This study presents a novel approach to simulating the fatigue stress spectra of short- to medium-span bridges under stochastic and dynamic traffic loads. The stochastic traffic load is simulated based on the weigh-in-motion (WIM) measurements of a heavy-duty highway bridge in China, and the dynamic effects are modeled using a vehicle-bridge coupled vibration system. An interpolation RSM is used to approximate the effective stress ranges of a bridge with respect to road roughness conditions, gross vehicle weights, vehicle configurations, and driving speeds. The RSM provides a platform for an efficient spectrum simulation of bridges under stochastic and dynamic traffic loads. A case study of a simply supported T-girder bridge demonstrates the effectiveness and efficiency of the proposed approach. The proposed computational framework provides an effective approach for simulating the fatigue stress spectra for short- to medium-span bridges with WIM data. However, the efficiency of the approach depends on the number of intervals of driving speed and gross vehicle weight in the interpolation RSM. Additionally, overloading control has a considerable influence on the probability density of the high-amplitude stresses in the fatigue stress spectrum. Even a relatively high overloading limit value will considerably increase the fatigue reliability of a bridge. In addition, the numerical results provide a theoretical basis for bridge deck retrofitting and truck overloading control measures.

Bridges are vulnerable to the fatigue damage accumulation caused by traffic loading over the service period. A continuous growth in both the vehicle weight and the traffic volume may cause a safety hazard to existing bridges. This study presented a computational framework for probabilistic modeling of the fatigue damage accumulation of short to medium span bridges under actual traffic loading. Stochastic truck-load models were simulated based on site-specific weigh-in-motion measurements. A response surface method was utilized to substitute the time-consuming finite element model for an efficient computation. A case study of a simply supported bridge demonstrated the effectiveness of the computational framework. Numerical results show that the simulated fatigue stress spectrum captures the probability density functions of the heavy traffic loading. The equivalent fatigue stress range increases mostly linearly in the good road roughness condition with the growth of the gross vehicle weight. The vehicle type and the road roughness condition affect the stress range. The influence of the driving speed on the equivalent stress range is non-monotonic. The bridge fatigue reliability has a considerable increase even under a relatively high overload limit. It is anticipated that the proposed computational framework can be applied for more types of bridges.