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A.A. Meghoe, R. Loendersloot, T. Tinga, "Uncertainty propagation in rail wear prediction using an analytical method and field observations", in J. Pombo, (Editor), "Proceedings of the Fifth International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 1, Paper 10.9, 2022, doi:10.4203/ccc.1.10.9

Keywords: rail, wear, maintenance, prediction, modelling.

Abstract

Rail wear management based on accurate rail wear prediction is essential for railway maintenance. The implementation of rail wear prediction models in maintenance decision tools is not yet available due to detailed modelling and the absence of direct coupling with operational conditions. A method that does not provide any confidence interval on the prediction is not very helpful if one wants to use the results of the prediction for maintenance decision-making and there is variation in the input. Therefore, in this study a wear prediction model that does take into account these limitations is used to predict the amount of rail wear with certain confidence bounds. The uncertainty in the output of the model is quantified. This is realized by considering probability distribution functions for the input parameters and analytical analyses. The results obtained from these analyses are then compared with field measurements and a good agreement is found.

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Front Page Browse CCC CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Conferences ISSN 2753-3239 CCC: 1 PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo Paper 10.9 Uncertainty propagation in rail wear prediction using an analytical method and field observations A.A. Meghoe, R. Loendersloot and T. Tinga Dynamics Based Maintenance, University of Twente, Enschede, The Netherlands doi:10.4203/ccc.1.10.9 Full Bibliographic Reference for this paper A.A. Meghoe, R. Loendersloot, T. Tinga, "Uncertainty propagation in rail wear prediction using an analytical method and field observations", in J. Pombo, (Editor), "Proceedings of the Fifth International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 1, Paper 10.9, 2022, doi:10.4203/ccc.1.10.9 Keywords: rail, wear, maintenance, prediction, modelling. Abstract Rail wear management based on accurate rail wear prediction is essential for railway maintenance. The implementation of rail wear prediction models in maintenance decision tools is not yet available due to detailed modelling and the absence of direct coupling with operational conditions. A method that does not provide any confidence interval on the prediction is not very helpful if one wants to use the results of the prediction for maintenance decision-making and there is variation in the input. Therefore, in this study a wear prediction model that does take into account these limitations is used to predict the amount of rail wear with certain confidence bounds. The uncertainty in the output of the model is quantified. This is realized by considering probability distribution functions for the input parameters and analytical analyses. The results obtained from these analyses are then compared with field measurements and a good agreement is found. download the full-text of this paper (PDF, 6 pages, 441 Kb) go to the previous paper go to the next paper return to the table of contents return to the volume description
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