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A Bayesian model to assess rail track geometry degradation through its life-cycle

Author

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  • Andrade, António Ramos
  • Teixeira, Paulo Fonseca

Abstract

One of the major drawbacks in rail track investments is the high level of uncertainty in maintenance, renewal and unavailability costs for the Infrastructure Managers (IM) during the life-cycle of the infrastructure. Above all, rail track geometry degradation is responsible for the greatest part of railway infrastructure maintenance costs. Some approaches have been tried to control the uncertainty associated with rail track geometry degradation at the design stage, though little progress has improved the investors' confidence. Moreover, many studies on rail track life-cycle cost modelling tend to forget the dynamic perspective in uncertainty assessments and do not quantify the expected reduction of the uncertainty associated with degradation parameters as more inspection data is collected after operation starts.

Suggested Citation

  • Andrade, António Ramos & Teixeira, Paulo Fonseca, 2012. "A Bayesian model to assess rail track geometry degradation through its life-cycle," Research in Transportation Economics, Elsevier, vol. 36(1), pages 1-8.
    • Handle: RePEc:eee:retrec:v:36:y:2012:i:1:p:1-8
    DOI: 10.1016/j.retrec.2012.03.011
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    Cited by:

    1. Ana Cabrera-Tobar & Alessandro Massi Pavan & Giovanni Petrone & Giovanni Spagnuolo, 2022. "A Review of the Optimization and Control Techniques in the Presence of Uncertainties for the Energy Management of Microgrids," Energies, MDPI, vol. 15(23), pages 1-38, December.
    2. Hui Shang & Christophe Bérenguer & John Andrews, 2017. "Delayed maintenance modelling considering speed restriction for a railway section," Journal of Risk and Reliability, , vol. 231(4), pages 411-428, August.

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