Irradiation increases the yield stress and embrittles light water reactor(LWR)pressure vessel steels.In this study,we demonstrate some of the potential benefits and risks of using machine learning models to predict ir...Irradiation increases the yield stress and embrittles light water reactor(LWR)pressure vessel steels.In this study,we demonstrate some of the potential benefits and risks of using machine learning models to predict irradiation hardening extrapolated to low flux,high fluence,extended life conditions.The machine learning training data included the Irradiation Variable for lower flux irradiations up to an intermediate fluence,plus the Belgian Reactor 2 and Advanced Test Reactor 1 for very high flux irradiations,up to very high fluence.Notably,the machine learning model predictions for the high fluence,intermediate flux Advanced Test Reactor 2 irradiations are superior to extrapolations of existing hardening models.The successful extrapolations showed that machine learning models are capable of capturing key intermediate flux effects at high fluence.Similar approaches,applied to expanded databases,could be used to predict hardening in LWRs under life-extension conditions.展开更多
基金D.M.,H.W.,R.J.,and T.M.gratefully acknowledge partial funding from NSF SI2-SSI award 1148011the Light Water Reactor Sustainability program,and Nuclear Energy University Program (NEUP) 21-24382+1 种基金Y.-c.L.gratefully acknowledge the financial support from Graduate Student Study Abroad Program (GSSAP) (107-2917-I-006-008),project (110-2222-E-006-008) from the Ministry of Science and Technology (MOST)the Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) and MOST (110-2634-F-006-017) in Taiwan,China.
文摘Irradiation increases the yield stress and embrittles light water reactor(LWR)pressure vessel steels.In this study,we demonstrate some of the potential benefits and risks of using machine learning models to predict irradiation hardening extrapolated to low flux,high fluence,extended life conditions.The machine learning training data included the Irradiation Variable for lower flux irradiations up to an intermediate fluence,plus the Belgian Reactor 2 and Advanced Test Reactor 1 for very high flux irradiations,up to very high fluence.Notably,the machine learning model predictions for the high fluence,intermediate flux Advanced Test Reactor 2 irradiations are superior to extrapolations of existing hardening models.The successful extrapolations showed that machine learning models are capable of capturing key intermediate flux effects at high fluence.Similar approaches,applied to expanded databases,could be used to predict hardening in LWRs under life-extension conditions.
