Algorithm for Automating Input and Processing of Initial Data for Computer Forecasting of Spatial Migration of Radionuclides in Soils

P. K. Shalkevich () and A. O. Dalmatava

Digital Transformation, 2023, vol. 29, issue 3

Abstract: An important tool for solving problems associated with the migration of radionuclides is computer technology that makes it possible to predict the spread of radioactive contamination in soils, which are an important component of the biosphere. At the same time, most modern software for the prediction of the spread of radioactive contamination is based on idealizations that simplify the understanding of this process, while solving the problem of a comprehensive assessment of the biosphere requires the use of a full-fledged spatial model of radionuclide migration in soils. Such a model was developed by P. K. Shalkevich within SPS (Simulation of Processes in Soil) software. SPS uses the initial values of radionuclide concentrations, hydrological and thermal properties of soils and information about meteorological conditions as input data for forecasting. At the same time, the listed initial data must be previously collected, processed and converted into a form that the software able to work with. Such processes require significant intellectual and time costs. These costs negatively affect the possibility of generating operational forecasts of the radioactive situation, but can be significantly reduced by using systems for automated radiation monitoring of soils and automating input and processing of initial data when predicting the spatial migration of radionuclides in the appropriate software, what is considered in the present article.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:abx:journl:y:2023:id:777

DOI: 10.35596/1729-7648-2023-29-3-34-42

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