Next Article in Journal
Direction of Arrival Estimation for MIMO Radar via Unitary Nuclear Norm Minimization
Previous Article in Journal
Improving Passive Time Reversal Underwater Acoustic Communications Using Subarray Processing
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(4), 936; doi:10.3390/s17040936

Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair

1
School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea
2
Fire Research Institute, Korea Institute of Civil Engineering and Building Technology, Hwaseong 18544, Korea
3
Department of Transportation and Logistics Engineering, Hanyang University ERICA Campus, Ansan 15588, Korea
4
Department of Mechanical and Aerospace Engineering, Trine University, Angola, IN 46703, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 21 February 2017 / Revised: 12 April 2017 / Accepted: 19 April 2017 / Published: 24 April 2017
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [3372 KB, uploaded 24 April 2017]   |  

Abstract

Railway bridges are exposed to repeated train loads, which may cause fatigue failure. As critical links in a transportation network, railway bridges are expected to survive for a target period of time, but sometimes they fail earlier than expected. To guarantee the target bridge life, bridge maintenance activities such as local inspection and repair should be undertaken properly. However, this is a challenging task because there are various sources of uncertainty associated with aging bridges, train loads, environmental conditions, and maintenance work. Therefore, to perform optimal risk-based maintenance of railway bridges, it is essential to estimate the probabilistic fatigue life of a railway bridge and update the life information based on the results of local inspections and repair. Recently, a system reliability approach was proposed to evaluate the fatigue failure risk of structural systems and update the prior risk information in various inspection scenarios. However, this approach can handle only a constant-amplitude load and has limitations in considering a cyclic load with varying amplitude levels, which is the major loading pattern generated by train traffic. In addition, it is not feasible to update the prior risk information after bridges are repaired. In this research, the system reliability approach is further developed so that it can handle a varying-amplitude load and update the system-level risk of fatigue failure for railway bridges after inspection and repair. The proposed method is applied to a numerical example of an in-service railway bridge, and the effects of inspection and repair on the probabilistic fatigue life are discussed. View Full-Text
Keywords: railway bridge; fatigue life updating; inspection and repair; system reliability railway bridge; fatigue life updating; inspection and repair; system reliability
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Lee, Y.-J.; Kim, R.E.; Suh, W.; Park, K. Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair. Sensors 2017, 17, 936.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top