Research On Reliability Assessment Method Of Marine Passive Residual Heat Removal System

The inherent safety of marine nuclear power plant is an important index to evaluate its performance.Complicated ocean motions will introduce unsteady-state force fields,change the thermal and hydraulic characteristics of passive safety systems.Quantifying the reliability of passive safety systems is an important part of the extensive use of passive systems in marine nuclear power plants.In this paper,aiming at the deficiencies in the existing research,the research on the reliability analysis method of marine passive resiudal heat removal system was carried out.In this paper,a thermal hydraulic program suitable for passive system reliability analysis under ocean conditions is developed.The applicability of the program is verified by comparison with reference values.The uncertainty analysis function is added to the program,which lays the foundation for further reliability analysis.The operational characteristics of passive resiudal heat removal system in the marine-type integrated pressurized water reactor IP200 under different ocean conditions was studied.The results show that the inclining conditions will cause uneven flow distribution on the left loops and right loops,and the flow offset value will increase as the inclining angle increases.The natural circulation flow rate of the core reduces,and the coolant temperature increases significantly.The larger the rolling amplitude or the smaller the period is,the greater the natural circulation flow fluctuations in the loop are.The fluctuation amplitude of the flow is small,and the fluctuation period is half of the rolling period.When the rolling motion is severe,the average flow rate of the core coolant decreases and the coolant temperature increases.The rolling motion will cause the flow of the passive residual heat removal system to oscillate at a high frequency.Under heaving conditions,both the coolant flow rate and the passive residual heat removal system flow rate show the same flow fluctuation as the heaving period.The amplitude of the total core flow is close to the sum of the amplitudes of the loops.With larger fluctuation amplitudes and periods,the flow fluctuations increase,and the fluctuation amplitudes are more significant than the fluctuation periods.In order to solve the problems of high calculational cost and insufficient accuracy in the existing passive safety system reliability assessment methods,a high-precision surrogate model research was carried out based on the kriging model in this paper.The calculation results show that the use of particle swarm optimization algorithm instead of the pattern search method,which is commonly used in traditional Kriging models,can effectively reduce the dependence on the initial point in the process of solving hyperparameters.Tthe multi-point parallel method effectively avoids the possibility of falling into a local optimum.Particle swarm optimization to solve hyperparameters can improve the robustness of the model.The kriging model based on the polynomial chaos expansion as a trend function can take advantage of the strong global approximation ability of the polynomial chaos expansion,significantly improve the global approximation ability of the model,and further improve the accuracy of the kriging model.In order to further improve the efficiency of passive system reliability asssessment,the research about optimized sampling strategies was carried out.The sample point added to the experimental design is determined according to the the adaptive learning function,which is used to update the kriging model.On this basis,the metamodel-based importance sampling method is improved,and the adaptive kriging model is used to replace the real model to solve the indicator function value in the important samples set,to reduce the runs of the numerical model.The results show that the adaptive kriging model determines the optimal sample point according to the U function.It's able to accurately move the sampling points to the domain with greater uncertainty in prediction or the vicinity of the limit state function,which can effectively improve the sampling efficiency.Improved metamodel-based important sampling method coupled with adaptive kriging model solves the issue that the importance sampling method cannot analyze multiple failure domain problems.At the same time method proposed avoids the need to repeatedly call the real numerical model when solving the correction factor in the traditional meta-model important sampling method.The important sampling probability density function construced by the iterative improvement strategy approaches the optimal solution.The sampling center is moved near the failure domain and improve the quality of the samples in the candidate sample pool.The process of adaptive sampling is speeded up and calculational cost is significantly reduced.The improved algorithm has good applicability to small failure probability problems,multiple failure region problems,and high-dimensional problems.The reliability of the passive residual heat removal system in IP200 is analyzed under ocean conditions.The improved metamodel sampling algorithm is used to calculate the probability of functional failure.Surrogate model technology and global sensitivity analysis methods are combined to perform sensitivity analysis,which helps to identify key parameters that affect system function.The physical process failure is integrated into the probabilistic safety analysis model.The improved meta-sampling algorithm can significantly reduce the number of calls to the RELAP5 program.The global sensitivity analysis combining the Kriging model and the Sobol method solves the problem that the local sensitivity analysis cannot consider the interaction influence between the parameters and avoids the large calculation amount of the global sensitivity analysis method.The results show that ocean conditions have an important effect on the failure of passive residual heat removal systems.The inclining angle,rolling amplitude,and period of motion have significant effects on the function of the passive systems.The results of probabilistic safety analysis indicate that the failure of the passive system plays a leading role in system reliability,and the failure of the check valve and the blockage of the heat exchanger also have a great impact on the system reliability.The reliability analysis method of passive safety system proposed in this paper can consider the influence of uncertain factors introduced by ocean conditions on marine nuclear power plant and fill the gap in the reliability assessment of marine nuclear power passive system.It solves the defects of traditional analysis methods such as low analysis efficiency and insufficient accuracy.It helps improve the safety and reliability of nuclear power plants and has practical significance for the wide application of the passive safety system in marine nuclear power plant.