Research of Functional Reliability Evaluation Method for Passive Systems Based on Data Mining Technology

In order to solve the problem of multi-dimensional uncertainty parameters and small probability of functional failure, an innovative functional reliability estimation method named Data Mining Technology was presented. In the presented method, with the combination of the bootstrap response surface model and optimization line sampling design, the functional failure probability can be evaluated with high efficiency. This method was applied in the natural circulation cooling in Xi’an Pulsed Reactor (XAPR). Combined with Medium Break Loss of Coolant Accident (MLOCA), the uncertainties related to the input parameters and the model were considered. And then the probability of functional failure was estimated with the presented method. The numerical results show that the bootstrap response surface model has a high degree of fitting, and the optimized line sampling technique has a high computational efficiency and an excellent computational accuracy. In addition, the evaluation method in this paper has strong adaptability to the implicit nonlinear functional failure analysis of the passive systems.