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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.
Ke Zhao, Belle R. Upadhyaya, Richard T. Wood
Nuclear Technology | Volume 153 | Number 3 | March 2006 | Pages 326-340
Technical Paper | Nuclear Plant Operations and Control | doi.org/10.13182/NT06-A3711
Articles are hosted by Taylor and Francis Online.
A design approach to sensor fault detection and isolation (FDI) of helical coil steam generator (HCSG) systems of the International Reactor Innovation Secure (IRIS) reactor is presented. In the design phase, a physical model is first developed to provide a realistic simulation and generate data characterizing the system dynamics. A subspace identification technique is then used to extract a low-order linear state-space model from the data. Finally, a robust dynamic parity space approach is utilized to design residual generators for FDI. This design approach is able to achieve fault isolation following a predetermined logic without the need to use data during fault conditions, which is an unrealistic assumption of many FDI approaches studied for nuclear power plants. The results of the HCSG application show that the approach is robust to not only measurement and process noises but also operation condition changes and has the capability of correct FDI during reactor power transients and during the propagation of sensor faults in a control loop.