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<p>Vibrations in railway infrastructure constructed on soft soil require efficient strengthening techniques. This research examines the dynamic behavior of a geogrid-reinforced railway embankment supported by pile (GRSP) subjected to high-speed train loads with a validated 3D finite element model. The model includes a moving train load via a Hertzian contact model and is calibrated using field data from the Harbin-Dalian line. A full fractional factorial (FFF) L27 design of trials is used to investigate the effects of pile stiffness, diameter, and embankment height on vibration acceleration. The results show that embankment height has the greatest influence, with taller embankments reducing ground vibrations while increasing track-level accelerations due to the soil arching effect. A multiple-linear regression model is developed to forecast peak accelerations, which helps with the design of GRSP systems for optimal vibration control. The study sheds new light on the coupled dynamics of train-track-GRSP systems and offers practical design advice.</p>

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Key Factors Influencing the Dynamic Response of Pile Supported Railway Embankments under Train Loading

  • 期刊论文

  • 发表日期：

    2026年2月19日

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  • Ishola Valere Loic Chango,
  • Jun Chen

摘要

Vibrations in railway infrastructure constructed on soft soil require efficient strengthening techniques. This research examines the dynamic behavior of a geogrid-reinforced railway embankment supported by pile (GRSP) subjected to high-speed train loads with a validated 3D finite element model. The model includes a moving train load via a Hertzian contact model and is calibrated using field data from the Harbin-Dalian line. A full fractional factorial (FFF) L27 design of trials is used to investigate the effects of pile stiffness, diameter, and embankment height on vibration acceleration. The results show that embankment height has the greatest influence, with taller embankments reducing ground vibrations while increasing track-level accelerations due to the soil arching effect. A multiple-linear regression model is developed to forecast peak accelerations, which helps with the design of GRSP systems for optimal vibration control. The study sheds new light on the coupled dynamics of train-track-GRSP systems and offers practical design advice.