Machine learning approach to railway ballast degradation prognosis considering crumb rubber modification and parent rock strength

Parent rock strength and crumb rubber modification are two critical mechanical parameters that significantly decide the ballast layer degradation subjected to train dynamic loading. Using machine learning to predict ballast degradation considering these two parameters is helpful for deciding ballasted track maintenance cycle. In the current...

Numerical analysis of train-track-subgrade dynamic performance with crumb rubber in ballast layer

Crumb rubber (CR) has been proposed to apply in the ballast or sub-ballast layer for ballast degradation mitigation and vibration (noise) reduction. The CR can change the ballast layer stiffness, which can affect the train-track-subgrade dynamic performance and cause travel comfort and safety issues. Towards this, this study aims at...

Effects of crumb rubber size and percentage on degradation reduction of railway ballast

Higher speed, more freight and frequent maintenance increase ballast degradation and reduce the ballast lifespan. To reduce ballast degradation, crumb rubber used as buffering aggregates in ballast bed is relatively unexplored and needs more studies, because using it has the advantage of reusing the waster rubber and absorbing the noises. The...