Fatigue is a primary concern for railroad bridge owners because railroad bridges typically have high live load to dead load ratios and high stress cycle frequencies. However, existing inspection and post-inspection analysis methods are unable to accurately consider the full influence of bridge behavior on the fatigue life of bridge components. Reliability-based fatigue analysis methods have emerged to account for uncertainties in analysis parameters such as environmental and mechanical properties. While existing literature proposes probabilistic fatigue assessment of bridge components, this body of work relies on train parameter estimates, finite element model simulations, or controlled loading tests to augment monitoring data. This article presents a probabilistic fatigue assessment of monitored railroad bridge components using only continuous, long-term response data in a purely data-driven reliability framework that is compatible with existing inspection methods. As an illustrative example, this work quantifies the safety profile of a fracture-critical assembly comprising of six parallel eyebars on the Harahan Bridge (Memphis, TN). The monitored eyebars are susceptible to accelerated fatigue damage because changes in the boundary conditions cause some eyebars to carry a greater proportion of the total assembly load than assumed during design and analysis; existing manual inspection practices aim to maintain an equal loading distribution across the eyebars. Consequently, the limit state function derived in this article accounts for the coupled behavior between fatigue and relative tautness of the parallel eyebars. The reliability index values for both the element (i.e. individual eyebars) and system (i.e. full eyebar assembly) reliability problems are assessed and indicate that under the conservative assumption that progressive failure is brittle, first failure within the parallel eyebar system is generally equivalent to system failure. The proposed method also serves as an intervention strategy that can quantify the influence of eyebar realignment on the future evolution of the reliability index.

中文翻译：

---

使用可靠性框架中的长期响应数据对受监控的铁路桥梁部件进行概率疲劳评估

疲劳是铁路桥梁所有者的主要关注点，因为铁路桥梁通常具有高活荷载与静荷载比和高应力循环频率。然而，现有的检查和检查后分析方法无法准确考虑桥梁行为对桥梁构件疲劳寿命的全部影响。已经出现了基于可靠性的疲劳分析方法，以解决环境和机械特性等分析参数的不确定性。虽然现有文献提出了桥梁部件的概率疲劳评估，但这项工作依赖于列车参数估计、有限元模型模拟或受控加载测试来增加监测数据。本文介绍了仅使用连续、在与现有检查方法兼容的纯数据驱动的可靠性框架中提供长期响应数据。作为说明性示例，这项工作量化了 Harahan 大桥（田纳西州孟菲斯）上由六个平行眼杆组成的断裂临界组件的安全性。受监控的眼条容易受到加速疲劳损坏，因为边界条件的变化导致一些眼条承载的总装配载荷比例大于设计和分析期间的假设；现有的手动检查实践旨在保持眼杆上的负载分布均匀。因此，本文中推导出的极限状态函数解释了平行眼条的疲劳和相对绷紧之间的耦合行为。两个元素的可靠性指标值（即 单个眼条）和系统（即完整的眼条组件）可靠性问题进行评估，并表明在渐进式故障是脆弱的保守假设下，平行眼条系统内的首次故障通常等同于系统故障。所提出的方法还可以作为一种干预策略，可以量化眼球重新对齐对可靠性指标未来演变的影响。