles are compared to measured data from the benchmark as well as the results of similar reactor analysis tools. The comparisons to measured data show that Kraken performs well in the task. The accuracy of Kraken is comparable to other nodal diffusion based solvers.

Original language	English
Article number	109878
Number of pages	14
Journal	Annals of Nuclear Energy
Volume	190
DOIs	https://doi.org/10.1016/j.anucene.2023.109878
Publication status	Published - 15 Sept 2023
MoE publication type	A1 Journal article-refereed

Keywords

Ants
Fuel cycle
Kraken
Serpent
VVER-1000
X2 benchmark

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10.1016/j.anucene.2023.109878Licence: CC BY

Cite this

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title = "Validating Kraken for VVER-1000 fuel cycle simulations using the X2 benchmark",

abstract = "This article contributes to the validation of the Kraken framework for VVER-1000 fuel cycle modelling. Four fuel cycles from the X2 VVER-1000 benchmark are simulated along with the start-up tests at the beginning of each cycle. Predicted boron letdown curves, power distributions and start-up test results for the four fuel cycles are compared to measured data from the benchmark as well as the results of similar reactor analysis tools. The comparisons to measured data show that Kraken performs well in the task. The accuracy of Kraken is comparable to other nodal diffusion based solvers.",

keywords = "Ants, Fuel cycle, Kraken, Serpent, VVER-1000, X2 benchmark",

author = "Ville Valtavirta and Antti Rintala",

note = "Funding Information: The authors thank Thomas L{\"o}tsch for providing the reference data and specifications for the X2 benchmark. This work has received funding from the LONKERO project under the Finnish National Research Programme on Nuclear Power Plant Safety, SAFIR2022. This work has received funding from the DECAPOD project under the Finnish National Nuclear Safety and Waste Management Research Programme 2023–2028, SAFER2028.",

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N2 - This article contributes to the validation of the Kraken framework for VVER-1000 fuel cycle modelling. Four fuel cycles from the X2 VVER-1000 benchmark are simulated along with the start-up tests at the beginning of each cycle. Predicted boron letdown curves, power distributions and start-up test results for the four fuel cycles are compared to measured data from the benchmark as well as the results of similar reactor analysis tools. The comparisons to measured data show that Kraken performs well in the task. The accuracy of Kraken is comparable to other nodal diffusion based solvers.

AB - This article contributes to the validation of the Kraken framework for VVER-1000 fuel cycle modelling. Four fuel cycles from the X2 VVER-1000 benchmark are simulated along with the start-up tests at the beginning of each cycle. Predicted boron letdown curves, power distributions and start-up test results for the four fuel cycles are compared to measured data from the benchmark as well as the results of similar reactor analysis tools. The comparisons to measured data show that Kraken performs well in the task. The accuracy of Kraken is comparable to other nodal diffusion based solvers.

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Validating Kraken for VVER-1000 fuel cycle simulations using the X2 benchmark

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Keywords

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