[1G07-11] Reactor Pressure Vessel Steels

2:45 PM - 3:00 PM JST(5:45 AM - 6:00 AM UTC)

[1G07] Prediction model for Charpy absorbed energy of reactor pressure vessel steels using machine learning method

*Yoshinori Hashimoto¹, Akiyoshi Nomoto¹, Mark Kirk¹ (1. CRIEPI)

Keywords:

Machine learning,Reactor pressure vessel steel,Neutron irradiation embrittlement,Charpy absorbed energy

Predictions of the ductile to brittle transition temperature (DBTT) and upper shelf energy (USE) are used in the neutron irradiation embrittlement estimation for the reactor pressure vessel (RPV) steels. DBTT and USE are calculated from the temperature dependence of Charpy absorbed energy. If the CVE can be predicted, the irradiation embrittlement can be directly predicted and estimated. In this presentation, we discuss the construction of the prediction model for the CVE of RPV steels using the US REAP database and the machine learning method, the use of which has been rapidly expanding in recent years.