The Nuclear Energy Agency (NEA) is a specialized agency within the Organization for Economic Co-operation and Development (OECD). The International Fire Data Exchange Project (OECD FIRE) was designed by the NEA to encourage multilateral co-operation in the collection and analysis of data relating to fire events in nuclear power plants. We used Python advanced software to analyze the data related to CANDU reactor plants in Canada from the OECD FIRE Database, while providing weighting factors/percentage tables to be used in CANDU Fire probabilistic risk assessment analysis. We also used 5 different time-series methods to predict future potential fires in CANDU reactors, compared the results from different methods, and identified the best method to predict future fires in CANDU power plants.
Fire Probabilistic Risk Assessment (PRA) is being introduced to the fire protection engineering practice both locally and worldwide. The commercial nuclear power industry has also experiencing the impact of this new approach. This paper examines the work performed to assess the relative accuracy of fire models for CANDU nuclear power plant (NPP) applications. The Canadian NPP uses some portions of NUREG/CR-6850 in performing fire PRA. Canadian fire ignition frequencies have been provided by International Fire Data Exchange Project. The CANDU Fire PRA Model can quantitatively evaluate plant damage states and core damage frequencies. This model will assist fire engineers in performing CANDU Fire PRA analysis, by recognizing vulnerabilities related to fire events and will contribute to further improvement of the Canadian NPPs’ safety.
A fuel survey was carried out at all operating CANDU reactors in Canada in 5 sites (Bruce A, Bruce B, Darlington, Pickering, and Point Lepreau). The survey used the National Fire Protection Association 557 combination method for the fire zones that contain fire safe shutdown analysis equipment. A fire zone group list for the sites was developed to combine fire zones with similar functions; 38 fire zone groups were produced from this exercise. The results of the survey show that the average fuel load density for all 1230 fire zones is 170.1 MJ/m2, and the average fuel load is 79 183 MJ. The maximum fuel load density is 1319 MJ/m2, and the maximum fuel load is 2 785 404 MJ. High-energy arcing faults risk was found in 254 fire zones out of the 1230 fire zones. Electric fault is the highest ignition source risk present in all 1230 fire zones.
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