Библиографическое описание:Modeling The Assessment Of Technogenic Risks Impact At Arctic Enterprises : доклад, тезисы доклада / Y. V. Grebnev, A. K. Moskalev. - [S. l. : s. n.], 2021. - Текст : непосредственный // European Proceedings of Social and Behavioural Sciences EpSBS / II International Conference on Economic and Social Trends for Sustainability of Modern Society (2021 ; 19.05 - 21.05 ; Krasnoyarsk). - Krasnoyarsk, Russia : ISO LONDON LIMITED - European Publisher, 2021. - Volume 116. - P. 2641-2651. - ISBN 9781802961157, DOI 10.15405/epsbs.2021.09.02.294.
Аннотация:In the world, environmental priorities are becoming increasingly important, especially important for fragile ecosystems such as the Arctic. These territories require close attention, due to the increasing frequency of man-made accidents, the bottling of oil products. Tank farms, which in many ways have already exhausted their design resource, are becoming a zone of increased attention, but are still in operation. In order to reduce man-made risks caused by depressurization of tanks with oil products, it is necessary to organize continuous monitoring and forecasting of risks, assess possible consequences, organize preventive measures, and develop response plans in the event of emergencies. It is necessary to create complex security systems at an accelerated pace to prevent and eliminate the consequences of natural and man-made emergencies in the Arctic zone. The work solved the problem of modelling the development of events during emergency bottling of oil products at a tank farm in the Arctic zone of the Krasnoyarsk Territory. The assessment of the area of bottling of oil products into the reservoir has been carried out. Modelling of emergency situations was carried out using the “Toxy+” risk software product, and the neural network forecasting methodology using the neural network simulator “NeuroPro”, developed at the Institute of Computational Modelling of the Federal Research Center of the KSC SB RAS to estimate the bottling area until the moment of localization. Comparison of the analytical method for determining the area of the oil spill in a reservoir and the neural network method is made.
