Nuclear Physics and Atomic Energy

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Nuclear Physics and Atomic Energy

  ISSN: 1818-331X (Print), 2074-0565 (Online)
  Publisher: Institute for Nuclear Research of the National Academy of Sciences of Ukraine
  Languages: Ukrainian, English
  Periodicity: 4 times per year

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Nucl. Phys. At. Energy 2014, volume 15, issue 2, pages 132-139.
Section: Atomic Energy.
Received: 12.03.2014; Published online: 30.06.2014.
PDF Full text (ru)
https://doi.org/10.15407/jnpae2014.02.132

On accuracy of the parameter of deep subcriticality determination by the Feynman method

V. M. Pavlovych1,2, O. V. Pidnebesnyy2

1Institute for Nuclear Research, National Academy of Sciences of Ukraine, Kyiv, Ukraine
2Institute for Safety Problems of Nuclear Power Plants, National Academy of Sciences of Ukraine, Chornobyl, Ukraine

Abstract: This paper considers the application of the Feynman method of neutron noise analysis for determination of the deep subcriticality parameters for multiplying systems. In particular, it is shown that the selection of the width of the timeslots, for which the mean and variance of the number of the neutron detector counts should be determined, can significantly affect the accuracy of determination of prompt neutron decay constant (α), especially in case of deep subcriticality. Analysis is based on the Monte Carlo method of calculation (code MCNP) of the simple multiplying systems with different neutron multiplication factors. Simple method is proposed for determination of the optimum width of the timeslot, from the standpoint of α calculation increasing accuracy, near which it is advisable to build the experimental dependence of the dispersion to mean ratio for the determination of α. It is also shown that bias estimates of α is determined not only by the finite sampling data, but also by the overlapping of neutron chains. That is, the intensity of the external neutron source must not exceed a certain value, which depends on the neutron multiplication factor.

Keywords: neutron noise, the Feynman method, constant Rossi-alpha, the Monte Carlo method.

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