Application of seismic tomography for assessment of the railway substructure condition

Author:

Lazarević Luka1,Vučković Dejan2,Vilotijević Milica1,Popović Zdenka1

Affiliation:

1. Faculty of Civil Engineering, University of Belgrade, Belgrade, Serbia

2. Faculty of Mining and Geology, University of Belgrade, Belgrade, Serbia

Abstract

This article presents results obtained in the research conducted on railway infrastructure in Serbia, which aimed at prediction of substructure condition based on the analysis of track quality. It presents the results of seismic tomography application as non-destructive procedure for assessment of railway substructure condition. Track geometry quality was assessed according to analysis of longitudinal level data, which was recorded during regular track geometry inspections. Track section for application of seismic tomography was chosen on the basis of analysed track geometry data recorded during the regular track geometry inspections in 2006, 2008, 2009, 2012, 2013 and 2014. Tomographic imaging of railway platform on Test Section enabled the creation of two-dimensional finite element model, which was used for determination of propagation speed of seismic P-waves. Seismic tomography on Test Section, which is the part of the international railway line Belgrade–Vrbnica, was performed in 2014. Obtained tomographic image was discussed and compared to track geometry data recorded during the regular track geometry inspections.

Funder

Ministry of Education, Science and Technological Development of Republic of Serbia

Publisher

SAGE Publications

Subject

Mechanical Engineering,Biophysics

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3