This paper presents a progressive numerical model validation of a bowstring-arch railway bridge based on the analysis of experimental data from different structural response measurements, namely, static deformations under environmental actions, modal vibrations, and transient dynamic responses under traffic loads. This work also addresses an integrated approach that uses structural health monitoring (SHM) measurements in combination with FE modelling to understand the structural behaviour of a long-span complex bridge. A progressively phased in situ SHM system has provided a diverse set of data streams ranging from static and dynamic responses to the measurement of environmental and operational traffic loads. The first phase consists of defining a detailed baseline finite-element (FE) model of the bridge, envisaging the initial condition of the structure immediately after construction, and its validation using modal parameters (natural frequencies and mode shapes) derived from an ambient vibration test. Since overall in-service deflections in general do not exercise the non-linear regime of the bridge response, the second phase focuses on the analysis of static response data and temperature measurements to validate the non-linear behaviour of the structural system, particularly at the bearing devices, under slow actions. The third and final phase addresses the dynamic analysis under traffic actions, which provides greater sensitivity in the detection of non-linear behaviour due to the effects of high-amplitude actions induced by regular train loading profiles. To guarantee the accuracy of the baseline numerical model, particularly under temperature and traffic actions, it was necessary to use contact restrictions in some specific bearing devices. This improvement is in line with the structural changes detected in some bearing devices through visual inspections. As a result, an updated numerical model capable of reproducing the modal, static, and dynamic structural responses was achieved, showing a very good agreement between experimental and numerical data. In future applications, this updated numerical model will be useful for assessing the condition of the bridge under traffic loads, namely to identify damages and support the adoption of life cycle maintenance strategies based on the integration of SHM systems with (stochastic) load and failure models.

本文基于对不同结构响应测量的实验数据的分析，提出了弓弦拱形铁路桥梁的渐进式数值模型验证，这些结构响应测量是环境作用下的静态变形，模态振动以及交通荷载下的瞬态动力响应。这项工作还解决了一种综合方法，该方法结合使用结构健康监测（SHM）测量和有限元建模来了解大跨度复杂桥梁的结构行为。逐步分阶段的原位SHM系统提供了各种数据流，范围从静态和动态响应到环境和运营交通负载的测量。第一阶段包括定义桥梁的详细基线有限元（FE）模型，设想构筑物后立即确定结构的初始状态，并使用从环境振动测试中得出的模态参数（固有频率和模态形状）进行验证。由于总体在役挠度通常不会影响桥梁响应的非线性状态，因此第二阶段着重分析静态响应数据和温度测量值，以验证结构系统的非线性行为，尤其是在动作缓慢的轴承装置。第三阶段也是最后一个阶段，涉及交通行为下的动态分析，由于规则的火车载客量曲线引起的高振幅行为的影响，在非线性行为的检测中提供了更高的灵敏度。为了保证基线数值模型的准确性，特别是在温度和交通状况下，必须在某些特定的轴承装置中使用接触限制。该改进与通过视觉检查在某些轴承装置中发现的结构变化相符。结果，获得了能够再现模态，静态和动态结构响应的更新数值模型，表明实验数据与数值数据之间具有很好的一致性。在将来的应用中，此更新的数值模型将有助于评估交通负载下桥梁的状况，即基于SHM系统与（随机）负载和故障模型的集成来识别损坏并支持采用生命周期维护策略。该改进与通过视觉检查在某些轴承装置中发现的结构变化相符。结果，获得了能够再现模态，静态和动态结构响应的更新数值模型，表明实验数据与数值数据之间具有很好的一致性。在将来的应用中，此更新的数值模型将有助于评估交通负载下桥梁的状况，即基于SHM系统与（随机）负载和故障模型的集成，识别损坏并支持采用生命周期维护策略。该改进与通过视觉检查在某些轴承装置中发现的结构变化相符。结果，获得了能够再现模态，静态和动态结构响应的更新数值模型，表明实验数据与数值数据之间具有很好的一致性。在将来的应用中，此更新的数值模型将有助于评估交通负载下桥梁的状况，即基于SHM系统与（随机）负载和故障模型的集成，识别损坏并支持采用生命周期维护策略。在实验数据和数值数据之间显示出非常好的一致性。在将来的应用中，此更新的数值模型将有助于评估交通负载下桥梁的状况，即基于SHM系统与（随机）负载和故障模型的集成，识别损坏并支持采用生命周期维护策略。在实验数据和数值数据之间显示出非常好的一致性。在将来的应用中，此更新的数值模型将有助于评估交通负载下桥梁的状况，即基于SHM系统与（随机）负载和故障模型的集成来识别损坏并支持采用生命周期维护策略。