Exhaustive simulation approach for severe accident risk in nuclear power plants: OPR-1000 full-power internal events. (September 2022) - Cho, Jaehyun; Lee, Sang Hun; Bang, Young Suk; Lee, Suwon; Park, Soo Yong
Highlights: A MAAP5 automatic input generator using PSA event trees was developed. 690 severe accident scenarios of OPR-1000 internal events were simulated. Simulation of all the accident scenarios only required three days using a commercial computer. The exhaustive simulation approach was shown to combine sufficiently similar scenarios. Significant discrepancies between the risk values from two approaches were found (84%∼223%). Abstract: The estimation of severe accident risks in nuclear power plants (NPPs) is significant to confirm the safety level of NPPs and to reinforce their vulnerable points. Severe accident risks can be quantified by Level 2 probabilistic safety assessment (PSA), which traditionally applies a grouping feature to handle the tremendous numbers of accident scenarios. Accordingly, risk information is likely to be lost in the process of grouping similar scenarios and in the treatment of many scenarios with one representative scenario. To obtain more comprehensive risk information including source term behaviors and plant responses during severe accidents, this study suggests an exhaustive simulation approach with new software that helps to automatically generate a large number of input data for an accident simulation code, and performs an application study using PSA models from OPR-1000 full-power internal events. Only a three-day run time was required to simulate all the severe accident scenarios, totaling 690 scenarios, using a commercial computer. The application study revealed that the conventional grouping approach can either underestimate or overestimate overall NPP risk depending on the selection of the representative scenario.