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  • Особенности процесса поиска и внедрения новых технологических решений по выводу из эксплуатации объектов ядерного наследия и обращению с образующимися при этом радиоактивными отходами
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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Особенности процесса поиска и внедрения новых технологических решений по выводу из эксплуатации объектов ядерного наследия и обращению с образующимися при этом радиоактивными отходами

Радиоактивные отходы. 2022. № 4 (21). С. 90–102.
Тихонова А. А., Самойлов А. А., Ильина О. А., Иванов А. Ю., Белоусов С. В., Сергунин А. П., Stupin R., Grebneva A.

Effective decommissioning of nuclear legacy facilities depends directly on the applied engineering methods providing decontamination, dismantlement and RW management. The effectiveness of widely known and commonly applied methods cannot be seen as a constant value since it is governed by multiple factors, including the specific characteristics of the considered facilities. Pre-decommissioning stage should also consider some alternative techniques, methods, types of equipment and tooling, including those that are currently used outside the scope of nuclear industry.

To increase the decommissioning performance, including the efforts implemented under the Federal Target Program Nuclear and Radiation Safety in 2016—2035, on the one hand, some digital and calculation tools providing variant- based evaluation of different alternative options and supporting the selection of an optimal one may be used, and on the other hand — some tools helping to search for and implement more advanced decommissioning and RW management technologies may be developed.

The paper summarizes the assessment of nuclear decommissioning technologies and equipment applied in Russia and abroad showing certain potential for further industrial development. It also considers the scouting results focused on developments, prototypes, technologies and equipment associated with the areas of further industrial development providing opportunities for an increased performance during the implementation of key decommissioning operations.

Research target: Computer Science Electronics and Electrical Engineering Materials Technologies
Language: Russian
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Keywords: робототехникаинформационное моделированиетехнологии информационного моделированиярадиоактивные отходыradioactive wasteцифровой двойникdigital twinsbuilding information modelingdecommissioningradioactive waste managementвывод из эксплуатации
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