重载铁路道岔区动力学特性与滚动接触疲劳损伤研究

刘洋, 王泓豪, 林强, 丁昊昊, 王梁, 张群莉, 姚建华, 王文健

表面技术 ›› 2026, Vol. 55 ›› Issue (13) : 287-299.

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表面技术 ›› 2026, Vol. 55 ›› Issue (13) : 287-299. DOI: 10.16490/j.cnki.issn.1001-3660.2026.13.025
摩擦磨损与润滑

重载铁路道岔区动力学特性与滚动接触疲劳损伤研究

  • 刘洋1, 王泓豪1, 林强1, 丁昊昊1, 王梁2, 张群莉2, 姚建华2, 王文健1,*
作者信息 +

Dynamic Behavior and Rolling Contact Fatigue Damage of Turnouts in Heavy-haul Railways

  • LIU Yang1, WANG Honghao1, LIN Qiang1, DING Haohao1, WANG Liang2, ZHANG Qunli2, YAO Jianhua2, WANG Wenjian1,*
Author information +
文章历史 +

摘要

目的 研究重载铁路道岔区侧向通过时的极端动力学特性,精准定位易发生滚动接触疲劳(RCF)的区域,并量化心轨垂直磨耗对疲劳损伤演化的影响。方法 结合线性变截面拟合技术与Kik-Piotrowski多点接触算法,建立了高精度的重载车辆-道岔多体动力学模型。通过基准工况与极限工况(30 t轴重、50 km/h)下的多参数对比,严格验证了模型的通用性与可靠性。选取60 kg/m钢轨12号单开道岔,系统分析了不同速度、轴重对轮轨作用力的响应规律,基于材料安定图与表面疲劳指数定性评估了道岔滚动接触疲劳易发生区域,并引入3~6 mm的渐进式心轨垂直磨耗以探究其损伤加速效应。结果 重载货车侧逆向过岔时,垂向力随速度和轴重的增加而显著增大;横向力在尖轨上随参数增加而增大,但在心轨上受复杂接触游移影响而在20 kN左右低幅波动。RCF高危区域精确定位于距尖轨尖端1.24 m处及理论心轨尖端后方262 mm处。受非对称轮载转移与接触斑形态非线性重构的影响,心轨疲劳指数峰值并未随速度和轴重呈现单调变化趋势。此外,心轨垂磨深度的增加迫使疲劳指数最大值所在位置后移,且损伤程度显著高于无磨耗状态。结论 重载侧向过岔时,RCF极易在心轨变截面区萌生。心轨塑性压溃导致的垂直磨耗是加速疲劳失效的关键驱动因素,深度磨耗会显著提升严重疲劳损伤的风险。在实际重载运营中,除了控制轴重与限速等机械边界外,还需警惕热-机及环境介质等多因素耦合对疲劳演化的成倍放大效应,及时对心轨进行视情打磨与维护。

Abstract

Heavy-haul railways play a pivotal role in the modern freight transportation, yet the turnout zones remain the most vulnerable bottlenecks within the track network. The inherent structural discontinuities, particularly the variable cross-sections of the switch and nose rails, lead to severe dynamic wheel-rail interactions. This problem is drastically amplified during diverging route negotiations, where vehicles experience abrupt centrifugal forces, intense asymmetric load transfers, and high-frequency multi-point contacts. While extensive research has focused on rolling contact fatigue (RCF) during straight-line passages, a comprehensive system-level investigation into the dynamic behavior and RCF damage mechanisms of heavy-haul trains negotiating turnouts in the diverging reverse direction remains noticeably absent.
To bridge this critical research gap, this study establishes a high-fidelity, multi-body dynamic simulation model coupling a heavy-haul freight wagon with a complete turnout structure. The vehicle model integrates detailed structural parameters, including a K6 bogie and LM wheel tread profiles, while the track model represents a standard 60 kg/m rail, No. 12 single turnout. To accurately capture the complex spatial geometry of the turnout, a linear variable cross-section fitting technique is employed. The dynamic wheel-rail interaction is resolved using the Kik-Piotrowski multi-point contact algorithm, which balances computational efficiency with the precise capturing of non-Hertzian contact characteristics. The robustness and predictive accuracy of the model are systematically verified against established field trial data and standard engineering thresholds, including derailment coefficients and wheel load reduction rates, under both baseline (25 t axle load, 45 km/h) and extreme limit operational conditions (30 t axle load, 50 km/h).
Utilizing this validated framework, extensive parametric analyses are conducted to evaluate the influence of varying operating speeds (40, 45, and 50 km/h) and axle loads (23, 25, and 30 t) on the wheel-rail interaction forces. The computational results demonstrate that vertical wheel-rail forces exhibit a consistent and significant upward trend in response to increases in both speed and axle load. Conversely, the lateral forces present a distinct spatial sensitivity: while lateral forces on the switch rail increase monotonically with operational parameters, reaching a peak of 90 kN, the lateral forces on the nose rail fluctuate at a lower, relatively stable amplitude of approximately 20 kN, governed primarily by the complex contact wandering rather than load increments.
Furthermore, the dynamic loads are mapped onto a material shakedown diagram to calculate the surface fatigue index, enabling the precise spatial localization of RCF hotspots. The analysis reveals that the regions are most susceptible to severe RCF, where the material enters the ratcheting effect zone with irreversible plastic accumulation, are located at 1.24 meters from the tip of the switch rail and 262 mm from the theoretical tip of the nose rail. Interestingly, due to the non-linear reconfiguration of contact patch morphology and multi-point creepages during asymmetric load transfer, the peak surface fatigue index on the nose rail does not exhibit a simple monotonic relationship with increasing speed or axle load.
Recognizing the detrimental impact of structural degradation caused by plastic crushing, the study further quantifies the accelerating effect of progressive vertical wear (ranging from 3 mm to 6 mm) on the nose rail. The findings indicate that deeper vertical wear profiles significantly elevate the maximum fatigue index and force the damage hotspot to shift further away from the theoretical tip, drastically exacerbating the risk of severe shelling and fatigue fracture compared with an unworn state.
In conclusion, this research confirms that the variable cross-sections within the turnout, particularly the nose rail under progressive vertical wear, serve as the primary drivers of RCF failure in heavy-haul diverging passages. The findings underscore the critical necessity for timely, condition-based grinding and maintenance of the nose rail. Moreover, the study highlights that future RCF management must transcend pure mechanical boundaries, maintaining vigilance against the exponential damage amplification triggered by multi-factor coupling, such as thermal-mechanical softening and environmental fluid pressurization in actual heavy-haul operations.

关键词

普速道岔 / 动力学模型 / 钢轨滚动接触疲劳 / 疲劳指数

Key words

conventional speed turnout / dynamic model / rail rolling contact fatigue / fatigue index

引用本文

导出引用
刘洋, 王泓豪, 林强, 丁昊昊, 王梁, 张群莉, 姚建华, 王文健. 重载铁路道岔区动力学特性与滚动接触疲劳损伤研究[J]. 表面技术. 2026, 55(13): 287-299
LIU Yang, WANG Honghao, LIN Qiang, DING Haohao, WANG Liang, ZHANG Qunli, YAO Jianhua, WANG Wenjian. Dynamic Behavior and Rolling Contact Fatigue Damage of Turnouts in Heavy-haul Railways[J]. Surface Technology. 2026, 55(13): 287-299
中图分类号: TH117.1   

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基金

国家重点研发计划课题(2023YFB4603400); 国家自然科学基金(52575234); 中央高校基本科研业务费专项资金(2682024CG007)

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