PREDICTIVE ANALYTICS OF THE OBJECTS OF THE GAS DISTRIBUTION SYSTEM OF THE REPUBLIC OF BELARUS: CURRENT STATUS AND PROSPECTS

Article Sidebar

Abstract views: 26
PDF Downloads: 5
pdf (rus) (Русский)
Published: Nov 15, 2024
DOI: https://doi.org/10.52928/2070-1683-2024-38-3-12-18
Keywords:
engineering infrastructure, gas distribution system, predictive analytics, condition forecasting, software, big data, digital twin инженерная инфраструктура, газораспределительная система, предиктивная аналитика, прогнозирование состояния, программное обеспечение, большие данные, цифровой двойник
Issue
No. 3 (2024)
Section
Construction

Main Article Content

V. ROMANIUK
Belarusian National Technical University, Minsk
A. NIYAKOVSKII
Euphrosyne Polotskaya State University of Polotsk
https://orcid.org/0000-0001-5106-6278
N. STRUTSKY
Beltopgaz SPA, Minsk

Abstract

The article highlights the experience of creating, applying and developing a digital twin of the gas distribution system of the Republic of Belarus. The effect of using IT technologies in the field of gas supply as an integral part of the overall engineering infrastructure of the country is shown. The principles of the construction and functioning of the existing set of software tools that ensure the production activities of gas supply organizations and the management apparatus of GPO "Beltopgaz" are described. Scientific and methodological approaches to the creation of predictive analytics tools for objects of the gas distribution system of the Republic of Belarus are formulated.

Article Details

How to Cite
ROMANIUK, V., NIYAKOVSKII, A., & STRUTSKY, N. (2024). PREDICTIVE ANALYTICS OF THE OBJECTS OF THE GAS DISTRIBUTION SYSTEM OF THE REPUBLIC OF BELARUS: CURRENT STATUS AND PROSPECTS. Vestnik of Polotsk State University. Part F. Constructions. Applied Sciences, (3), 12-18. https://doi.org/10.52928/2070-1683-2024-38-3-12-18
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Author Biographies

V. ROMANIUK, Belarusian National Technical University, Minsk

д-р техн. наук, проф.

A. NIYAKOVSKII, Euphrosyne Polotskaya State University of Polotsk

канд. техн. наук, доц.

Crossref
Scopus
Google Scholar
Europe PMC

References

Roberty, E.A.M. (2021). Predictive Analytics Applications for Oil and Gas Processing Facilities. Massachusetts: MIT. URL: https://dspace.mit.edu/bitstream/handle/1721.1/140083/machadoroberty-emachado-sm-sdm-2021-thesis.pdf?sequence=1.

Welland, C. (2023). Predictive Analytics in 2024: Definition, Benefits, Use Cases and Tools. Medium. URL: https://medium.com/piexchange/predictive-analytics-3260e7fe4596.

Strutskii, N.V. & Vasil'ev, V.Yu. (2017). Edinaya avtomatizirovannaya sistema GPO «Beltopgaz». Ot idei k rezul'tatu. Energeticheskaya strategiya, 3(57), 52–54. (In Russ.).

Ryndina, S.V. (2023). Tekhnologii analiza bol'shikh dannykh (prodvinutyi uroven'): upravlenie i rukovodstvo dannymi, khranenie i obrabotka dannykh: ucheb.-metod. posobie. Penza: PGU. (In Russ.).

Strutskii, N.V., Morozov, S.I., Golubeva, O.V., Boslovyak, S.V. & Yanushonok, A.N. (2023). Printsipy postroeniya, vozmozhnosti i opyt aprobatsii programmnogo modulya «Gidravlicheskii (poverochnyi) raschet gazoprovodov» [Principles of construction, possibilities and experience of testing the software module "Hydraulic (verification) calculation of gas pipelines"]. Vestn. Polots. gos. un-ta. Ser. B, Promyshlennost'. Prikladnye nauki [Herald of Polotsk State University. Series B, Industry. Applied sciences], (2), 66–69. (In Russ, abstr. in Engl.). DOI: 10.52928/2070-1616-2023-48-2-66-69.

Grieves, M. & Vickers, J. (2017). Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems. In F.J. Kahlen (Eds.), S. Flumerfelt (Eds.), & A.C. Alves (Eds.) Transdisciplinary Perspectives on Complex Systems (85–113). Switzerland: Springer. DOI: 10.1007/978-3-319-38756-7_4.