Neural network applied to prediction of the failure stress for a pressurized cylinder containing defects

被引：9
|
作者：
Han, LH [1 ]
Han, LX [1 ]
Liu, CD [1 ]
机构：
[1] Tsing Hua Univ, Inst Nucl Energy Technol, CAD, Beijing 100084, Peoples R China
来源：
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING | 1999年 / 76卷 / 04期
关键词：
neural network; pressurized cylinder; failure stress;
D O I：
10.1016/S0308-0161(98)00129-X
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
An application of the neural network to predict the failure stress of a cylinder with penetrating flaws under internal pressure is studied in this article, The results from the new method are compared with the experimental results. In addition, the neural network method is used to analyze the sensitivity of parameters of a pressurized cylinder with defects. Satisfactory results are obtained. It is shown that the neural network could be a potential tool in engineering practice. (C) 1999 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码：215 / 219
页数：5
相关论文
共 50 条
  • [11] Artificial neural network applied to austenite formation temperatures prediction
    You, W
    Bai, BZ
    Fang, HS
    Xie, XS
    ACTA METALLURGICA SINICA, 2004, 40 (11) : 1133 - 1137
  • [12] Asynchronous Synthesis of a Neural Network Applied on Head Load Prediction
    Varacha, P.
    NOSTRADAMUS: MODERN METHODS OF PREDICTION, MODELING AND ANALYSIS OF NONLINEAR SYSTEMS, 2013, 192 : 225 - 240
  • [13] Fuzzy neural network model applied in the traffic flow prediction
    Tong, Gang
    Fan, Chunling
    Cui, Fengying
    Meng, Xiangzhong
    2006 IEEE INTERNATIONAL CONFERENCE ON INFORMATION ACQUISITION, VOLS 1 AND 2, CONFERENCE PROCEEDINGS, 2006, : 1229 - 1233
  • [14] Empirical Failure Pressure Prediction Equations for Pipelines with Longitudinal Interacting Corrosion Defects Based on Artificial Neural Network
    Vijaya Kumar, Suria Devi
    Lo, Michael
    Karuppanan, Saravanan
    Ovinis, Mark
    JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2022, 10 (06)
  • [15] NEURAL NETWORK PREDICTION OF STRESS-CORROSION CRACKING
    SMETS, HMG
    BOGAERTS, WFL
    MATERIALS PERFORMANCE, 1992, 31 (09) : 64 - 67
  • [16] Physics informed neural network for dynamic stress prediction
    Hamed Bolandi
    Gautam Sreekumar
    Xuyang Li
    Nizar Lajnef
    Vishnu Naresh Boddeti
    Applied Intelligence, 2023, 53 : 26313 - 26328
  • [17] Physics informed neural network for dynamic stress prediction
    Bolandi, Flamed
    Sreekumar, Gautam
    Li, Xuyang
    Lajnef, Nizar
    Boddeti, Vishnu Naresh
    APPLIED INTELLIGENCE, 2023, 53 (22) : 26313 - 26328
  • [18] Residual stress prediction using neural network approach
    Menda, František
    More, Marcel
    Cardona-Cuervo, G.P.
    Martinez-Tabares, F.J.
    Applied Mechanics and Materials, 2014, 611 : 436 - 440
  • [19] PRESSURIZED WATER-REACTOR CORE PARAMETER PREDICTION USING AN ARTIFICIAL NEURAL NETWORK
    KIM, HG
    CHANG, SH
    LEE, BH
    NUCLEAR SCIENCE AND ENGINEERING, 1993, 113 (01) : 70 - 76
  • [20] Prediction of safety parameters of pressurized water reactor based on feature fusion neural network
    Chen, Yinghao
    Wang, Dongdong
    Kai, Cao
    Pan, Cuijie
    Yu, Yayun
    Hou, Muzhou
    ANNALS OF NUCLEAR ENERGY, 2022, 166
12345