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X. Zhu, J. Xu, P. Wang, "A Stochastic Dynamics–Based Approach for Rapid Prediction of the Bending Fatigue Life of Mixed Passenger–Freight Railway Frogs", in J. Pombo, (Editor), "Proceedings of the Seventh International Conference on Railway Technology: Research, Development and Maintenance ", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 15, Paper 6.3, 2026, doi:10.4203/ccc.15.6.3

Keywords: mixed passenger and freight railway, movable-point frog, vehicle-turnout coupled rigid and flexible model, rail bottom, bending fatigue, probability fatigue life.

Abstract

The concurrent operation of high-speed and heavy-haul services on mixed-traffic railways imposes heightened demands on track structures, particularly the movable point rail of the frog. The complex geometry of the point rail, in conjunction with the significant wheel load transfer, renders the point rail bottom susceptible to fatigue damage under cyclic loading. The present paper integrates a structural finite element turnout model into a multibody system dynamics framework and develops dedicated post-processing procedures for the rapid extraction of stresses in variable-section rails. The investigation builds upon this foundation, systematically examining the spatial distribution characteristics of point rail bottom fatigue life. This is achieved by accounting for the operational patterns of mixed passenger and freight railway, the unique structure of the frog, and the random nature of alternating loads. The research reveals the spatial non-uniformity and probabilistic sensitivity of point rail fatigue, providing innovative engineering methodologies and theoretical foundations for turnout life assessment and high-reliability operations.

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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: 15 PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo Paper 6.3 A Stochastic Dynamics–Based Approach for Rapid Prediction of the Bending Fatigue Life of Mixed Passenger–Freight Railway Frogs X. Zhu, J. Xu and P. Wang MOE Key Laboratory of High-speed Railway Engineering, Southwest Jiaotong University, Chengdu, China doi:10.4203/ccc.15.6.3 Full Bibliographic Reference for this paper X. Zhu, J. Xu, P. Wang, "A Stochastic Dynamics–Based Approach for Rapid Prediction of the Bending Fatigue Life of Mixed Passenger–Freight Railway Frogs", in J. Pombo, (Editor), "Proceedings of the Seventh International Conference on Railway Technology: Research, Development and Maintenance ", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 15, Paper 6.3, 2026, doi:10.4203/ccc.15.6.3 Keywords: mixed passenger and freight railway, movable-point frog, vehicle-turnout coupled rigid and flexible model, rail bottom, bending fatigue, probability fatigue life. Abstract The concurrent operation of high-speed and heavy-haul services on mixed-traffic railways imposes heightened demands on track structures, particularly the movable point rail of the frog. The complex geometry of the point rail, in conjunction with the significant wheel load transfer, renders the point rail bottom susceptible to fatigue damage under cyclic loading. The present paper integrates a structural finite element turnout model into a multibody system dynamics framework and develops dedicated post-processing procedures for the rapid extraction of stresses in variable-section rails. The investigation builds upon this foundation, systematically examining the spatial distribution characteristics of point rail bottom fatigue life. This is achieved by accounting for the operational patterns of mixed passenger and freight railway, the unique structure of the frog, and the random nature of alternating loads. The research reveals the spatial non-uniformity and probabilistic sensitivity of point rail fatigue, providing innovative engineering methodologies and theoretical foundations for turnout life assessment and high-reliability operations. download the full-text of this paper (PDF, 13 pages, 1422 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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