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IAEA project aims to develop polymer irradiation model
The International Atomic Energy Agency has launched a new coordinated research project (CRP) aimed at creating a database of polymer-radiation interactions in the next five years with the long-term goal of using the database to enable machine learning–based predictive models.
Radiation-induced modifications are widely applicable across a range of fields including healthcare, agriculture, and environmental applications, and exposure to radiation is a major factor when considering materials used at nuclear power plants.
Meng Yue, Lap-Yan Cheng, Robert A. Bari
Nuclear Technology | Volume 162 | Number 1 | April 2008 | Pages 26-44
Technical Paper | Reactor Safety | doi.org/10.13182/NT08-A3931
Articles are hosted by Taylor and Francis Online.
A Markov model approach is developed for the evaluation of proliferation resistance (PR) of nuclear energy systems. The focus of this study is to create a high-fidelity probabilistic assessment model that better represents nuclear energy systems. Both extrinsic and intrinsic barriers associated with the energy systems are considered. Modeling uncertainty and safeguards false alarms, composite safeguards approaches, concealment, and human performance are particularly discussed in detail and incorporated in the Markov model. These features are anticipated to have significant impacts on PR assessment. The Markov model approach is adapted to a hypothetical example sodium fast reactor (ESFR) system using physically meaningful parameters that can be obtained from physical processes. Development of metrics for six PR measures is discussed. Computation of the PR measures using the Markov model of the ESFR system is illustrated. The results obtained in this study demonstrate applicability and effectiveness of the Markov model approach in the PR assessment.