Russian Federation
Russian Federation
UDC 51
The combination of information and production risks and their aggregation in fire hazards have a destructive effect on the technosphere. Limited and unsystematic research in the field of formal description of models of information, functional, and fire safety at hazardous production facilities necessitates the development of a comprehensive mathematical model for the technosphere. Mathematical models based on Markov processes are considered, which are used to solve various problems related to emergencies at hazardous production facilities.
mathematical model, Markov model, information security, functional security, fire safety, hazardous production facility, technosphere
1. Baybutt P. Issues for security risk assessment in the process industries // J. Loss Prev. Process. Ind. 2017. № 49. P. 509–518.
2. A holistic framework for process safety and security analysis / Md T. Amin [et al.] // Comput. Chem. Eng. 2022. 2022. № 165.
3. Meyer T., Reniers G. Engineering risk management. Walter de Gruyter GmbH & Co KG, 2022.
4. Risk assessment methods for process safety, process security and resilience in the chemical process industry: A thorough literature review / M.Sh. Ab Rahim [et al.] // Journal of Loss Prevention in the Process Industries. 2024. Vol. 88. P. 105274. DOI:https://doi.org/10.1016/j.jlp.2024.105274. EDN IMLZLS.
5. O sostoyanii zashchity naseleniya i territorij Rossijskoj Federacii ot chrezvychajnyh situacij prirodnogo i tekhnogennogo haraktera v 2023 godu: gos. doklad. M., 2024.
6. Ivahnenko N.N. Osobennosti ocenki nadezhnosti tekhnicheskih sistem // Nauka i perspektivy. 2020. № 1. S. 56–67. EDN UOMLAV.
7. Tukmacheva M.A., Shestakov A.V. Model' svyaznosti informacionnoj, funkcional'noj i pozharnoj bezopasnosti opasnyh proizvodstvennyh ob"ektov // Nauch.-analit. zhurn. «Vestnik S.-Peterb. un-ta GPS MCHS Rossii». 2024. № 3. S. 98–126. DOI:https://doi.org/10.61260/2218-130X-2024-3-98-126. EDN ANQYHG.
8. Coupling of adjoint-based Markov/CCMT predictive analytics with data assimilation for real-time risk scenario forecasting of industrial digital process control systems / J. Chenyua [et al.] // Process Safety and Environmental Protection. 2023. Vol. 171. P. 951–974.
9. Bryan DFH, Ceng FIEE. Operation and Maintenance: Telecommunications Engineer's Reference. 1993.
10. Safety and risk analysis in digitalized process operations warning of possible deviating conditions in the process environment / C. Benson [et al.] // Process Safety and Environmental Protection. 2021 Vol. 149. P. 750–757.
11. Fire risk assessment for building operation and maintenance based on BIM technology / L. Wang [et al.] // Building and Environment. 2021. Vol. 205. P. 108188.
12. Androsenko O.S., Devyatchenko L.D., Mayachenko E.P. Postanovka i reshenie zadach Markovskih processov na EVM: metod. ukazaniya i varianty kontrol'nyh zadanij dlya studentov vsekh special'nostej. Magnitogorsk: GOU VPO «MGTU», 2007. 51 s.
13. Matveev A.V. Metody modelirovaniya i prognozirovaniya. SPb.: S.-Peterb. un-t GPS MCHS Rossii, 2022. 230 s. EDN IMLKWS.
14. Awad M., Khanna R. Hidden Markov Model. In: Efficient Learning Machines. Apress, Berkeley, CA, 2015.
15. Vodnev S.A., Maksimov A.V., Matveev A.V. Model' kompleksnoj ocenki processa tekhnicheskogo obespecheniya avarijno-spasatel'nyh sredstv podrazdelenij MCHS Rossii // Problemy upravleniya riskami v tekhnosfere. 2018. № 2 (46). S. 73–80. EDN YLLCZN.
