• Title of article

    Cavitation Damage Prediction on Dam Spillways using Fuzzy-KNN Modeling

  • Author/Authors

    Fadaei Kermani, E Department of Civil Engineering - Faculty of Engineering - Shahid Bahonar University of Kerman, Kerman, Iran , Barani, G. A Department of Civil Engineering - Faculty of Engineering - Shahid Bahonar University of Kerman, Kerman, Iran , Ghaeini Hessaroeyeh, M Department of Civil Engineering - Faculty of Engineering - Shahid Bahonar University of Kerman, Kerman, Iran

  • Pages
    7
  • From page
    323
  • To page
    329
  • Abstract
    The present paper deals with a numerical method for prediction of cavitation damage level and location on dam spillways. A method was applied to predict the intensity of cavitation damage to spillways, using the fuzzy k-nearest neighbor algorithm. Five levels of damage intensity were considered to predict cavitation damage in the spillway of Karun-1 Dam in Iran. According to the results, the proposed model could properly predict the location and intensity of damage in comparison with the actual damage reports of past floods. According to the Pearson's correlation coefficient, mean absolute error, coefficient of residual mass, and normalized root mean square error, the fuzzy k-nearest neighbor model is efficient and suitable.
  • Keywords
    Damage intensity , Fuzzy k-nearest neighbor model , Cavitation damage , Spillways
  • Journal title
    Astroparticle Physics
  • Serial Year
    2018
  • Record number

    2468623