| Issue |
E3S Web Conf.
Volume 417, 2023
III International Conference on Geotechnology, Mining and Rational Use of Natural Resources (GEOTECH-2023)
|
|
|---|---|---|
| Article Number | 03002 | |
| Number of page(s) | 10 | |
| Section | Energy Saving and Energy Efficiency of Mining Enterprises, Other Industries and Transport Infrastructure | |
| DOI | https://doi.org/10.1051/e3sconf/202341703002 | |
| Published online | 21 August 2023 | |
Assessment of natural and technogenic hazard at large hydraulic structures in the northern and arctic territories
1 Siberian Federal University, 79 Svobodny Pr., 660041 Krasnoyarsk, Russia
2 Emergency Forecasting Department, Main Directorate of the Ministry of Emergency Situations of Russia for the Krasnoyarsk Territory, 68 Mira Pr., Krasnoyarsk, Russia
* Corresponding author: yaroslav.grebnev@gmail.com
Hydroelectric power plants are an important source of electricity in the world, but at the same time they can face various emergency situations that can lead to significant economic and environmental consequences. Recently, neural networks have become an increasingly popular tool for modeling and predicting emergency situations at hydroelectric power plants. This article discusses approaches to assessing the consequences of possible accidents at northern hydraulic structures. To develop scenarios and models, the Toxy + risk software and analytical complex and recurrent neural networks developed in the python programming language were used in the work. Various scenarios for the development of emergency situations have been developed and an assessment of the risk of their occurrence has been made.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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