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Stability improvement of noise analysis method in the case of random noise contamination for subcriticality measurements

机译：亚临界测量中随机噪声污染情况下噪声分析方法的稳定性改进

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摘要

The performances of five noise analysis methods (Rossi-alpha, cross-correlation, Feynman-alpha, Feyn-man difference, and power spectral density) have been evaluated for subcriticality measurement of nuclear reactors, and two new approaches have been proposed to improve the stability of k_(eff) estimations: (1) introduction of multiple detector signals and (2) new formulation of the Rossi-alpha method considering random noise contaminations. Modified thermal Godiva problem has been designed for the evaluations. The analysis was performed with fission count signals from the core of the Godiva model on three cases according to the level of random noise. The five noise analysis methods showed high accuracy of the estimated k_(eff) when there was no contamination. In the case of low level contamination, they showed stable results with acceptable accuracy. However, in the case of high level contamination, although the Rossi-alpha results still showed high accuracy, the stability of the five noise analysis methods was significantly decreased. In order to reduce the instability for estimating the k_(eff), two novel approaches were proposed: one is to design eight-detector model problem, and the other is to derive the advanced Rossi-alpha equation with consideration of random noise. In the eight-detector problem, one signal from the core is equally divided by three planes passing through the center of the model geometry and perpendicular to one another. It describes the situation using multiple detector signals to reduce the adverse impact of random noise contamination. On the other hand, the advanced Rossi-alpha formulation was used as the fitting curve equation for the evaluations. As a result, it was confirmed that the new approaches improved the stability of k_(eff) estimations.
机译：评估了五种噪声分析方法（Rossi-alpha，互相关，Feynman-alpha，Feyn-man差和功率谱密度）的性能，用于核反应堆的亚临界测量，并提出了两种新方法来改进核反应堆的运行。 k_（eff）估计的稳定性：（1）引入多个检测器信号，（2）考虑随机噪声污染的Rossi-alpha方法的新公式。修改后的热戈迪瓦问题已设计用于评估。根据Godiva模型核心的裂变计数信号，根据随机噪声的级别对三种情况进行了分析。当没有污染时，五种噪声分析方法显示出估计k_（eff）的高精度。在低水平污染的情况下，它们显示出稳定的结果，并具有可接受的精度。但是，在高水平污染的情况下，尽管Rossi-alpha结果仍然显示出较高的准确性，但五种噪声分析方法的稳定性却大大降低了。为了减少估计k_（eff）的不稳定性，提出了两种新颖的方法：一种是设计八探测器模型问题，另一种是在考虑随机噪声的情况下推导高级Rossi-alpha方程。在八探测器问题中，来自铁芯的一个信号被穿过模型几何中心且彼此垂直的三个平面均分。它描述了使用多个检测器信号来减少随机噪声污染的不利影响的情况。另一方面，先进的Rossi-alpha公式被用作拟合曲线方程式进行评估。结果，证实了新方法提高了k_（eff）估计的稳定性。

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  • 来源
    《Annals of nuclear energy》 |2014年第9期|245-253|共9页
  • 作者

    Chidong Kong; Deokjung Lee; Eunki Lee;

  • 作者单位

    Ulsan National Institute of Science and Technology, UNIST-gil 50, Eonyang-eup, Ulju-gun, Ulsan 689-798, Republic of Korea;

    Ulsan National Institute of Science and Technology, UNIST-gil 50, Eonyang-eup, Ulju-gun, Ulsan 689-798, Republic of Korea;

    Korea Hydro & Nuclear Power Corporation, 1312-70, Yuseong-daero, Yuseong-gu, Daejeon 305-343, Republic of Korea;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Noise analysis method; Rossi-alpha formulation; Random noise;

    机译：噪声分析方法;罗西-阿尔法配方;随机噪音;

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