nucВестник НЯЦ РКNNC RK Bulletin1729-75161729-7885Национальный ядерный центр Республики Казахстан10.52676/1729-7885-2025-1-161-166nuc-803Research ArticleСтатьиМАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ ПРОЦЕССОВ КОНТРОЛЯ БЕЗОПАСНОСТИ НА АТОМНЫХ ЭЛЕКТРОСТАНЦИЯХMATHEMATICAL MODELING OF SAFETY CONTROL PROCESSES AT NUCLEAR POWER PLANTSЕлекеевЕ. М.YelekeyevY. М.

Астана

Astana

erbol.elekeev@mail.ruСтепановБ. П.StepanovB. P.

Томск

Tomsk

sbp@tpu.ruАО "Самрук-Казына"Казахстан«Samruk-Kazyna» JSCKazakhstanФГАОУ ВО «Национальный исследовательский Томский политехнический университет»РоссияFederal State Autonomous Educational Institution of Higher Education “National Research Tomsk Polytechnic University”Russian Federation20250104202501161166Copyright © Елекеев Е.М., Степанов Б.П., 20252025Елекеев Е.М., Степанов Б.П.Yelekeyev Y.М., Stepanov B.P.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://journals.nnc.kz/jour/article/view/803

В статье рассматривается использование математического моделирования для повышения безопасности атомных электростанций. Исследование показывает, что время реакции на аварийную ситуацию играет ключевую роль: если оператор принимает меры в течение 30 секунд, вероятность предотвращения аварии составляет 95%, но при задержке в 5 минут она падает до 30%. Также анализируется влияние профилактического обслуживания и резервирования оборудования. Без технического обслуживания вероятность отказа через 1000 часов эксплуатации достигает 40%, тогда как регулярные проверки снижают этот показатель до 15%, а резервные системы – до 8%. Дополнительно изучены каскадные отказы, которые могут привести к серьезным последствиям: при увеличении числа взаимозависимых компонентов с 3 до 10 риск полного отказа системы возрастает с 15% до 80%. В работе предлагаются практические рекомендации по повышению надежности АЭС, включая автоматизацию мониторинга, внедрение предиктивных алгоритмов и использование машинного обучения для прогнозирования возможных сбоев.

This paper examines the use of mathematical modeling to enhance the safety of nuclear power plants (NPPs). The study demonstrates that reaction time plays a crucial role in accident prevention: if an operator takes action within 30 seconds, the probability of preventing an accident is 95%, whereas a 5-minute delay reduces this probability to 30%. The impact of preventive maintenance and system redundancy on reliability is also analyzed. Without maintenance, the probability of equipment failure after 1000 hours of operation reaches 40%, whereas regular inspections reduce this to 15%, and redundancy further lowers it to 8%. Additionally, cascading failures were studied, showing that as the number of interdependent components increases from 3 to 10, the risk of total system failure rises from 15% to 80%. The paper provides practical recommendations for improving NPP reliability, including the automation of monitoring, the implementation of predictive algorithms, and the use of machine learning for failure forecasting.

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The authors declare that there are no conflicts of interest present.