• Title of article

    Degradation Prediction of Rail Tracks: A Review of the ExistingLiterature

  • Author/Authors

    Elkhoury, Najwa Civil and Infrastructure Engineering Discipline - School of Engineering - RMIT University, Melbourne, Australia , Hitihamillage, Lalith Civil and Infrastructure Engineering Discipline - School of Engineering - RMIT University, Melbourne, Australia , Moridpour, Sara Robert, Dilan Civil and Infrastructure Engineering Discipline - School of Engineering - RMIT University, Melbourne, Australia

  • Pages
    17
  • From page
    88
  • To page
    104
  • Abstract
    Abstract: In the past few decades, the railway infrastructure has been widely expanded in urban and rural areas, making it the mostcomplex matrix of rail transport networks. Safe and comfortable travel on railways has always been a common goal fortransportation engineers and researchers, and requires railways in excellent condition and well-organized maintenance practices.Degradation of rail tracks is a main concern for railway organizations as it affects the railway’s behaviour and its parameters, such astrack geometry, speed, traffic and loads. Therefore, the prediction of the degradation of rail tracks is very important in order tooptimise maintenance needs, reduce maintenance and operational costs of railways, and improve rail track conditions.This paper provides a comprehensive review of rail degradation prediction models, their parameters, and the strengths andweaknesses of each model. A comprehensive discussion of existing research and a comparison of different models of degradation ofrail tracks is also provided. Finally, this review presents concluding remarks on the limitations of existing studies and providesrecommendations for further research and appraisal practices
  • Farsi abstract
    فاقد چكيده فارسي
  • Keywords
    Rail Track , Degradation , Rail , Prediction , Parameters , Variables , Deterioration , Models
  • Journal title
    Open Transportation Journal
  • Serial Year
    2018
  • Record number

    2563870