Robust assessment of railway vehicle safety risks in operation using a proposed data-driven wheel profile generation approach: Design of computer experiments and surrogate models
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1-s2.0-S095183202400293X-main.pdf
Description
Published version
Size
8.03 MB
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Adobe PDF
Checksum (MD5)
830af601f5d8c44b3ff8388a9b9b741a
Author(s)
Braga, Joaquim A.P.
Costa, João N.
Ambrósio, Jorge
Frey, Daniel
Andrade, António R.
Date Issued
September 2024
Journal
Reliability Engineering & System Safety
Publisher
Elsevier BV
Citation
Braga, Joaquim A.P., Costa, João N., Ambrósio, Jorge, Frey, Daniel and Andrade, António R. 2024. "Robust assessment of railway vehicle safety risks in operation using a proposed data-driven wheel profile generation approach: Design of computer experiments and surrogate models." Reliability Engineering & System Safety, 249.
Version
Final published version
Abstract
Worldwide objectives for railway vehicles are increased capacity, faster travels and higher levels of safety. In the vehicle-track complex system, assessing and controlling the interactions between the wheels and the rail track is crucial to these goals. Wheel profiles are specifically designed to steer the vehicle and avoid derailment. Maintenance standards and train operating companies establish safe envelopes for wheel profile geometric parameters. A design of experiments is conducted to model relationships between allowable wheel parameters and expected vehicle safety risks, which is supported by condition monitoring data from operation. Such a robust assessment is missing in the literature. The applied methods consist of: (i) selection of predictors and pre-processing, based on literature, standards and a purely data-driven approach to generate wheel profiles; (ii) space-filling design, using Latin hypercube sampling; (iii) obtaining vehicle responses and post-processing, using a multibody dynamics commercial software and according to standards; (iv) surrogate modelling, using Gaussian processes and linear models; (v) sensitivity analysis, through Sobol indices; (vi) safety assessment, analysing response surfaces. Wheels with large flange height and thickness result in higher flange climb derailment risks. The proposed approach allows quantifying this risk as a function of profile parameters and mitigate it through maintenance actions.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.ress.2024.110220
