• DocumentCode
    2572898
  • Title

    Research on Landslide Mechanism Based upon the Geo-material Parameter Identification

  • Author

    Kang-mei Guo ; Jing-lei Liu

  • Author_Institution
    Sch. of Civil & Environ. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China
  • fYear
    2009
  • fDate
    2-3 May 2009
  • Firstpage
    47
  • Lastpage
    50
  • Abstract
    The genetic algorithm and its actual application for the parameter identification are represented. Based upon the in-situ investigation of one loess landslide in Gansu, the key parameter in the slope stability analysis, the depth of rainwater infiltration (DRI), is identified utilizing the genetic algorithm. DRI is proposed as a boundary above which the soil is regarded as saturated, and beneath which is not. A detailed analysis for the landslide is carried out using the genetic algorithm and the software FLAC / SLOPE. The results show that landslide will take place when DRI reaches a certain value and the shear strength parameters are reduced in the soil above this boundary. The genetic algorithm is proved very suitable for the parameter identification in the slope stability analysis. The mechanism of the loess landslide is a rainwater infiltration caused landslide where the upper soil body pushes the lower soil body.
  • Keywords
    genetic algorithms; geophysics computing; rain; shear strength; soil; FLAC software; Gansu; SLOPE software; genetic algorithm; geo-material parameter identification; landslide mechanism; rainwater infiltration depth; shear strength parameters; slope stability analysis; soil; Accidents; Algorithm design and analysis; Biological cells; Civil engineering; Genetic algorithms; Genetic engineering; Parameter estimation; Soil; Stability analysis; Terrain factors; depth of rainwater infiltration; genetic algorithm; landslide; mechanism; parameter identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering Computation, 2009. ICEC '09. International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-0-7695-3655-2
  • Type

    conf

  • DOI
    10.1109/ICEC.2009.26
  • Filename
    5167088