Validation of a rail temperature model with experimental measurements

Abstract

Rail temperature is a key factor when studying the effects of thermal buckling. Many models have been developed to simulate rail temperatures under various weather conditions. This work is based on the model developed by the Chungnam National University (CNU), which includes the shadow effect on the rail and the solar position to improve the temperature prediction during several periods of the day, validates it with experimental data, and compares it with a finite element model. Furthermore, a python library is developed based on the lumped thermal model with small adaptations, called railtemp. The python package has slightly better performance over the original CNU model, reaching a correlation factor R2 of 0.947 and a root mean square error of 2.6°C. Furthermore, a new proposal is presented to determine the temperatures on rail tracks based on air temperature.

Using Detailing Concept to Assess Railway Functional Safety

“…However, modern tools used to determine the state of an object are based on principles developed to determine the first limit state, which determines the general suitability of an object to work in certain conditions [58][59][60]. The strength [61][62][63] and stability [64][65][66][67] indicators used to evaluate this state are obtained by numerical modeling to simulate quasi-dynamic deformation processes [68][69][70][71] occurring inside the elements under the influence of external [72][73][74] and climatic impulses [75][76][77].…”