Analysis of the influence of train load characteristics on the water damage of slab tracks

High-speed train load is one of the main factors that causes the failure of a slab track and is also the direct cause for producing water pressure in the cracks. Hence, choosing the right loading method is the key to analyze the water damage of slab tracks. In order to identify the distribution characteristics of the vertical force acting on the slab track, the analytic expression of fastener load was derived, and the field test was conducted to verify the theoretical model. According to the distribution characteristics of fastener load and the area of crack filled with water, the loading method was presented to analyze the water damage of slab tracks, and the influence of loading characteristics on the hydrodynamic pressure and crack propagation was analyzed. The results show that the distribution of fastener load in the main affected zone approximately accords with the Gaussian distribution under the single wheel load. When under the action of double wheels, the superimposed effect makes the second derivative of the loading function to increase by 99.93%. The superimposed effect of three or more wheels is less than 1% and can be ignored. Considering that the hydrodynamic pressure is highly sensitive to the second derivative of loading function, the load applied on the track slab should be in the form of a bogie, and different loads should be applied step by step based on the time series. The distribution of hydrodynamic pressure along the crack is approximately equal to the cubic polynomial, and the pressure peak appears at the crack tip. Also, the pressure is proportional to the square of the running speed of the train. In the region with abundant rainwater and a poor drainage system, reducing the train speed and taking timely measures such as grouting can effectively reduce the water damage of slab tracks.

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  • English

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  • Accession Number: 01678494
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jul 30 2018 11:12AM