Choi، نويسنده , , Jungyoul، نويسنده ,
In the track design and behavior prediction, the variable contribution of wheel load was evaluated by considering the design load for the tracks. Further, the track impact factor was used to calculate the dynamic wheel load as a single value, which was chosen according to the rail type (i.e., continuous welded rail or joint rail) and the design speed but did not take into consideration the track conditions (i.e., the ballast condition good or bad), train type (i.e., tilting train and EMU), and track components (i.e., sleeper type and fastening type). In this study, the measured track impact factor was applied to the time history function of the FE analysis in order to predict the displacement of ballasted tracks under real conditions, which included curved and the deteriorated tracks, thus increasing the train speed by approximately 20–30% of the existing train speed. Therefore, the dynamic wheel load and the rail and sleeper displacement were measured for two different trains running on four conventional curved track sections with two different sleeper types. The track impact factor was estimated from the measured dynamic wheel load, and the empirical dynamic wheel load was calculated using the measured track impact factor at each site. The measured track impact factors were used for simulating the dynamic wheel loads applied on the derived time history function for fast trains. A finite element analysis model using the derived time history function based on the empirical dynamic wheel load was used to predict the train-induced track displacement. The numerical simulations and field test results were compared with German and Japanese regulations for train-induced track displacement, and the speedup effect of a tilting train was compared with that of a general train (EMU).
pirical track impact factors were 17–18% higher in the R400 sections than in the R600 sections. As the track curvature decreased, the impact on the track increased. Therefore, the empirical track impact factors were 21–23% higher in the WT sections than in the PCT sections. At 70 km/h, the impact on the track from a tilting train was 7–11% less than that from EMU. Although the tilting train sped up by 30% (90 km/h), its response level was similar to or less than that of the EMU. The analytical results reproduced the experimental results well within about 2–5% difference in the values. Therefore, the derived time history function based on the measured track impact factors is considered to provide sufficiently reliable FEA results in the investigation of the behavior of ballasted tracks. The difference between the maximum displacements for both train types on all the sections was about 15–20%.
alytical results show that the speed limits of the tilting train were higher than those of the EMU by approximately 8–23 km/h at each test site. Therefore, the speed limit of each test site was estimated by considering the limit of sleeper displacement. It was shown that the time history function derived using the measured track impact factor on a small track curvature with wooden sleepers was higher than that in other test sections. Therefore, it would be advantageous to increase the weight of sleepers on existing lines to increase the train speed through the speedup effect without increasing the track curvature. The increase in the speed of a tilting train with a small track curvature was much better than that by a track curvature increased by approximately 10%.
Speedup effect , Tilting train , Track impact factor , Track component , Empirical dynamic wheel load