Reliability intelligence analysis of concrete arch bridge based on Kriging model and PSOSA hybrid algorithm

Abstract

The traditional probabilistic reliability analysis methods have problems such as poor convergence, low calculation accuracy, and long time-consuming in the reliability calculation of concrete arch bridges. Due to the uncertainty of the parameters of the structure itself, the performance function is highly nonlinear, and other factors. A reliability calculation method for concrete arch bridges based on the Kriging model and particle swarm optimization algorithm (PSOSA) based on a simulated annealing algorithm is proposed. Take advantage of the Kriging model in small samples, nonlinear, high-dimensional data processing capabilities. With the help of the PSO algorithm, it has the advantages of strong global optimization ability and strong robustness. Combined with the SA algorithm self-adaptive, variable probability mutation operation. The ability of the PSO algorithm to get rid of the local minima is enhanced and supplemented, effectively avoiding falling into the local minima and making the result tend to the global optimum, which improves the slow convergence speed and precociousness of the traditional PSO algorithm. A numerical example verifies the method's effectiveness, and a reliability evaluation of an actual concrete arch bridge is carried out. The research results show that the method improves the calculation accuracy, dramatically improves the calculation efficiency, and realizes the rapid and accurate assessment of the reliability of complex bridge structures.