FRUIT: An operational tool for multisphere neutron spectrometry in workplaces

Evolutionary Artificial Neural Networks in Neutron Spectrometry

“…As a result, there is an increasing demand in the field of radiation protection to quantify these various neutron fields and to determine the radiation doses involved (Mazrou et al, 2008). The dosimetry of neutron radiation is one of the most complicated tasks in radiation protection (Wielunski et al, 2008a), mainly because is a complex technique (Bedogni et al, 2007), and highly neutron energy dependent, and a precise knowledge on neutron spectrometry is highly essential for all dosimetry-related studies as well as many nuclear physics experiments. In consequence, it becomes necessary to develop additional measuring techniques to enhance the actual workers monitoring systems.…”

“…Among the many available neutron spectrometry techniques, the multisphere or Bonner sphere spectrometer (BSS) system is the most used for radiation protection purposes (El Messaoudi et al, 2004;Lacoste et al, 2004;Vylet, 2002), due to advantageous characteristics as wide energy range (from thermal to GeV neutrons), large variety of active or passive thermal sensors allowing adapting the sensitivity to the specific workplace, good photon discrimination and simple signal management. Disadvantages are the poor energy resolution, which does not allow appreciating fine structures as narrow peaks, the weight, and the need to sequentially irradiate the spheres, requiring, in general, long exposure periods (Bedogni et al, 2007). The BSS consists of a thermal neutron sensor such as 6 LiI(Eu), which is placed at the centre of a number of moderating spheres of different diameter.…”

“…The procedure of selecting the solution that has meaning for the problem type, is part of the unfolding process (Vega-Carrillo et al, 2005;2006). The spectral information needs to be unfolded from the BSS system detector responses by using a suitable computational code, most of them are based in some of these methods: least square, iterative (Bedogni et al, 2007;Miller, 1993), bayesian and maximum entropy (Reginatto & Zimbal, 2008), and Monte-Carlo (Vega-Carrillo et al, 2007a). The current interest in the neutron spectrometry problem, has stimulated the development of diverse unfolding procedures which try to obtain a better energy resolution through the reconstruction of the spectrum.…”

“…The current interest in the neutron spectrometry problem, has stimulated the development of diverse unfolding procedures which try to obtain a better energy resolution through the reconstruction of the spectrum. During the past decades have been carried out intents to develop new neutron spectra unfolding codes like BUNKIUT (Miller, 1993), FRUIT (Bedogni et al, 2007), MAXED, UMG (Roberts, 2007), etc., to attain improved energy resolution through spectrum unfolding. However, these methods still present the serious drawback of requiring a very expert user for their operation and the necessity to provide an initial guess spectrum for the deconvolution of the spectrum.…”

“…For the anterior, the nuclear research community needs approaches that implement ANN models faster than what is currently available. In consequence, more research has been suggested in order to overcome these drawbacks (Bedogni et al, 2007;Vega-Carrillo et al, 2007b;2006;2010). At present, one promising technique to design the structural and learning parameters of ANN is by introducing adaptation of network training using EA.…”