Quantifying uncertainties of aspects of the neutronics modelling of the Kozloduy-6 system using SCALE 6.2.1
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This work is based on the benchmark for Uncertainty Analysis in Modelling (UAM) of light water reactors compiled by the Nuclear Energy Agency within the Organisation for Economic Cooperation and Development (OECD/NEA). The objective of the OECD/NEA benchmark is to form uncertainty bounds of results for calculations of LWRs based on operating data using best-estimate (BE) transport codes. The main contribution of this thesis to the OECD/NEA benchmark is the quantification of uncertainties in the Kozloduy-6 VVER-1000 reactor system using SCALE-6.2.1 methodology. The OECD/NEA benchmark consists of three phases, each with three exercises. Three reactor systems are also studied, viz. the PWR, VVER and BWR reactors. In this study, the first phase of the OECD/NEA benchmark was considered for the uncertainty quantification of the Kozloduy-6 VVER-1000 reactor system. The sources of uncertainties are classified into three groups, namely uncertainties due to nuclear data, uncertainties due to manufacturing tolerances and uncertainties due to numerical methods implementations. In order to identify the source of uncertainties in the system, as a first step, a local sensitivity analysis was performed for certain input data to obtain the input uncertainties that requires propagation. Thereafter, an uncertainty quantification was performed on the input data that showed substantial effect on the results. The calculations are performed using BE codes obtained from the SCALE 6.2.1 code system, i.e. KENO-VI and NEWT to perform the neutronics calculations and TSUNAMI-2D/3D and SAMPLER to perform the sensitivity and uncertainty analysis. The identified uncertain input data were further propagated on a fuel depletion analysis of the VVER-1000 system. The fuel depletion analyses were performed using TRITON of the SCALE 6.2.1 code. To validate the KENO-VI neutronics calculations, LR-0 benchmark tests were considered. Uncertainty quantification analysis was extended to this LR-0 system's neutronics calculations. As an addition, a verification of the LR-0 model was performed using NWURCS code. The principal input data related to the physical models and to the system description such as geometry, materials properties, etc. are characterised by their uncertainty ranges and probability distributions based on state-of-the-art knowledge (Blanchet, et al., 2007). The uncertainty due to nuclear data was obtained for both the OECD/NEA benchmark and the LR-0 benchmark models. The uncertainty due to nuclear data will vary, depending on the size and material of the system. Furthermore, it was shown that, although other parameters had an influence on the uncertainty, the nuclear data still remain as the highest contributor of uncertainty of a reactor system in terms of all input parameters considered in this study. Although this is true, the uncertainty due to other parameters must always be considered and be analysed together with the uncertainty due to nuclear data, since some of them could be significant.
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