In order to improve the calculation efficiency for seismic reliability of cast iron pipelines with bell-and-spigot joints

a Monte Carlo simulation method based on active learning Kriging model (AK-MCS) was proposed to calculate the seismic reliability of buried pipelines. A seismic response analysis model for buried pipeline system was established

in which the beam element was adopted to simulate the pipeline structure

and soil spring and joint spring were used to simulate the pipe-soil interaction and the constraint of adjacent pipe segments respectively. Considering the randomness of critical parameters such as the allowable displacement of pipeline joints

the depth of the pipeline

the unit weight

and the friction angle of the surrounding soil

based on the safety criteria of the allowable relative joint displacement

the active learning Kriging method was used to establish a surrogate model between the relative displacement of the pipeline joint and the random parameters. The safety margin of the pipeline joint was subsequently obtained through the validated surrogate model. Numerical results show that the relative difference of the pipeline failure probability between AK-MCS method and standard MCS method was less than 5%

and the computational time of the AK-MCS method was only about 2% of the standard MCS method. Therefore

the proposed AK-MCS method is an efficient alternative to evaluate the seismic reliability of buried pipelines.