Hitachi-Ge Nuclear Energy, Ltd.

Mayu Sasaki

Tsuyoshi Ito

Hideyuki Hosokawa

Naoshi Usui

Hiroko Sukeda

Kazushige Ishida

Masahiko Tachibana

Youichi Wada

Ryosuke Shimizu

Nobuyuki Oota

More accurate prediction of reactor water quality of a nuclear reactor is implemented. A device for prediction of reactor water quality of a nuclear reactor in a nuclear power plant is disclosed. The device stores a reactor water quality prediction model which is learned using learning data, and with which future reactor water quality is predicted. An explanatory variable of the reactor water quality prediction model includes a value in a predetermined period unit that is generated from data acquired in an operating nuclear power plant. The device generates the value in a predetermined period unit from data acquired in a target operating nuclear power plant, and acquires a predicted value of the reactor water quality in the target nuclear power plant based on the reactor water quality prediction model and the value in a predetermined period unit.

Device for prediction of reactor water quality of nuclear reactor

A reactor water radioactivity concentration of a nuclear power plant can be predicted with high accuracy. First, a plant state quantity prediction value is calculated by using a physical model that describes plant state quantities of the power plant including a flow rate of feedwater and a metal corrosion product concentration in feedwater of the reactor water is calculated. Next, data for supervised learning is created, and the data for supervised learning includes the previously calculated plant state quantity prediction value and a plant state quantity such as the flow rate of feedwater, the metal corrosion product concentration in feedwater, a metal corrosion product concentration in reactor water, and a radioactive metal corrosion concentration of the reactor water in the reactor as input data and includes a radioactive metal corrosion concentration in the reactor water which is an actual measured value as output data, and a predictive model is trained.

Predictive model construction and prediction method for radioactive metal corrosion concentration in nuclear reactor water

The present disclosure provides a method for relieving a corrosive environment of a boiling water reactor, the method including a step of injecting hydrogen and a noble metal compound into water to be replenished into the reactor pressure vessel during a period of a generating operation of a boiling water nuclear power plant including the reactor pressure vessel. In the method, the hydrogen is injected into water to be supplied into the reactor pressure vessel, and the noble metal compound is injected into water in a line of the boiling water nuclear power plant in which a concentration of oxygen or hydrogen peroxide is stoichiometrically higher than the concentration of hydrogen at which hydrogen undergoes a chemical reaction to turn to water. Thus, when a noble metal is injected into a boiling water reactor, the noble metal can be restrained from adhering onto a pipe for an injection and other pipes, and thereby can increase the amount of the noble metal to be injected into a cooling water in a reactor pressure vessel.

Method for relieving corrosive environment of boiling water reactor, nuclear power plant, and method for injecting noble metal which is carried out in nuclear power plant

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Ibaraki, Japan

Mayu Sasaki