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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.
Günyaz Ablay, Can Emre Koksal, Tunc Aldemir
Nuclear Science and Engineering | Volume 170 | Number 1 | January 2012 | Pages 27-43
Technical Paper | doi.org/10.13182/NSE10-21
Articles are hosted by Taylor and Francis Online.
A secure long-distance monitoring scheme is proposed for nuclear engineering applications using chaos synchronization and nonlinear observers for online transmittal of operational data, distance monitoring, fault detection, and other related processes. The proposed system consists of three components: (a) chaotic transmitter to encrypt and send signals coming from a message originating system, (b) chaotic receiver to decrypt information signals, and (c) reconstruction of the message originating system using the decrypted signals. The Lorenz chaotic system whose parameters are defined as nonlinear functions of the state variables to improve the security level of the chaos-based communication is considered as the chaotic encrypter. In the receiver section, a nonlinear observer is used to provide synchronization and to decrypt the message signal. A similar nonlinear observer is employed to reconstruct the message originating system state variables from the recovered message signal. Numerical results and case studies against certain passive eavesdropping attacks are provided to demonstrate the resilience of the proposed method. A reduced-order boiling water reactor model is used as the message originating system in the illustrations.