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Viktoriia Biliaieva
Larysa Levchenko
Iryna Myshchenko
Oksana Tykhenko
Vitalii Kozachyna


Despite the fact that much attention is paid to the safe operation of nuclear power plants, there is a possibility of an accident with the release of radionuclides. This is especially true in Ukraine, where there is a threat of the damage to nuclear reactors as a result of military operations. It is impossible to research the distribution of products emergency releases radioactive substances in laboratory conditions. Therefore, the only tool for the development predicting of an accident is the modeling the spread of a radionuclides cloud. The purpose of the research is a modeling the distribution of emergency release products in a nuclear power plant unit, suitable for the operative assessment of a development an accident. Results of the research: The mathematical model of the distribution emission products of a nuclear power plant has been developed, which takes into account the value of the initial activity of emission products, the rate of the settling radioactive particles, the wind speed components, the intensity changes radionuclide emission over time. The technique for solving the boundary value problem of modeling in conditions of a complex shape of the computational domain, taking into account the presence of obstacles to the spread of emission products has been developed. The use of the velocity potential equation in evolutionary form allows us to speed up the calculation process. The chosen splitting scheme of an alternating-triangular method allows to find the speed potential according to the explicit form at each splitting step. This allowed software implementation of the CFD model. The visualized models of the emission cloud distribution allow to determine the radiation situation in any place of the emission product distribution zone. The developed model makes it possible to quickly predict the development of an accident in space and time, which makes it possible to take measures to protect people from exposure in the shortest possible time. Conclusions: The obtained emission cloud propagation models and their visualization make it possible to determine the state of environmental pollution under various initial conditions during the development of the accident.

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How to Cite
Biliaieva , V. ., Levchenko , L. ., Myshchenko , I. ., Tykhenko , O. ., & Kozachyna , V. . (2024). MODELING THE DISTRIBUTION OF EMERGENCY RELEASE PRODUCTS AT A NUCLEAR POWER PLANT UNIT. Advanced Information Systems, 8(2), 20–26.
Information systems modeling
Author Biographies

Viktoriia Biliaieva , Ukrainian State University of Science and Technologies, Dnipro

Doctor of Technical Sciences, Associate Professor, Professor of Department of Energy Systems and Energy Management

Larysa Levchenko , National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute», Kyiv

Doctor of Technical Sciences, Professor, Professor of Department Digital Technologies in Energy

Iryna Myshchenko , Wroclaw University of Science and Technology, Wroclaw

dr MHSc, Laboratory of Occupational Health and Safety, Faculty of Geoengineering, Mining and Geology

Oksana Tykhenko , National Aviation University, Kyiv

Doctor of Technical Sciences, Professor, Professor of Department of Ecology

Vitalii Kozachyna , Ukrainian State University of Science and Technologies, Dnipro

PhD, Associate Professor, Associate Professor of Department  of Hydraulics, Water Supply and Physics


Ravshanov, N., Narzullayeva, N. and Muradov, F. (2021), “Model and Numerical Algorithm for Monitoring and Forecasting Transfer and Diffusion of Active Aerosol Particles in the Atmosphere”, Int. Conf. on Inf. Science and Comm. Technologies: Applications, Trends and Opportunities, ICISCT 2021, doi:

Zhan, Dou, Zhe, Liu, Lili, Li, Hang, Zhou, Qianlin Wang, Jianwen, Zhang and Liangchao, Chen (2022), “Atmospheric dispersion prediction of accidental release: A review”, Emergency Management Science and Technology, vol. 2, no. 9, doi:

Yang, Zhiyi, Li, Fengchen and Chai, Guohan (2022), “Status and Perspective of China’s Nuclear Safety Philosophy and Requirements in the Post-Fukushima Era”, Frontiers in Energy Research, vol. 9, doi:

Hossny, K., Villanueva, W. and Wang, H.D. (2023), “Distinctive physical insights driven from machine learning modelling of nuclear power plant severe accident scenario propagation”, Scientific Reports, 13, Article number: 930, doi:

Voutilainen, M., Peltonen, T., Ukkonen, A., Mattila, A., Routamo, T., Muikku, M. and Vesterbacka, P. (2022), Potential consequences of hypothetical nuclear power plant accidents in Finland, STUK-A 268, 120 p., URL:

Shuliang, Zou, Na, Liu and Binhai, Huang (2021), “Study on Airborne Radionuclide Dispersion in Floating Nuclear Power Plant under the Loss-of-Coolant Accident”, Science and Technology of Nuclear Installations, article ID 1299821, doi:

Abe, T., Yoshimura, K. and Sanada, Y. (2021), “Temporal Change in Atmospheric Radiocesium during the First Seven Years after the Fukushima Dai-ich Nuclear Power Plant Accident”, Aerosol Air Qual. Res., vol. 21, iss. 7, 200636, doi:

Bohanec, M., Vrbanic, I., Basic, I., Debelak, K. and Strubelj, L. (2020), “A decision-support approach to severe accident management in nuclear power plants”, Journal of Decision Systems, vol. 29, iss. 1, pp. 438‒449, doi:

Levchenko, L., Biliaiev, M., Biliaieva V., Ausheva, N. and Tykhenko, O. (2023), Methodology for modeling the spread of radioactive substances in case of an emergency release at a nuclear power plant. Advanced Information Systems, vol. 7, no. 3, pp. 13–17, doi:

Dotsenko, N., Chumachenko, I., Galkin, A., Kuchuk, H. and Chumachenko, D. (2023), “Modeling the Transformation of Configuration Management Processes in a Multi-Project Environment”, Sustainability (Switzerland), vol. 15(19), 14308, doi:

de Sampaio, P.A.B., Junior, M.A.G., Lapa, C.M.F. (2008), “A CFD approach to the atmospheric dispersion of radionuclides in the vicinity of NPPs”, Nuclear Engineering and Design, vol. 238(1), pp. 250–273, doi:

Kovalenko, A. and Kuchuk, H. (2022), “Methods to Manage Data in Self-healing Systems”, Studies in Systems, Decision and Control, vol. 425, pp. 113–171, doi:

Shutovskyi, A.M. (2023), “Some applied aspects of the Dirac delta function”, Journal of Mathematical Sciences (United States), 276(5), pp. 685–694, doi:

Kuchuk, G.A., Akimova, Yu.A. and Klimenko, L.A. (2000), “Method of optimal allocation of relational tables”, Engineering Simulation, Vol. 17(5), pp. 681–689.

Malachivskyy, P.S., Melnychok, L.S., Pizyur, Y.V. (2023), “Chebyshev Approximation of a Multivariable Function with Reproducing the Values of the Function and Its Partial Derivatives”, Cybernetics and Systems Analysis, 59(4), pp. 660–671, doi:

Vasylkivskyi, I., Ishchenko, V., Kochan, O. and Ivakh, R. (2023), “Environmental Pollution from Nuclear Power Plants: Modelling for the Khmelnytskyi Nuclear Power Plant (Ukraine)”, Lecture Notes on Data Engineering and Communications Technologies, 181, pp. 815–826, doi: