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Civil-Comp Conferences
ISSN 2753-3239 CCC: 10
PROCEEDINGS OF THE EIGHTEENTH INTERNATIONAL CONFERENCE ON CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING COMPUTING Edited by: P. Iványi, J. Kruis and B.H.V. Topping
Paper 2.6
A New Algorithm To Determine Critical Speeds on Ballasted High-Speed Railway Bridges G. Ferreira1, P.A. Montenegro1, A.A. Henriques2 and R. Calçada1
1CONSTRUCT-iRAIL, Faculty of Engineering, University of Porto, Portugal
Full Bibliographic Reference for this paper
G. Ferreira, P.A. Montenegro, A.A. Henriques, R. Calçada, "A New Algorithm To Determine Critical Speeds on Ballasted High-Speed Railway Bridges", in P. Iványi, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Eighteenth International Conference on
Civil, Structural and Environmental Engineering Computing", Civil-Comp Press, Edinburgh, UK,
Online volume: CCC 10, Paper 2.6, 2025,
Keywords: railway bridges, high-speed railways, subset simulation, ballasted track, Eurocodes, probabilistic analysis.
Abstract
Like all structures, it is impossible to characterize a bridge in a definitive manner. The intrinsic variability of materials, actions and building processes introduces mechanical and geometrical uncertainties. The study of structural safety, assessed through the relation between actions and bearing capacity, is as challenging as the variability of those parameters. One of the limits the Eurocodes impose on high-speed ballasted track railway bridges is verifying vertical deck acceleration. However, the apparently arbitrary origin of the normative limit has been discussed in recent years. To study this problem, it is necessary to address situations where the probabilities of failure are lower than 10e-4, which comes at a significant computational cost, especially considering multiple load models and possible critical speeds. A new algorithm is proposed based on subset simulation to find those speeds. An optimization study of the algorithm's parameters is presented. This process to determine critical speeds reduces the computational expense by three orders of magnitude that a more traditional Monte Carlo simulation would entail.
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