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Development and validation of isotope prediction module for VVER spent nuclear fuel analysis

이덕중|장재림
한국원자력학회 (Korean Nuclear Society)|2024.05|Nuclear Engineering and Technology|제56권 제5호|pp. 1762-1776|DOI 10.1016/j.net.2023.12.032

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키워드

Spent nuclear fuelVVERBack-end cycle analysisNovovoronezh-4Burnup credit
주제분류원자력공학

초록

A spent nuclear fuel (SNF) analysis module for the Vodo-Vodyanoi Energetichesky Reactor (VVER) was developed and validated in this study. This advancement expands the application area of the existing nodal diffusion code, RAST-V, and reduces the need for additional code during 3D core simulations for SNF analysis, leading to increased efficiency in simulation time. RAST-V uses Lagrange interpolation and a power correction factor derived from the Bateman equation to bypass the re-depletion calculations, which are used to solve the microdepletion chain. This approach improved the efficiency of analysis. To mirror the conditions during the 3D core simulations, the module used history indices related to the moderator temperature, fuel temperature, and boron concentration. The module can predict 1620 isotopes. This paper presents the validation of this isotope inventory prediction and the application of burnup credit. The VVER analysis module was validated using 28 samples discharged from the Novovoronezh-4. Most isotopes were within 10 % of the boundaries of the measurements. This study successfully offers verification results using VVER benchmarks and discusses the application of burnup credit using a VVER-440 cask.

Abstract

A spent nuclear fuel (SNF) analysis module for the Vodo-Vodyanoi Energetichesky Reactor (VVER) was developed and validated in this study. This advancement expands the application area of the existing nodal diffusion code, RAST-V, and reduces the need for additional code during 3D core simulations for SNF analysis, leading to increased efficiency in simulation time. RAST-V uses Lagrange interpolation and a power correction factor derived from the Bateman equation to bypass the re-depletion calculations, which are used to solve the microdepletion chain. This approach improved the efficiency of analysis. To mirror the conditions during the 3D core simulations, the module used history indices related to the moderator temperature, fuel temperature, and boron concentration. The module can predict 1620 isotopes. This paper presents the validation of this isotope inventory prediction and the application of burnup credit. The VVER analysis module was validated using 28 samples discharged from the Novovoronezh-4. Most isotopes were within 10 % of the boundaries of the measurements. This study successfully offers verification results using VVER benchmarks and discusses the application of burnup credit using a VVER-440 cask.

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