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Civil-Comp Conferences
ISSN 2753-3239 CCC: 7
PROCEEDINGS OF THE SIXTH INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo
Paper 3.7
Numerical Modelling of Partially Loaded Freight Train Entering a Tunnel Z. Liu and D. Soper
School of Civil Engineering, University of Birmingham, United Kingdom Z. Liu, D. Soper, "Numerical Modelling of Partially Loaded Freight Train Entering a Tunnel", in J. Pombo, (Editor), "Proceedings of the Sixth International Conference on
Railway Technology: Research, Development and Maintenance",
Civil-Comp Press, Edinburgh, UK,
Online volume: CCC 7, Paper 3.7, 2024, doi:10.4203/ccc.7.3.7
Keywords: freight train, computational fluid dynamics, one-dimensional numerical method, train/tunnel aerodynamics, large eddy simulation, vehicle aerodynamics.
Abstract
The large gaps between wagons and loaded goods, influence the pressure wave pattern generated by it passing through a tunnel. The accurate resolution of separation regions at the head of the blunted containers, and at unloaded gap sections is essential for precise predictions of pressure magnitude. Achieving this accuracy demands exceptional mesh quality, significant computational resources, and the careful selection of numerical models. This paper evaluates various numerical models to capture these complexities in separation regions. A 1d programme is developed to calculate the pressure wave generated by freight loco entering a tunnel, and is further extended to consider the discontinuities of the train body by implementing new mesh system and boundary conditions into the 1d programme. The results obtained from the 1d programme are validated against large eddy simulation data. A parameterisation study for different loading configurations improves program adaptability, and the relationship between predetermined parameters and gap length is investigated. This research bridges the gap in freight train tunnel aerodynamics, offering a versatile 1d computational tool for accurate pressure wave prediction.
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