Abstract: Probabilistic safety performance of nuclear containment structure subjected to severe accident conditions is the focus of probabilistic safety assessment (PSA) of nuclear power plant structures. Based on detailed three-dimensional finite element model of the nuclear containment structure, probabilistic safety performance of nuclear containment structure under severe accident conditions is evaluated in this study. To realize the automatic running of nonlinear finite element analysis, Python and Matlab scripts are developed. To quantitatively evaluate the effect of statistical uncertainty on the fragility function parameters, statistical inference and bootstrap method are used to estimate the confidence interval of the fragility function parameters. Moreover, statistical characteristics of reliability index and total failure probability of the nuclear containment structure are quantitatively analyzed by bootstrap method. Finally, median value and confidence interval method are used to evaluate the safety margin of the nuclear containment structure. Results indicate that confidence interval of fragility function parameter,p_\rmm, estimated by statistical inference and bootstrap method are almost the same. As for confidence interval of fragility function parameter \beta _\rmS, statistical inference method tends to overestimate the confidence interval of fragility function parameter \beta _\rmS. Statistical uncertainty of fragility function parameters has negligible influence on reliability index and total failure probability, and the influence of the statistical uncertainty of the fragility function parameters on total failure probability is greater than that of reliability index. There is small difference between the safety margin calculated by median value method and the safety margin with 95% confidence level calculated by confidence interval method. In general, nuclear containment structure used in this study meets the requirements of probabilistic performance under severe accident conditions, and it also meets the requirements of safety margin of no less than 2.5.