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Sensitivity analysis of CHF parameters under flow instability by using a neural network method

机译：用神经网络方法对流量不稳定条件下CHF参数的敏感性分析

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摘要

Construct the predicting model of CHF based on BP neural network. The sensitivity coefficients of different parameters could be calculated by solving partial differential of the predicting model. With the method of neural network connection weight sensitivity analysis and the data from other researchers' experiments, the sensitivity of different factors to the critical heat flux (CHF) is analyzed. The result shows that, ΔG_(max)/G_0 has the largest sensitivity coefficients to CHF and the inlet temperature has the smallest sensitivity coefficients in the test range. The sensitivity of ΔG_(max)/G_0 could be 20 times of that of the inlet temperature. The BP predictions of CHF fit well with the experimental data, and the errors fall in the margin of 5%. The BP predictions of the influences of ΔG_(max)/G_0 and τ to CF_m fit well with Kim's formula, and the largest error is 12.5％.
机译：基于BP神经网络构建CHF预测模型。通过求解预测模型的偏微分，可以计算出不同参数的灵敏度系数。利用神经网络连接权重敏感性分析方法和其他研究人员的实验数据，分析了不同因素对临界热通量（CHF）的敏感性。结果表明，在测试范围内，ΔG_（max）/ G_0对CHF的灵敏度系数最大，入口温度的灵敏度系数最小。 ΔG_（max）/ G_0的灵敏度可以是入口温度的20倍。 CHF的BP预测与实验数据非常吻合，误差下降了5％。 BP预测ΔG_（max）/ G_0和τ对CF_m的影响与Kim公式吻合得很好，最大误差为12.5％。

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  • 来源
    《Annals of nuclear energy》 |2014年第9期|211-216|共6页
  • 作者

    Li Jingjing; Zhou Tao; Ju Zhongyun; Huo Qijun; Xiao Zejun;

  • 作者单位

    Nuclear Safety and Thermal Power Standardization Institute, North China Electric Power University, Changping District, Beijing 102206, China;

    Nuclear Safety and Thermal Power Standardization Institute, North China Electric Power University, Changping District, Beijing 102206, China;

    Nuclear Safety and Thermal Power Standardization Institute, North China Electric Power University, Changping District, Beijing 102206, China;

    Nuclear Safety and Thermal Power Standardization Institute, North China Electric Power University, Changping District, Beijing 102206, China;

    CNNC Key Laboratory on Nuclear Reactor Thermal Hydraulics Technology, Chengdu 610041, Sichuan Province, China;

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

    Flow oscillation; Critical of heat flux; Neural network; Sensitivity analysis;

    机译：流动振荡;临界热通量;神经网络;敏感性分析;

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