Stochastic Analysis on the Resonance of Railway Trains Moving over a Series of Simply Supported Bridges

Resonance problems encountered in vehicle-bridge interaction (VBI) have attracted widespread concern over the past decades. Due to system random characteristics, the prediction of resonant speeds and responses will become more complicated. To this end, this study presents stochastic analysis on the...

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Autores principales: Tao Zhang, Taimu Jin, Jun Luo, Shengyang Zhu, Kaiyun Wang
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Publicado: Hindawi Limited 2021
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Acceso en línea:https://doaj.org/article/50a039e41afc4ac5aeae9280c115c5c7
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spelling oai:doaj.org-article:50a039e41afc4ac5aeae9280c115c5c72021-11-22T01:11:25ZStochastic Analysis on the Resonance of Railway Trains Moving over a Series of Simply Supported Bridges1875-920310.1155/2021/1491207https://doaj.org/article/50a039e41afc4ac5aeae9280c115c5c72021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/1491207https://doaj.org/toc/1875-9203Resonance problems encountered in vehicle-bridge interaction (VBI) have attracted widespread concern over the past decades. Due to system random characteristics, the prediction of resonant speeds and responses will become more complicated. To this end, this study presents stochastic analysis on the resonance of railway trains moving over a series of simply supported bridges with consideration of the randomness of system parameters. A train-slab track-bridge (TSB) vertically coupled dynamics model is established following the basic principle of vehicle-track-coupled dynamics. The railway train is composed of multiple vehicles, and each of them is built by seven rigid parts assigned with a total of 10 degrees of freedom. The rail, track slab, and bridge are considered as Euler–Bernoulli beams, and the vibration equations of which are established by the modal superposition method (MSM). Except for the nonlinear wheel-rail interaction based on the Hertz contact theory, the other coupling relations between each subsystem are assumed to be linear elastic. The number theory method is employed to obtain the representative sample point sets of the random parameters, and the flow trajectories of probabilities for the TSB dynamics system are captured by a probability density evolution method (PDEM). Numerical results indicate that the maximum bridge and vehicle responses are mainly dominated by the primary train-induced resonant speed; the last vehicle of a train will be more seriously excited when the bridges are set in resonance by the train; the resonant speeds and responses are rather sensitive to the system randomness, and the possible maximum amplitudes predicted by the PDEM are significantly underestimated by the traditional deterministic method; optimized parameters of the TSB system are preliminary obtained based on the representative point sets and imposed screening conditions.Tao ZhangTaimu JinJun LuoShengyang ZhuKaiyun WangHindawi LimitedarticlePhysicsQC1-999ENShock and Vibration, Vol 2021 (2021)
institution DOAJ
collection DOAJ
language EN
topic Physics
QC1-999
spellingShingle Physics
QC1-999
Tao Zhang
Taimu Jin
Jun Luo
Shengyang Zhu
Kaiyun Wang
Stochastic Analysis on the Resonance of Railway Trains Moving over a Series of Simply Supported Bridges
description Resonance problems encountered in vehicle-bridge interaction (VBI) have attracted widespread concern over the past decades. Due to system random characteristics, the prediction of resonant speeds and responses will become more complicated. To this end, this study presents stochastic analysis on the resonance of railway trains moving over a series of simply supported bridges with consideration of the randomness of system parameters. A train-slab track-bridge (TSB) vertically coupled dynamics model is established following the basic principle of vehicle-track-coupled dynamics. The railway train is composed of multiple vehicles, and each of them is built by seven rigid parts assigned with a total of 10 degrees of freedom. The rail, track slab, and bridge are considered as Euler–Bernoulli beams, and the vibration equations of which are established by the modal superposition method (MSM). Except for the nonlinear wheel-rail interaction based on the Hertz contact theory, the other coupling relations between each subsystem are assumed to be linear elastic. The number theory method is employed to obtain the representative sample point sets of the random parameters, and the flow trajectories of probabilities for the TSB dynamics system are captured by a probability density evolution method (PDEM). Numerical results indicate that the maximum bridge and vehicle responses are mainly dominated by the primary train-induced resonant speed; the last vehicle of a train will be more seriously excited when the bridges are set in resonance by the train; the resonant speeds and responses are rather sensitive to the system randomness, and the possible maximum amplitudes predicted by the PDEM are significantly underestimated by the traditional deterministic method; optimized parameters of the TSB system are preliminary obtained based on the representative point sets and imposed screening conditions.
format article
author Tao Zhang
Taimu Jin
Jun Luo
Shengyang Zhu
Kaiyun Wang
author_facet Tao Zhang
Taimu Jin
Jun Luo
Shengyang Zhu
Kaiyun Wang
author_sort Tao Zhang
title Stochastic Analysis on the Resonance of Railway Trains Moving over a Series of Simply Supported Bridges
title_short Stochastic Analysis on the Resonance of Railway Trains Moving over a Series of Simply Supported Bridges
title_full Stochastic Analysis on the Resonance of Railway Trains Moving over a Series of Simply Supported Bridges
title_fullStr Stochastic Analysis on the Resonance of Railway Trains Moving over a Series of Simply Supported Bridges
title_full_unstemmed Stochastic Analysis on the Resonance of Railway Trains Moving over a Series of Simply Supported Bridges
title_sort stochastic analysis on the resonance of railway trains moving over a series of simply supported bridges
publisher Hindawi Limited
publishDate 2021
url https://doaj.org/article/50a039e41afc4ac5aeae9280c115c5c7
work_keys_str_mv AT taozhang stochasticanalysisontheresonanceofrailwaytrainsmovingoveraseriesofsimplysupportedbridges
AT taimujin stochasticanalysisontheresonanceofrailwaytrainsmovingoveraseriesofsimplysupportedbridges
AT junluo stochasticanalysisontheresonanceofrailwaytrainsmovingoveraseriesofsimplysupportedbridges
AT shengyangzhu stochasticanalysisontheresonanceofrailwaytrainsmovingoveraseriesofsimplysupportedbridges
AT kaiyunwang stochasticanalysisontheresonanceofrailwaytrainsmovingoveraseriesofsimplysupportedbridges
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