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

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.