Abstract

Coarse mesh nodal methods are widely used in the analysis of nuclear reactors. However, these methods provide only average values of the neutron fluxes. From a safety point of view, it is important to have an accurate analysis of the pin to pin flux distribution that nodal methods are not able to provide. Many articles have been published that make use of mathematical techniques to determine flux distributions. Most of these techniques use expansion functions to estimate these distributions. The expansion coefficients of these works are determined by conditions that take into account the average values of certain fluxes supplied by the nodal methods. There are also methods that employ analytical solutions of the neutron diffusion equation. This article presents a different approach for calculating the pin to pin neutron flux distribution for a PWR reactor. The developed method uses support vector regression (SVR) technique to determine this pin to pin neutron flux. The SVR technique uses average data computed with the Nodal Expansion Method (NEM) for learning purposes. A total of 70% of the computed data were used for training and 30% for validation, using multifold-cross-validation. Two fuel elements were removed from the training and validation sets, to test the method. Less than 2% errors were found when compared to the values ​​obtained by the nodal expansion method (NEM), using a fine-mesh spatial discretization. We concluded that use of SVR to reconstruct pin to pin fluxes is another option, which will be of great value in fuel reload calculations, since the same parameters will be applied to all cycles, thus expediting calculations when compared to standard procedure calculations.

Highlights

  • The nodal expansion method (NEM) [1] is widely used in reactor physics calculations

  • With the support vector regression (SVR) technique, we were able to compute pin fluxes, so that the error for the fuel elements tested were lower than 2%

  • With the optimal parameters defined, the algorithm provides the values of the pin to pin fluxes for each test fuel assembly in negligible time. These results show that the machine learning technique using SVR is able to reconstruct the pin to pin fluxes

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Summary

Introduction

The nodal expansion method (NEM) [1] is widely used in reactor physics calculations. This method divides the reactor core into well-defined volumes, called nodes (n), with cross sections of the order of the fuel element crosssectional dimensions. NEM is only able to provide nodal average results, as the nodal average neutron fluxes (fng ), and if we are treating thermal reactors, usually two neutron groups are used These values do not include detailed information of the neutron flux at each position of the fuel element, namely, the pin to pin neutron flux (fg,hom (x, y)). Examining in a more detailed way the problem of reconstruction, it can be concluded that all of these procedures make use of correlations between the average nodal fluxes, determined by coarse mesh nodal methods, and pin to pin neutron flux values. These parameters have to be determined in order to obtain important safety related variables, like hot channel factors. A new procedure is proposed to reconstruct the detailed pin to pin flux distribution in a PWR reactor, and results obtained demonstrate the feasibility of the procedure

Literature review
N ðji þ jÃi Þ
N À aiðe þ ji À yi þ w Á xi þ bÞ
Fundamental problem
Methodology
Reconstruction for two fuel rods using the same parameters of learning
Neutron flux pin to pin reconstruction for two elements
Findings
Conclusions
Full Text
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