Precise localization of neutron noise sources based on transport theory and comparison with diffusion theory. (February 2021)

• Record Type: Journal Article
• Authors: Bahrami, Mona; Vosoughi, Naser
• Is Part Of: Annals of nuclear energy. Volume 151(2021)
• Publication Date: 2021-02
• Subjects: Power reactor noise -- Unfolding -- Transport theory -- Sn Method -- Inversion method -- Scanning method; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; 621.4805
• DOI: 10.1016/j.anucene.2020.107981
• Languages: English
• ISSNs: 0306-4549

Abstract

Highlights: Transport Green function data is used for localization of a noise source. Comparative study between inverse Green's function based on SN transport and diffusion is performed. The impact of more accurate Green's function on the validation of the source localization is investigated. The sensitivity of the localization results to the position and the number of detectors is investigated. Abstract: In an attempt to explore the significance of transport theory in neutron noise, localization of a noise source by Green's function based on transport theory is investigated. There are considerable differences between Green's functions based on diffusion and transport, such as small dimensions, near edges, high heterogeneity medium and high-frequency source of perturbation. These differences are expected to significantly impact unfolding, reconstruction, and identification of the neutron noise source. Improvement in noise source unfolding methods is essential in terms of safety aspects and reactor performance enhancement. Since gaining the ability to monitor nuclear reactor based on noise diagnostics principle using few numbers of detectors is a challenging problem, more accurate methods of calculation of neutron noise can help reduce the detectors in number and sensitivity to location. This study revealed that inverse Green's function based on diffusion and transport is fundamentally different in concept. The inverse Green's function based on diffusion theory requires applying complicated reconstruction methods to gain more accurate results. This means that a large number of detectors must be used for noise source reconstruction. In contrast, in the case of inverse Green's function based on transport theory, each mesh's shape function is strongly correlated with the adjacent mesh. As a result, simple methods can be used to reconstruct the noise source. Therefore, the noise source can be identified and reconstructed with a smaller number of detectors in practical terms.