Retrofitting of Existing Railway Tracks Using Micropiles as a Ground Improvement Technique: Finite-Element and Genetic Programming Approach

Created by W.Langdon from gp-bibliography.bib Revision:1.8414

@InProceedings{gupta:2024:ICTG,

• author = "Randhir Kumar Gupta and Sowmiya Chawla",
• title = "Retrofitting of Existing Railway Tracks Using Micropiles as a Ground Improvement Technique: Finite-Element and Genetic Programming Approach",
• booktitle = "Proceedings of the 5th International Conference on Transportation Geotechnics (ICTG) 2024, Volume 1",
• year = "2024",
• editor = "Cholachat Rujikiatkamjorn and Jianfeng Xue and Buddhima Indraratna",
• pages = "211--220",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• URL = "https://link.springer.com/chapter/10.1007/978-981-97-8213-0_23",
• DOI = "doi:10.1007/978-981-97-8213-0_23",
• abstract = "micropiles are proposed as an alternative tool to reinforce the existing railway subgrade without removing the existing track and without blocking existing traffic. suitability of micropiles as a ground improvement method for the existing railway track was assessed. Micropiles were modelled along the sides of the track in various orientations. A complete parametric study varying the geometrical parameters of the micropile under static and realistic moving train load conditions was performed using Finite Element Method (FEM) software. Three-dimensional numerical models with variations in length, diameter, inclination and spacing of micropiles was also performed. The results of FEM analyses were used as an input to the Genetic Programming (GP) model. The GP analysis output generates empirical equations for the prediction of track performance with micropile parameters as an input variable. The GP analysis resulted in empirical equations for the prediction of track performance, with the micropile parameters as input variables. The input variables were: length, diameter, spacing, and inclination of the micropile. These empirical equations can be used to predict the performance of the track for different reinforcement conditions. The empirical equations by GP have been used to develop a design methodology and a flowchart illustrating the overall design steps is generated. This design methodology can be adopted for practicing civil engineers to perform the upgradation of the existing tracks.",

}

Genetic Programming entries for Randhir Kumar Gupta Sowmiya Chawla

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