Train Moving Load-Induced Vertical Superimposed Stress at Ballasted Railway Tracks
Ballasted railway track is an important factor that forms railway transportation over the world, which may face severe damage during operation due to the deterioration of the track ballast geometry. A practical method of evaluating train moving load-induced vertical superimposed stress in substructu...
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2020-01-01
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Series: | Advances in Civil Engineering |
Online Access: | http://dx.doi.org/10.1155/2020/3428395 |
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doaj-74a93a6afb904c8aa9386ebfc1cf14e02020-11-25T01:27:38ZengHindawi LimitedAdvances in Civil Engineering1687-80861687-80942020-01-01202010.1155/2020/34283953428395Train Moving Load-Induced Vertical Superimposed Stress at Ballasted Railway TracksHeng Wang0Ling-Ling Zeng1Xia Bian2Zhen-Shun Hong3School of Civil Engineering, Fujian University of Technology, Fuzhou 350108, ChinaCollege of Civil Engineering and Architecture, Zhejiang University of Technology, Hanzhou 310014, ChinaKey Laboratory of Ministry of Education for Geomechanics and Embankment Engineering, Hohai University, Nanjing 210098, ChinaInstitute of Geotechnical Engineering, School of Transportation, Southeast University, Nanjing 210096, ChinaBallasted railway track is an important factor that forms railway transportation over the world, which may face severe damage during operation due to the deterioration of the track ballast geometry. A practical method of evaluating train moving load-induced vertical superimposed stress in substructure by incorporating the effects of ballast characteristics and multilayered substructure is presented. The proposed method is validated by comparing with the field measurements compiled from the literature with the calculated value. It is found that the prediction accuracy of the proposed method is within ±10%, in comparison with field measurements. Meanwhile, it should be emphasized that the predicted value by traditional methods was 1.4–5.0 times field measurements. Also, key factors affecting the predicted accuracy are identified through parameter analysis by using the proposed and the traditional methods.http://dx.doi.org/10.1155/2020/3428395 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Heng Wang Ling-Ling Zeng Xia Bian Zhen-Shun Hong |
spellingShingle |
Heng Wang Ling-Ling Zeng Xia Bian Zhen-Shun Hong Train Moving Load-Induced Vertical Superimposed Stress at Ballasted Railway Tracks Advances in Civil Engineering |
author_facet |
Heng Wang Ling-Ling Zeng Xia Bian Zhen-Shun Hong |
author_sort |
Heng Wang |
title |
Train Moving Load-Induced Vertical Superimposed Stress at Ballasted Railway Tracks |
title_short |
Train Moving Load-Induced Vertical Superimposed Stress at Ballasted Railway Tracks |
title_full |
Train Moving Load-Induced Vertical Superimposed Stress at Ballasted Railway Tracks |
title_fullStr |
Train Moving Load-Induced Vertical Superimposed Stress at Ballasted Railway Tracks |
title_full_unstemmed |
Train Moving Load-Induced Vertical Superimposed Stress at Ballasted Railway Tracks |
title_sort |
train moving load-induced vertical superimposed stress at ballasted railway tracks |
publisher |
Hindawi Limited |
series |
Advances in Civil Engineering |
issn |
1687-8086 1687-8094 |
publishDate |
2020-01-01 |
description |
Ballasted railway track is an important factor that forms railway transportation over the world, which may face severe damage during operation due to the deterioration of the track ballast geometry. A practical method of evaluating train moving load-induced vertical superimposed stress in substructure by incorporating the effects of ballast characteristics and multilayered substructure is presented. The proposed method is validated by comparing with the field measurements compiled from the literature with the calculated value. It is found that the prediction accuracy of the proposed method is within ±10%, in comparison with field measurements. Meanwhile, it should be emphasized that the predicted value by traditional methods was 1.4–5.0 times field measurements. Also, key factors affecting the predicted accuracy are identified through parameter analysis by using the proposed and the traditional methods. |
url |
http://dx.doi.org/10.1155/2020/3428395 |
work_keys_str_mv |
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1715764928510427136 |