Sodium fast reactor power monitoring using F tagging agent

نویسندگان

  • R. Coulon
  • S. Normand
  • T. Domenech
  • G. Corre
  • T. Montagu
  • T. Dautremer
  • E. Barat
چکیده

This work deals with the use of gamma spectrometry to monitor the fourth generation of sodium fast reactor (SFR) power. Simulation part has shown that power monitoring in short response time and with good accuracy is possible measuring liquid sodium delayed gamma emitters produced in-core. An experimental test is under preparation at French SFR Phénix experimental reactor to validate simulation studies. Physical calculations have been done to correlate gamma activity to the released thermal power. Gamma emitter production rate in the reactor core was calculated with technical and nuclear data as sodium velocity, atomic densities, neutron spectra and incident neutron cross-sections of reactions producing gamma emitters. Then, a thermal hydraulic transfer function was used for taking into account primary sodium flow in our calculations and gamma spectra were determined by Monte-Carlo simulations. For power monitoring problematic, use of a short decay period gamma emitter will allowed to obtain a very fast response system without cumulative and flow distortion effects. The experiment will be set during the reactor “end of life testing”. The Delayed Neutron Detection (DND) system cell has been chosen as the best available primary sodium sample for gamma power monitoring on Phénix reactor due to its short transit time from reactor core to measurement sample and homogenized sampling in the reactor hot pool. The main gamma spectrometer is composed of a coaxial high purity germanium diode (HPGe) coupled with a transistor reset preamplifier. The signal will be then processed by a digital signal processing system (called Adonis) which is optimum for high count rate and various time activity measurements. To limit statistical problems of the signal, an analytical pileup correction method using duration variable given by our spectrometry system (Adonis) and a nonparametric Bayesian inference for photopeack deconvolution will be used.

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تاریخ انتشار 2012