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The Impact of Reactor Model Simplification for Fuel Evolution: A Bias Quantification for Fuel Cycle Dynamic Simulations

Abstract : In nuclear scenario studies, the use of simplified assembly models to simulate fuel irradiation in nuclear reactor core can lead to important biases. To calculate the spent fuel composition, the CLASS package (Core Library for Advanced Scenario Simulations) uses a physic model (usually, we define physics model as: 1- Fuel Loading Model, 2- Cross Section Predictor, 3- Bateman Solver), based on a large number of different fuel evolution simulations. For that, a simple and reproducible model has been chosen: the “assembly model” that is described in this paper. In this model, the whole core is represented by a single assembly, or a part of it, with reflecting boundary conditions. As a first step to quantify the errors related to this approximation, three real size assembly configurations have been simulated: a reflected one, an axial open one and a realistic one (with moderator and reflector at its top and bottom). An exhaustive comparison is presented in this paper. Hence this work focuses on the neutron axial leakage impact on burn-up and isotope inventories calculations. Evolutions up to 50 GWd/t have been simulated with the depletion code MURE for all the geometries and main isotope inventories, fission and capture cross sections and Keff have been reported for each time step. Axial leakage effects on neutron spectrum and inventory distributions have been observed. In this paper, a bias quantification of axial leakage and a comparison with homogeneous leakage models, available in the Serpent code, are analyzed.
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Conference papers
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Contributor : Sophie Heurteau Connect in order to contact the contributor
Submitted on : Tuesday, July 19, 2016 - 3:04:42 PM
Last modification on : Thursday, August 5, 2021 - 2:42:01 PM


  • HAL Id : in2p3-01346740, version 1


A. Somaini, S. David, X. Doligez, A.A. Zakari-Issoufou, A. Bidaud, et al.. The Impact of Reactor Model Simplification for Fuel Evolution: A Bias Quantification for Fuel Cycle Dynamic Simulations. 2016 International Congress on Advances in Nuclear Power Plants (ICAPP 2016), Apr 2016, San Francisco, United States. pp.1045-1053. ⟨in2p3-01346740⟩



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