Probabilistic estimation of dynamic impact factor for masonry arch bridges using health monitoring data and new finite element method

Abstract

The presence of uncertainties in the behavior of rolling stock, infrastructure, and the interaction between them undoubtedly generates a probabilistic nature for the structure impact factor. Such an effect becomes more severe in the case of the aged structures, specifically masonry arch bridges. This research initially provides a probabilistic estimation for the impact factor based on the ratio of the dynamic to static loads by using Weigh-In-Motion data. Then, the research is followed by proposing a new finite elements approach for a more precise estimation of the structure response pattern and a more rigorous evaluation of the masonry arch bridges. It uses optimization techniques for updating the model and results in the probabilistic estimation of the impact factor by using field measurements. Through these two methods and by using data from continuous monitoring of an 80-year-old masonry arch bridge with a length of 100 m and a span of 66 m, the impact factor is surveyed. The outputs prove to be 50% more accurate compared with the already established methods. The rate of variations of the impact factor within the first proposed method is 1.6 times more compared with the second approach. This emphasizes the uncertainties in the available approaches and the probabilistic nature of the impact factor. Therefore, the assumption of the absolute certainty for the impact factor becomes questionable. This survey reveals that for the best cases, the available certainty-based methods can only cover 17% of the probabilistic domain of the impact factor.