Reliability is one of the most important properties of road bridges due to their degree of responsibility and strategic importance for the transport system. For steel-reinforced concrete bridges, which are widespread nowadays, the question of their overall structure reliability dependence on the element’s condition of steel beam and reinforced concrete slab connection remains not fully studied. The authors have performed fatigue damage accumulation numerical modelling in the conjunction elements of steel-reinforced concrete beam from the cyclic temporary loads influence and analysed this process influence on the overall structure reliability. Based on the previous studies data, a relationship model between the conjunction element shear rigidity and the amount of damage accumulated by it is proposed. The nonlinear finite element calculation algorithm with regard to the conjunction element’s rigidity reduction is proposed and tested on the model of the steel-reinforced concrete superstructure. The selection method of the equivalent time load for modelling the accumulation of fatigue damage process from traffic flow is proposed. In order to optimise the computational resources used it is proposed to use loading process clusterization into enlarged cycles groups and the rational group size is determined. A numerical experiment on the simply supported steel reinforced concrete beam model with different loading cycles number (from 1 loading to 100 million loading cycles) to determine the reliability index β under the assumption of variability of two parameters — design steel resistance and the value of temporary load. FORM (First Order Reliability Method) was used for probabilistic analysis. The study results have shown that the accumulation of fatigue damage in the elements of steel-reinforced concrete superstructures has a significant effect both on the load-bearing capacity of the superstructure beams and on the quantitative indicators of structural reliability (increase in the probability of structural failure, decrease in the reliability index β).
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