Nuclear power plant accident online diagnosis and state tracking prediction method

Abstract

The invention relates to the technical field of nuclear safety and nuclear emergency, particularly to a nuclear power plant accident online diagnosis and state tracking prediction method. The existingnuclear power station diagnosis, evaluation and prediction system has the defects that the system seriously depends on a sample library, a diagnosis result is not accurate enough, and accident progress prediction is not enough. The method comprises the following steps: 1, identifying the state of a power plant; 2, identifying accident type/sequence; 3, carrying out arbitrary initialization; 4, carrying out a thermal hydraulic analysis program; and 5, carrying out comparing treatment. The method is comprehensive in accident diagnosis information, quick in response and accurate in judgment, canpredict three intervention schemes at the same time, and is high in efficiency.

Description

technical field [0001] The invention relates to the technical field of nuclear safety and nuclear emergency, in particular to a method for on-line diagnosis and state tracking and prediction of nuclear power plant accidents. Background technique [0002] During a nuclear power plant accident, especially under severe accident conditions, plant operators and emergency response technicians will be under considerable stress. Severe accidents are often accompanied by loss of power supply or large-scale damage to power plant instruments. At this time, the nuclear power plant is basically in a state of a black box, and the status information of the power plant that can be obtained is very limited. In this case, it is necessary to judge the root cause and state of the power plant accident based on limited data, and give correct intervention measures in a short period of time to alleviate the process of the accident and restore the power plant to a controllable state , is a great ch...

AI Technical Summary

Problems solved by technology

[0006]1. The diagnosis results are heavily dependent on the sample library. Enumerate all accident sequences;

[0007]2. The judgment of the root cause of the accident is based on the matching of the characteristic parameters and the sample library. The post-stage phenomenon of severe accidents is basically consistent with the heating and melting of the core. This characteristic parameter The matching method may give a variety of root causes of the accident, it is difficult to give accurate diagnosis resul

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