随机车流-风联合作用下沿海大跨度斜拉桥拉索疲劳寿命预测

为了预测沿海大跨度斜拉桥拉索在车流、风和波浪等变幅荷载长期作用下的疲劳寿命，提出了沿海大跨斜拉桥拉索在随机车流、风和波浪荷载联合作用下拉索应力谱的计算方法和步骤，并基于线性疲劳累积损伤理论建立了斜拉桥拉索疲劳可靠度的计算框架。首先，根据桥上实测车流数据，建立了随机车流模型，基于桥址处风浪观测数据，运用二维Copula函数建立了桥址处风浪联合概率模型。然后，将生成的随机车流及风浪荷载作为外部激励，基于风-浪-车-桥耦合振动数值模拟平台，实现随机车流、风、浪荷载联合作用下的斜拉索应力谱的计算分析。最后，基于线性疲劳累积损伤理论推导了服役期内斜拉索疲劳可靠度及疲劳寿命预测公式，并以一座沿海大跨斜拉桥为例，结合桥址处的实测车流、风和波浪数据，计算了拉索在随机车流、风和波浪荷载联合作用下关键拉索的疲劳寿命。结果表明：车辆荷载主要影响拉索的应力响应均值，风荷载主要影响拉索的应力响应的脉动部分，而波浪荷载对拉索的应力响应影响非常小，可以忽略。此外，在随机车辆、风和波浪荷载共同作用下，拉索的日累积疲劳损伤符合威布尔分布，并且岸侧拉索的中间索疲劳寿命最低，为121年。研究成果可为沿海大跨度斜拉桥拉索疲劳可靠度分析及疲劳寿命预测研究提供参考。

Fatigue Life Prediction of Cables Used in Coastal Long-span Cable-stayed Bridges Under Stochastic Traffic and Wind Loads

Here, a method to predict the fatigue life of cables used in coastal long-span cable-stayed bridges subject to long-term variable-amplitude traffic, wind, and wave loads was proposed. The proposed method computed the stress spectrum of the cables under combined stochastic traffic, wind, and wave loads. Based on this, a numerical framework for the fatigue reliability assessment of cables was established using the linear fatigue cumulative damage rule. First, the stochastic traffic flow was developed according to a statistical analysis of the traffic data on the bridge. Meanwhile, the joint probability distribution function of the correlated wind and wave data was also established using the Copula function, based on the historical wind and wave data at the bridge site. The traffic and joint wind and wave models were further used as external dynamic excitations of the established wind-wave-vehicle-bridge numerical platform to subsequently extract the stress spectrum of the cables. Finally, the linear fatigue cumulative damage rule was applied to derive the formulae for fatigue reliability assessment and fatigue life prediction of the cables during operation. As an example, the fatigue life of critical cables of a coastal long-span cable-stayed bridge under stochastic traffic, wind, and wave loads was predicted using insitu traffic, wind, and wave data at the bridge site. The results indicate that the traffic load mainly contributes to the mean trend of the stress response of the cables. Furthermore, wind mainly controls the fluctuations in the stress response of the cables, while waves havea negligible impact. Additionally, it was found that the daily fatigue damage accumulation of the cables under traffic, wind, and wave loads follows the Weibull distribution, and the middle cable at the riverbank sidehas the lowest fatigue life of 121 years. The results of the present study can provide a valuable reference for fatigue reliability evaluation and fatigue life prediction of cables of coastal long-span cable-stayed bridges.