On-line diagnosis and status tracking prediction method for nuclear power plant accidents

Abstract

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. Existing nuclear power plant diagnosis, evaluation, and prediction systems have shortcomings such as relying heavily on sample libraries, inaccurate diagnosis results, and insufficient prediction of accident progress. The present invention comprises the following steps: Step 1: power plant state identification; Step 2: accident type / sequence identification; Step 3: random initialization; Step 4: thermal hydraulic analysis program; Step 5: comparison processing. The invention has comprehensive accident diagnosis information, quick response, accurate judgment, can simultaneously predict three intervention schemes, and has high 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 results, and the support for emergency response is limited;

[0008] 3. Based on the diagnosis of this root cause, as the input of the predictive calculation module, it is difficult to accurately predict the progress of the accident, because the prediction of serious accidents is not only related to the sequence of accidents, but also related to the time when various accidents occur, so it is only based on accidents Sequence predictions cannot correctly reflect the real evolution of nuclear power accident states

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