Rail Temperature Prediction Model as a Tool to Issue Advance Heat Slow Orders

摘要

Track buckling due to excessive rail temperature may cause derailments with serious consequences. To minimize the risk of derailments, slow orders are typically issued on sections of track in areas where an elevated rail temperature is expected and risk of track buckling is increased. The Federal Railroad Administration's (FRA's) Office of Research and Development (ORD) has sponsored the development of a model for predicting rail temperatures using weather forecast data and predefined track parameters. The rail temperature prediction process was validated by comparing the model's output to rail temperatures measured at 23 sites throughout the CSX Transportation (CSXT) network between March 2012 and October 2012. Detection theory was used to evaluate the model's ability to correctly identify rail temperatures elevated above a wide range of thresholds in comparison to the current railroad practice of estimating rail temperature based on constant offsets above predicted peak ambient air temperature. The results are very favorable. Analysis indicates that use of the model offers advantages over the current practices in terms of identifying elevated rail temperatures with the potential for track buckling and that the implementation of the model as a heat slow order management tool would lead to improvements in safety without a negative economic impact on railroad operations since heat slow orders would be issued in more effective and targeted way. The model was also used to determine rail temperatures reached during past track buckle related derailments and showed that the railroad would benefit from implementation of flexible thresholds for elevated rail temperatures to identify buckling concerns.