Railroad Track Geometric Degradation Analysis: A BNSF Case Study
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 146, Issue 2
Abstract
Planning and optimizing maintenance actions for rail failures are possible through understanding rail behaviors, which can be captured by statistical models. In this study, a degradation analysis of railroad tracks is presented for three types of geometry failure modes. Using Burlington Northern Santa Fe (BNSF) data set, effective degradation stress factors are identified and inspection intervals are studied to attenuate the effect of hidden maintenance actions. Parameters of a general log linear Weibull model have been determined to estimate the failure probability at different stresses. To check the prediction performance, the models were applied on an independent test set, and the corresponding area under curve (AUC) were reported. Finally, a comprehensive sensitivity analysis was implemented to check the effect of different stress factors on residual life of a defected rail. This type of analysis is crucial in alerting railroad companies to fix a defect and to schedule preventive maintenance actions to reduce the probability of a track failure.
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Data Availability Statement
All data, models, or code generated or used during the study are available from the corresponding author by request.
Acknowledgments
The authors thank the Center for Advances in Port Management (CAPM) at Lamar University that financially supported this research. The authors also deeply appreciate Dr. Ramin Moghaddass from the University of Miami who provided insight and expertise that greatly assisted the research.
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Information & Authors
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 146 • Issue 2 • February 2020
Copyright
©2019 American Society of Civil Engineers.
History
Received: Feb 23, 2019
Accepted: Jul 3, 2019
Published online: Dec 6, 2019
Published in print: Feb 1, 2020
Discussion open until: May 6, 2020
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