基于高斯过程的研究核反应堆堆芯密度分布预测

IF 0.4 4区 物理与天体物理 Q4 PHYSICS, MULTIDISCIPLINARY
N. V. Smolnikov, M. N. Anikin, A. G. Naimushin, I. I. Lebedev
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引用次数: 0

摘要

研究堆采用局部换料方式运行,导致局部区域功率密度分布不均匀性高。这些区域影响燃料消耗的经济效率和反应堆堆芯的可靠性。这就需要功率密度分布剖面,并强调了在反应堆堆芯非均质结构中识别功率分布形成模式的重要性。本研究对该反应堆在不同燃料负荷下的运行经验进行了分析,确定了各单元内功率密度分布的特点。提出了一种应用机器学习模型预测IRT-T堆芯燃料电池功率密度分布不均匀性的方法。研究结果表明,应用监督学习概念和结合协方差(核)函数的高斯过程回归,可以在不考虑具体负载模式和燃料燃耗深度的情况下预测每个反应堆单元的功率分布参数。模型总体精度超过99 \(\%\),平均绝对误差不超过0.5 \(\%\)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Gaussian Process Based Prediction of Density Distribution in Core of Research Nuclear Reactor

Gaussian Process Based Prediction of Density Distribution in Core of Research Nuclear Reactor

Research nuclear reactors operate in a partial refueling mode, which leads to the formation of local areas with high nonuniformity of power density distribution. Such areas impact the economic efficiency of fuel consumption and the reactor core reliability. This necessitates the power density distribution profiling and underscores the importance of identifying the patterns of power distribution formation within the heterogeneous structure of the reactor core. In this study, an analysis of the reactor’s operational experience under various fuel loadings was conducted, and the characteristics of power density distribution in each cell were determined. An approach to applying a machine learning model for predicting power density distribution nonuniformity across the fuel cells of the IRT-T reactor core is presented. It is shown that the application of the supervised learning concept and Gaussian process regression with combined covariance (kernel) function enables the prediction of power distribution parameters in each reactor cell, regardless of the specific loading pattern and fuel burnup depth. The model achieved an overall accuracy of over 99\(\%\), with a mean absolute error not exceeding 0.5\(\%\).

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来源期刊
Moscow University Physics Bulletin
Moscow University Physics Bulletin PHYSICS, MULTIDISCIPLINARY-
CiteScore
0.70
自引率
0.00%
发文量
129
审稿时长
6-12 weeks
期刊介绍: Moscow University Physics Bulletin publishes original papers (reviews, articles, and brief communications) in the following fields of experimental and theoretical physics: theoretical and mathematical physics; physics of nuclei and elementary particles; radiophysics, electronics, acoustics; optics and spectroscopy; laser physics; condensed matter physics; chemical physics, physical kinetics, and plasma physics; biophysics and medical physics; astronomy, astrophysics, and cosmology; physics of the Earth’s, atmosphere, and hydrosphere.
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