• DocumentCode
    514807
  • Title

    Research of Functionally Graded Materials Database

  • Author

    Xiujuan, Zhang ; Yangang, Wei

  • Author_Institution
    Sch. of Mech. Eng., Dalian Jiaotong Univ., Dalian, China
  • Volume
    1
  • fYear
    2010
  • fDate
    6-7 March 2010
  • Firstpage
    655
  • Lastpage
    658
  • Abstract
    A FGM database is developed in this paper with the help of database management system, sub-database technologies, modules of material affinity and artificial neural network. In this database, the material relationship among constituents, distributions, and properties can be inquired and edited. The material information of constituents and distributions can be represented by sub-database of material distribution models. Material properties can be estimated by sub-database of material property estimation models and predicted by modules of material affinity and artificial neural network, respectively. Thus, this database provides an effective data management tool for FGMs, which greatly reduces the research time of FGMs and has the important guiding significance for developing the unknown FGMs.
  • Keywords
    database management systems; functionally graded materials; materials properties; neural nets; FGM database; artificial neural network; database management system; functionally graded materials database; material affinity modules; material distribution models; material information; material property estimation; sub-database technologies; Artificial neural networks; Composite materials; Database systems; Educational technology; Magnetic materials; Material properties; Materials science and technology; Mechanical engineering; Object oriented modeling; Spatial databases; FGMs database; estimation and prediction of material properties; modules of material affinity and artificial neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Education Technology and Computer Science (ETCS), 2010 Second International Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-6388-6
  • Electronic_ISBN
    978-1-4244-6389-3
  • Type

    conf

  • DOI
    10.1109/ETCS.2010.470
  • Filename
    5459096