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Abstract <p>The paper presents a method for unfolding the neutron energy spectrum from the results of measurements with a Bonner multi-sphere spectrometer. The method is based on solving the system of the Fredholm integral equation of the 1st kind using the Tikhonov regularization and decomposing the spectrum into shifted Legendre polynomials. To obtain an optimal solution, an algorithm for selecting the regularization parameter and the number of polynomials is proposed. Spectra were reconstructed for rooms near the Intense Resonance Neutron Source (IREN) facility at JINR in the energy range from <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11497_2025_10063_Article_IEq1.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="33" /> </InlineMediaObject> <EquationSource Format="TEX">\({{10}^{{ - 8}}}\)</EquationSource> <!--PhysPNLt2470239Chizhov-m1--> </InlineEquation> to 63.1 MeV. The effective dose rate and ambient dose equivalent rate were estimated for the obtained spectra. Results are compared with the statistical regularization method (the ”Reconst” software).</p>

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Neutron Spectrum Unfolding Method Based on Shifted Legendre Polynomials, Its Application to the IREN Facility

  • 期刊论文

  • 发表日期：

    2025年4月1日

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  • K. Chizhov,
  • L. Beskrovnaya,
  • A. Chizhov

摘要

Abstract

The paper presents a method for unfolding the neutron energy spectrum from the results of measurements with a Bonner multi-sphere spectrometer. The method is based on solving the system of the Fredholm integral equation of the 1st kind using the Tikhonov regularization and decomposing the spectrum into shifted Legendre polynomials. To obtain an optimal solution, an algorithm for selecting the regularization parameter and the number of polynomials is proposed. Spectra were reconstructed for rooms near the Intense Resonance Neutron Source (IREN) facility at JINR in the energy range from \({{10}^{{ - 8}}}\) to 63.1 MeV. The effective dose rate and ambient dose equivalent rate were estimated for the obtained spectra. Results are compared with the statistical regularization method (the ”Reconst” software).