Identification of Ways to Improve the Methods for Crushing and Sorting Irradiated Graphite from Nuclear Facilities

O. Yu. Dorman

Institute for Safety Problems of Nuclear Power Plants, NAS of Ukraine, 36a, Kirova St., Chornobyl, 07270, Ukraine

https://orcid.org/0009-0005-3894-7333

K. V. Simeiko

Institute for Safety Problems of Nuclear Power Plants, NAS of Ukraine, 36a, Kirova St., Chornobyl, 07270, Ukraine
Institute of Gas of the National Academy of Sciences of Ukraine, 39, Dehtiarivska St., Kyiv, 03113, Ukraine

https://orcid.org/0000-0002-1590-6281

DOI: doi.org/10.31717/2311-8253.26.1.6

Abstract

The article is devoted to the problem of handling irradiated graphite (IG) from nuclear installations (NI). Reactor graphite (or nuclear-grade graphite) has been used as a neutron moderator or reflector in more than 100 nuclear reactors and is a structural and functional material in Generation IV nuclear power systems, in particular in high-temperature gas-cooled reactors (HTGR, HTR, VHTR) and molten salt reactors (MSR). Therefore, the problem of handling IG from nuclear power plants is a pressing scientific issue. For some possible options for the utilization of IG, in particular, incineration, burial, and treatment with ion exchange resins, the issue of crushing and sorting IG is relevant. Based on the analysis of the physical properties of graphite after long-term exposure to high temperatures and neutron irradiation, the authors propose ways to improve the methods of IG crushing and sorting using artificial intelligence (AI). The article describes a method for crushing IG using a ball mill with discharge through a grid and a developed algorithm for separating IG using AI, which includes processing and control cycles using neural networks. Future improvements in the use of a ball mill with discharge through a grid and the separation algorithm should be aimed at reducing energy consumption and adapting to remote control conditions.

Keywords: nuclear energy, decommissioning of nuclear power plants, radioactive waste, irradiated graphite, artificial intelligence

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