Using Monte Carlo Method and Adaptive Sampling to Estimate the Limit Surface

Abstract In the research on the risk-informed safety margin characterization (RISMC) methodology, how to estimate the limit surface is important. Using the reduced Order Models (ROMs) to simulate calculations can obtain results more quickly and estimate the limit surface. For example, we use ROMs instead of Complex simulation model, Parameters that are critical to the safety of nuclear power plants, such as the peak temperature of the fuel cladding, can be calculated relatively quickly. Using Monte Carlo method to analyze nuclear accident is low efficiency and poor accuracy. To get relatively accurate results, a large amount of simulation experiments is needed. Based on adaptive sampling, the samples which will cause failure will be acquired more easily. Adaptive sampling uses the calculation results of the previous step to guide the next step of sampling, which can quickly obtain the samples points near the failure edge. This article will introduce the definition of the limit surface and use the Monte Carlo method and the adaptive sampling to estimate the limit surface through ROMs. And compare the calculation results of the two methods and the number of samples required. The two methods are verified by a case.