NUCLEAR TECHNIQUES, Volume. 46, Issue 11, 110604(2023)

Development and analysis of a K-nearest-neighbor-based transient identification model for molten salt reactor systems

Tianze ZHOU1,2, Kaicheng YU2,3, Maosong CHENG2,3、*, and Zhimin DAI1,2,3、**
Author Affiliations
  • 1ShanghaiTech University, Shanghai 201210, China
  • 2Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
  • 3University of Chinese Academy of Sciences, Beijing 100049, China
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    Figures & Tables(23)
    Development process of the system transient identification model
    KNN-based system transient identification model for the MSR system
    Framework of the KNN-based system transient identification model
    RELAP5-TMSR nodalization of the MSRE
    Hyper-parameter optimization results of the KNN-based system transient identification model
    Confusion matrix for the KNN-based system transient identification model
    Robustness test results
    Hyper-parameter optimization results of the system transient identification model trained on noisy data
    Confusion matrix for the KNN-based system transient identification model trained using noisy data on noiseless test datasets
    Confusion matrix for the KNN-based system transient identification model trained using noisy data on noisy test datasets
    Robustness test results of the system transient identification model trained on noisy data
    • Table 1. Hyper-parameters of KNN-based system transient identification model

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      Table 1. Hyper-parameters of KNN-based system transient identification model

      超参数Hyper-parameter选取范围Range selected
      邻近点数Number of neighbors[1~10]
      邻近点查找方法Algorithm to search neighbors[“auto”, “ball_tree”, “kd_tree”, “brute”]
      距离计算方法Method to calculate distance[1, 2]
      邻近点权重方式Method to weight neighbors[“uniform”, “distance”]
    • Table 2. MSRE operation condition type

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      Table 2. MSRE operation condition type

      运行工况Operation condition详细描述Description
      NOR稳态运行Steady state
      LOF_1燃料泵故障Fuel circulating pump failure
      LOF_2冷却剂泵故障Coolant circulating pump failure
      SBO全场断电Station black out
      URW_11根控制棒误提升Uncontrolled withdrawal of 1 control rod
      URW_22根控制棒误提升Uncontrolled withdrawal of 2 control rods
      URW_33根控制棒误提升Uncontrolled withdrawal of 3 control rods
      FSL_hot热段燃料盐泄漏Fuel salt leakage in hot leg
      FSL_cold冷段燃料盐泄漏Fuel salt leakage in cold leg
      CSL_hot热段冷却盐泄漏Coolant salt leakage in hot leg
      CSL_cold冷段冷却盐泄漏Coolant salt leakage in cold leg
    • Table 3. Feature parameters of identification in MSR system

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      Table 3. Feature parameters of identification in MSR system

      特征参数Feature parameter单位Unit
      功率PowerMW
      堆芯出口温度Core outlet temperatureK
      堆芯进口温度Core inlet temperatureK
      二回路热段温度Secondary hot leg temperatureK
      二回路冷段温度Secondary cold leg temperatureK
      堆芯出口压力Core outlet pressurekPa
      堆芯进口压力Core inlet pressurekPa
      二回路热段压力Secondary hot leg pressurekPa
      二回路冷段压力Secondary cold leg pressurekPa
      燃料盐质量流量Fuel salt mass flow ratekg·s-1
      冷却盐质量流量Coolant salt mass flow ratekg·s-1
    • Table 4. Binary classification results

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      Table 4. Binary classification results

      真实标签

      True label

      预测标签Predicted label
      10
      1TPFN
      0FPTN
    • Table 5. Hyper-parameters optimization results of KNN-based system transient identification model

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      Table 5. Hyper-parameters optimization results of KNN-based system transient identification model

      超参数Hyper-parameter优化结果Optimization results
      邻近点数Number of neighbors2
      邻近点查找方法Algorithm to search neighbors“auto”
      距离计算方法Method to calculate distance1
      邻近点权重方式Method to weight neighbors“distance”
    • Table 6. Test results of KNN-based identification models

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      Table 6. Test results of KNN-based identification models

      准确率

      Accuracy

      精确率

      Precision

      召回率

      Recall

      F1分数

      F1-score

      测试结果Test results99.99%99.99%99.99%99.99%
    • Table 7. F1-score of individual transient

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      Table 7. F1-score of individual transient

      运行工况

      Operation condition

      F1分数

      F1-score / %

      NOR100.00
      LOF100.00
      LOF_2100.00
      SBO100.00
      URW_1100.00
      URW_299.94
      URW_399.94
      FSL_hot100.00
      FSL_cold100.00
      CSL_hot100.00
      CSL_cold100.00
    • Table 8. Results of system transient identification model under 30 dB SNR

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      Table 8. Results of system transient identification model under 30 dB SNR

      准确率

      Accuracy

      精确率

      Precision

      召回率

      Recall

      F1分数

      F1-score

      测试结果Test results97.41%94.47%94.61%94.31%
    • Table 9. Hyper-parameters optimization results of system transient identification model trained by data with noise

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      Table 9. Hyper-parameters optimization results of system transient identification model trained by data with noise

      超参数Hyper-parameter优化结果Optimization results
      邻近点数Number of neighbors1
      邻近点查找方法Algorithm to search neighbors“kd tree”
      距离计算方法Method to calculate distance2
      邻近点权重方式Method to weight neighbors“uniform”
    • Table 10. Results of KNN-based system transient identification model trained by data with noise on noiseless test datasets

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      Table 10. Results of KNN-based system transient identification model trained by data with noise on noiseless test datasets

      准确率

      Accuracy

      精确率

      Precision

      召回率

      Recall

      F1分数

      F1-score

      测试结果Test results99.69%99.26%99.22%99.22%
    • Table 11. Results of KNN-based noise-added system transient identification model in test datasets

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      Table 11. Results of KNN-based noise-added system transient identification model in test datasets

      准确率

      Accuracy

      精确率

      Precision

      召回率

      Recall

      F1分数

      F1-score

      测试结果Test results99.89%99.73%99.73%99.73%
    • Table 12. F1-scores of individual transients using KNN-based system transient identification model trained by data with noise

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      Table 12. F1-scores of individual transients using KNN-based system transient identification model trained by data with noise

      运行工况

      Operation condition

      F1分数

      F1-score / %

      NOR100.00
      LOF100.00
      LOF_2100.00
      SBO100.00
      URW_199.61
      URW_298.77
      URW_398.62
      FSL_hot100.00
      FSL_cold100.00
      CSL_hot100.00
      CSL_cold100.00
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    Tianze ZHOU, Kaicheng YU, Maosong CHENG, Zhimin DAI. Development and analysis of a K-nearest-neighbor-based transient identification model for molten salt reactor systems[J]. NUCLEAR TECHNIQUES, 2023, 46(11): 110604

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    Paper Information

    Category: Research Articles

    Received: Apr. 24, 2023

    Accepted: --

    Published Online: Dec. 23, 2023

    The Author Email:

    DOI:10.11889/j.0253-3219.2023.hjs.46.110604

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