• DocumentCode
    2362675
  • Title

    Neural networks with NARX structure for material lifetime assessment application

  • Author

    Hidayat, Mas Irfan P ; Yusoff, Puteri Sri Melor M ; Berata, Wajan

  • Author_Institution
    Mater. Eng. Dept., Sepuluh Nopember Inst. of Technol. (ITS), Surabaya, Indonesia
  • fYear
    2011
  • fDate
    20-23 March 2011
  • Firstpage
    273
  • Lastpage
    278
  • Abstract
    In the present paper, neural networks (NN) with non-linear auto-regressive exogenous inputs (NARX) structure is developed and further applied for material lifetime assessment application. Rational of the use of the NARX structure in the application was emphasized and linked to the concept of constant life diagram (CLD), the well known concept in fatigue of material analysis and design. Fatigue life assessment was then performed and realized as one-step ahead prediction with respect to each stress level corresponding to stress ratio values arranged in such a way that transition took place from a fatigue region to another one in the CLD. As a result, material lifetime assessment can be fashioned for a wide spectrum of loading in an efficient manner. The simulation results for different materials and loading situations are presented and discussed.
  • Keywords
    autoregressive processes; fatigue; materials science computing; neural nets; NARX structure; constant life diagram; fatigue life assessment; material lifetime assessment application; neural networks; nonlinear auto-regressive exogenous input structure; Artificial neural networks; Data models; Fatigue; Loading; Materials; Predictive models; Stress; CLD; Lifetime Assessment; NARX; Neural Networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers & Informatics (ISCI), 2011 IEEE Symposium on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-61284-689-7
  • Type

    conf

  • DOI
    10.1109/ISCI.2011.5958926
  • Filename
    5958926