Development of nighttime rail temperature prediction method using GIS data

Abstract

It is important to predict rail temperatures not only at high temperatures (daytime in summer) but also at low temperatures (nighttime in winter) to prevent track buckling. The aim of this study is to clarify the effect of the longwave radiation from the geographic features on the rail temperature and reflect it in rail temperature management. We proposed a new method capable of predicting the rail temperature distribution in nighttime at intervals of about 1 m by modeling the radiant heat of rail in detail using digital surface model (DSM) and meteorological data.

To verify its prediction accuracy, the distribution of rail temperature and radiant heat were measured on an actual track. As a result, the minimum rail temperature was about 2 °C high at the measurement points near buildings compared with that at other points due to strong radiant heat. This result shows that there is a clear correlation between the location of buildings, radiant heat, and rail temperature. We also confirmed that the proposed method can accurately reproduce the actual rail temperature distribution in nighttime.