An Uncertainty Judgment Method for Passive Waste Heat Removal System

Abstract

The invention provides an uncertainty judgment method of a passive residual heat removal system. The uncertainty judgment method has the outstanding advantages that a new sampling method is provided and fitting precision of a fitting function in an invalidation area is improved. The sampling method is capable of increasing proportion of invalid sample points in gross sample points and improving fitting accuracy of the invalidation area. The uncertainty judgment method has another advantage that relation of input and output variables is fitted by an artificial neural network, so that limitations of the quadratic polynomial on function modes are avoided. Meanwhile, reliability probability is calculated by Monte Carlo sampling instead of a simple second-order matrix method, and error caused by secondary processing is avoided.

Description

technical field [0001] The invention relates to reliability analysis of a passive system, in particular to a method for judging the uncertainty of a passive system. Background technique [0002] Under accident conditions, when the function of the normal heat transfer system is completely lost, the residual heat in the reactor is discharged into the atmosphere by natural convection through the reactor vessel air cooling system (RVACS, hereinafter referred to as RVACS). The RVACS system consists of a safety container, a cylindrical isolation layer, a hot air ascending duct, a cold air descending channel, a thermal isolation layer inside the concrete, a pit, and a chimney outside the containment. The heat removal mechanism of the accident waste heat removal system is: heat conduction from the main container, heat radiation from the main container to the safety container, heat conduction from the safety container, heat radiation from the safety container to the hot air pipe and ...

AI Technical Summary

Problems solved by technology

[0010] In summary, the sampling cost of the existing method is too high, and it is impossible to quickly judge the influence of parameter uncertainty on the safety of the passive waste heat removal system. At the same time, the linear approximation in the data processing process reduces the accuracy of the safety judgment of the passive waste heat removal system. A method for judging the uncertainty of passive waste heat removal systems has improved sampling efficiency and result accuracy, and has increased the ability to correctly and quickly judge the safety of passive waste heat removal systems

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