Monitoring of the Efficiency of the IRT-T Reactor Heat Exchanger System by Machine Learning Method

This paper presents a study aimed at studying and evaluating the possibility of using machine learning in methods of predictive analysis of the operation of the cooling system of the IRT-T reactor. Machine learning is a subspecies of artificial intelligence used in large-volume data analytics. The c...

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Bibliographic Details
Published in:	Physics of particles and nuclei letters Vol. 21; no. 4; pp. 808 - 810
Main Authors:	Kublinskiy, M., Smolinkov, N., Naimushin, A.
Format:	Journal Article
Language:	English
Published:	Moscow Pleiades Publishing 2024 Springer Nature B.V
Subjects:	Artificial intelligence Computer Technologies in Physics Cooling systems Data analysis Data collection Data processing Heat exchangers Machine learning Parameters Particle and Nuclear Physics Physics Physics and Astronomy heat exchangers research reactor data analytics cooling system machine learning artificial intelligence
Online Access:	Get full text
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Summary:	This paper presents a study aimed at studying and evaluating the possibility of using machine learning in methods of predictive analysis of the operation of the cooling system of the IRT-T reactor. Machine learning is a subspecies of artificial intelligence used in large-volume data analytics. The currently existing methods of processing data on technological parameters are imperfect and do not allow predicting the development of operational events. The proposed approach will allow not only to centrally collect data on technological parameters, but also to output an analysis of possible outcomes and recommendations for changing operating modes.
ISSN:	1547-4771 1531-8567
DOI:	10.1134/S1547477124701413