RECONSTRUCTION OF CORE OVERHEATING DAMAGE FRACTION BASED ON NEURAL NETWORK METHOD

被引:0
|
作者
Li, Wenjing [1 ]
Yang, Xiaoming [1 ]
Yu, Xinli [1 ]
机构
[1] China Nucl Power Engn Co LTD, 117 Xisanhuanbeilu, Beijing, Peoples R China
关键词
Neural network; Core overheating damage fraction; Reconstruction;
D O I
暂无
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
Core damage assessment is of great importance to the emergency response of nuclear power plants. In this paper, the neural network method is introduced into the core damage assessment process. The hydrogen concentration, together with the temperature and pressure in the containment, are taken as the input parameters of the model. With the simulated result of MAAP codes as the sample data, a neural network model is developed to reconstruct the core overheating damage fraction. According to the calculation of the neural network model, the deviations of the reconstructed results are quite small compared with the simulation results, and one of the typical errors is 1.76%. It can be concluded that the model based on neural network method satisfies the analysis accuracy requirements and can be used as a diverse analytical tool in the core damage assessment of nuclear power plant.
引用
收藏
页数:4
相关论文
共 50 条
  • [21] A Structure Damage Diagnosis Method Based on Wavelet Packet Transform and Neural Network
    Liu, Y. -Y.
    Ju, Y. -F.
    Duan, C. -D.
    He, Y-Y
    2011 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION AND INDUSTRIAL APPLICATION (ICIA2011), VOL III, 2011, : 168 - 171
  • [22] Model-Embedding based Damage Detection Method for Recurrent Neural Network
    Weng, Shun
    Lei, Aoqi
    Chen, Zhidan
    Yu, Hong
    Yan, Yongyi
    Yu, Xingsheng
    Hunan Daxue Xuebao/Journal of Hunan University Natural Sciences, 2024, 51 (07): : 21 - 29
  • [23] STRUCTURAL DAMAGE IDENTIFICATION METHOD BASED ON ROUGH SET AND PROBABILISTIC NEURAL NETWORK
    Jiang, Shao-Fei
    Yao, Juan
    PROCEEDINGS OF THE TENTH INTERNATIONAL SYMPOSIUM ON STRUCTURAL ENGINEERING FOR YOUNG EXPERTS, VOLS I AND II, 2008, : 1579 - 1584
  • [24] A Structure Damage Diagnosis Method Based on Wavelet Packet Transform and Neural Network
    Liu, Y. -Y.
    Ju, Y. -F.
    Duan, C. -D.
    He, Y-Y
    2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL VIII, 2010, : 168 - 171
  • [25] Neural network method based on a new damage signature for structural health monitoring
    Yuan, SF
    Wang, L
    Peng, G
    THIN-WALLED STRUCTURES, 2005, 43 (04) : 553 - 563
  • [26] Multi-Stage Damage Identification Method Based on Integrated Neural Network
    Yang, Ya-Xun
    Yu, Hai-Bo
    Chai, Wen-Hao
    Yang, Fu-Li
    CICTP 2020: ADVANCED TRANSPORTATION TECHNOLOGIES AND DEVELOPMENT-ENHANCING CONNECTIONS, 2020, : 1675 - 1684
  • [27] Convolutional neural network-based damage detection method for building structures
    Oh, Byung Kwan
    Glisic, Branko
    Park, Hyo Seon
    SMART STRUCTURES AND SYSTEMS, 2021, 27 (06) : 903 - 916
  • [28] Flowfield Reconstruction Method Using Artificial Neural Network
    Yu, Jian
    Hesthaven, Jan S.
    AIAA JOURNAL, 2019, 57 (02) : 482 - 498
  • [29] A new method based on artificial neural network techniques for determining the fraction of binaries in star clusters
    SerraRicart, M
    Aparicio, A
    Garrido, L
    Gaitan, V
    ASTROPHYSICAL JOURNAL, 1996, 462 (01): : 221 - 230
  • [30] A neural network based UHE neutrino reconstruction method for the Askaryan Radio Array (ARA)
    Pan, Yue
    37TH INTERNATIONAL COSMIC RAY CONFERENCE, ICRC2021, 2022,