Probabilistic model for predicting rail breaks and controlling risk of derailment

J Zhao, Andrew Chan, Michael Burrow

Research output: Contribution to journalArticle

19 Citations (Scopus)


A model is developed to analyze the risk of derailment of railway vehicles by using a probabilistic approach to model the development of rail defects leading to rail breaks and further to derailment. The risk of derailment is measured by the expected number of rail breaks multiplied by the severity of rail break. To evaluate the risk, four submodels are combined to predict the rate of occurrence of rail defects and breaks. These submodels include one to predict the expected number of weld defects, considering the effect of rail repair; a fatigue model of the rails; and a grinding model to take into account removal of defects through maintenance. The fourth submodel concerns the impact of inspections that are imperfect and of nonconstant frequency. The performance and application of the proposed combined model are illustrated by an example that shows the effectiveness of alternative measures in reducing the risk of derailment. It also shows that the proposed model can be used as a tool for quantitatively evaluating the risk of derailment and for decision making on control of the risk.
Original languageEnglish
Pages (from-to)76-83
Number of pages8
JournalTransportation Research Record
Issue number1995
Publication statusPublished - 1 Jan 2007


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