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Empirical Model of Ground-Borne Vibration Induced by Freight Railway Traffic

Mohd Khairul Afzan Mohd Lazi, Muhammad Akram Adnan and Norliana Sulaiman

Pertanika Journal of Social Science and Humanities, Volume 29, Issue 3, July 2021

DOI: https://doi.org/10.47836/pjst.29.3.21

Keywords: Empirical model, freight train, ground-borne vibration, peak particle velocity

Published on: 31 July 2021

Developing an empirical model that can predict ground-borne vibration is required in the modelling process using actual data of ground vibration velocity induced by train traffic collected from sites. In the preliminary and mitigation planning stages of the project, the empirical models developed are expected to predict the ground-borne vibration velocity due to rail traffic. The findings of this research are expected to provide a new perspective for railway planners and designers to improve the national design to improve the quality of life for the residents living close to the rail tracks. This research study firmly fills the information gap towards a fundamental understanding of ground-borne vibration in numerous areas of learning regarding the condition of train operation. This study has developed a prediction model of regression to forecast the peak particle velocity of ground-borne vibration from freight trains based on correlated and fixed parameters. The models developed have considered a few parameters obtained from sites using minimal or without tools altogether. Speed of trains and distance of receivers from the sources were the only significant parameters found in this study and used to simplify the empirical model. Type of soil, which is soft soil, and type of train, which is freight train, were the fixed parameters for this study. The data collected were measured along the ground rail tracks involving human-operated freight trains. Residents from the landed residential areas near the railway tracks were chosen as the receivers. Finally, the peak particle velocity models have been successfully developed, and validation analysis was conducted. The model can be used by authorities in the upcoming plan for the new rail routes based on similar fixed parameters with correlated parameters from the study.

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ISSN 0128-7702

e-ISSN 2231-8534

Article ID

JST-2382-2020

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