SIMULATION MODEL OF A DIGITAL TWIN FOR AN NPP POWER UNIT TECHNOLOGICAL PROCESS

Kostiantyn Brovko; Pavlo Budanov; Oleh Velykohorskyi; Yuliia Oliinyk; Nataliia Vynokurova; Serhii Voitenko

doi:10.20535/kpisn.2026.2.352429

Vol. 143 · Issue 2 · 2026 Jun 29, 2026 Robotics, Automation and Control Systems

SIMULATION MODEL OF A DIGITAL TWIN FOR AN NPP POWER UNIT TECHNOLOGICAL PROCESS

Kostiantyn Brovko Corresponding V. N. Karazin Kharkiv National University Ukraine

Pavlo Budanov V. N. Karazin Kharkiv National University Ukraine

Oleh Velykohorskyi V. N. Karazin Kharkiv National University Ukraine

Yuliia Oliinyk V. N. Karazin Kharkiv National University Ukraine

Nataliia Vynokurova V. N. Karazin Kharkiv National University Ukraine

Serhii Voitenko V. N. Karazin Kharkiv National University Ukraine

Pages36-43 PublishedJun 29, 2026 LicenseOpen Access

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VOL 143 · ISS 2 · 2026 View issue

Abstract

Background. Modern nuclear power plant (NPP) units are characterised by high structural complexity, multi-level hierarchical Information and Control (I&C) systems, and a vast number of interconnected technological parameters. Existing digital twin models primarily focus on individual physical processes – such as neutron kinetics, thermal hydraulics, or protection logic – often overlooking the comprehensive structure of control systems. The lack of a formalised approach for real-time assessment of subsystems’ hierarchical integrity limits the early detection of pre-accident states and proactive safety management.

Objective. The paper aims to develop a simulation model of a digital twin for the NPP technological process based on a system-cluster approach. This method enables the assessment of the hierarchical, self-similar scaled structure of subsystems using fractal dimension as a quantitative metric.

Methods. The study utilises a system-cluster approach, decomposing the power unit into functional sub-clusters: power control, protection system, coolant parameter regulation, and emergency shutdown. The mathematical framework integrates neutron kinetics equations, thermal-hydraulic relations, and logical-dynamic algorithms. To quantify structural complexity, the information space coverage method was employed to calculate fractal dimensions. The digital twin was implemented as a hardware-and-software complex integrated with the I&C, incorporating modules for data acquisition, structural identification, and predictive analytics.

Results. Fractal dimension values were obtained for key subclusters of the power unit, reflecting their hierarchical complexity (notably, the maximum of 1.83 for the coolant control system and the minimum of 1.0 for the protection system). Normalised ranges of fractal dimension were determined as indicators of normal operation. Furthermore, a monitoring algorithm was developed to detect the loss of structural levels or subsystem degradation before functional failures manifest. Practical implementation demonstrated the feasibility of real-time structural diagnostics and adaptive response.

Conclusions. The proposed fractal-cluster approach ensures comprehensive modelling of the NPP technological process by accounting for its hierarchical structure. Utilising fractal dimension as a structural diagnostic parameter expands the capabilities of traditional control methods and establishes the necessary framework for proactive safety management strategies based on digital twin technology.

Keywords

#digital twin #power unit #fractal dimension #system-cluster approach #information and management system

References

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Y. Weng, H. Wang, H. Wang, J. Liu, J. Pan, and Z. Deng, “The thermal-fluid-solid coupling effect in nuclear reactor vessel with direct vessel injection,” Progress in Nuclear Energy, vol. 152, article 104364, 2022. Retrieved from: https://doi.org/10.1016/j.pnucene.2022.104364
K. Zhang et al., “Towards safe, efficient long-reach manipulation in nuclear decommissioning: A case study on fuel debris retrieval at Fukushima Daiichi,” Journal of Nuclear Science and Technology, vol. 62, no. 1, pp. 1–16, 2025. Retrieved from: https://doi.org/10.1080/01691864.2023.2169588
B. M. T. Costa Peluzo and E. Kraka, “Uranium: the nuclear fuel cycle and beyond,” International Journal of Molecular Sciences, vol. 23, no. 9, article 4655, 2022. Retrieved from: https://doi.org/10.3390/ijms23094655
B. Dechenaux, T. Delcambre, and E. Dumonteil, “Percolation properties of the neutron population in nuclear reactors,” Physical Review E, vol. 106, no. 6, article 064126, 2022. Retrieved from: https://asnr.hal.science/irsn-04122103/document
P. Budanov, I. Kyrysov, Y. Oliinyk, K. Brovko, and S. Zhukov, “Fractal approach for researching information emergency features of technological parameters,” International Journal of Computing, vol. 24, no. 1, pp. 171–177, 2025. Retrieved from: https://doi.org/10.47839/ijc.24.1.3889
P. Budanov, Y. Oliinyk, A. Cherniuk, and K. Brovko, “Dynamic fractal cluster model of informational space technological process of power station,” Lecture Notes on Data Engineering and Communications Technologies, vol. 221, pp. 141–155, 2024. Retrieved from: https://doi.org/10.1007/978-3-031-71801-4_11
Y. Jiang, D. Tang, H. Yuan, and Y. Zhang, “Eco-zoning management based on thresholds of NPP driving factors,” Frontiers in Forests and Global Change, vol. 8, article 1712019, 2025. Retrieved from: https://doi.org/10.3389/ffgc.2025.1712019
A. Ramezani, T. Nazari, and O. Noori-Kalkhoran, “A proposed improvement for the design of safety injection system in VVER-1000/V446 reactor,” Progress in Nuclear Energy, vol. 137, article 103767, 2021. Retrieved from: https://doi.org/10.1016/j.pnucene.2021.103767
K. Brovko, P. Budanov, N. Vinokurova, and O. Velykohorsky, “Development of an integrated digital twin model for efficient operation of nuclear power plant units,” Tekhnichna Inzheneriya, no. 2(96), pp. 58–67, 2025. Retrieved from: https://doi.org/10.26642/ten-2025-2(96)-58-67
K. Brovko, P. Budanov, O. Velykohorsky, and N. Vinokurova, “Providing quantitative assessment of quality of technological process control of a nuclear power unit using a digital twin,” Visnyk NTU “KhPI”. Series: New Solutions in Modern Technologies, no. 3(25), pp. 3–12, 2025. Retrieved from: https://doi.org/10.20998/2413-4295.2025.03.01
G. Espinosa-Paredes and C. A. Cruz-López, “A new compartmental fractional neutron point kinetic equations with different fractional orders,” Nuclear Engineering and Design, vol. 423, article 113184, 2024. Retrieved from: https://doi.org/10.1016/j.nucengdes.2024.113184
P. Budanov, K. Brovko, Melnykov, M. Yakymchuk, V. Kononov, I. Kyrysov, A. Nosyk, O. Karpenko, S. Kalnoy, and E. Khomiak, “Construction of an information model of the digital twin of the technological process in a power unit at a nuclear power plant,” Eastern-European Journal of Enterprise Technologies, vol. 4, no. 9(136), pp. 39–49, 2025. Retrieved from: https://doi.org/10.15587/1729-4061.2025.335712
S. Kordalivand, R. Akbari, and M. Abbasi, “Quantifying the impact of risk mitigation measures using SPAR-H and RCM approaches: Case study based on VVER-1000 systems,” Nuclear Engineering and Design, vol. 423, article 113174, 2024. Retrieved from: https://doi.org/10.1016/j.nucengdes.2024.113174

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§ 06 — Related

[1] S. M. Bigonah Ghalehsari, J. Wang, and T. Zhao, “A review of the evaluation, simulation, and control of the air conditioning system in a nuclear power plant,” Energies, vol. 18, no. 7, article 1719, 2025. Retrieved from: https://doi.org/10.36074/logos-01.03.2024.052

[2] M. Krecicki and D. Kotlyar, “Thermal hydraulic modeling of solid-fueled nuclear thermal propulsion reactors part II: Full-core coupled neutronic and thermal hydraulic analysis,” Annals of Nuclear Energy, vol. 179, article 109397, 2022. Retrieved from: https://doi.org/10.1016/j.anucene.2022.109397

[3] Y. Weng, H. Wang, H. Wang, J. Liu, J. Pan, and Z. Deng, “The thermal-fluid-solid coupling effect in nuclear reactor vessel with direct vessel injection,” Progress in Nuclear Energy, vol. 152, article 104364, 2022. Retrieved from: https://doi.org/10.1016/j.pnucene.2022.104364

[4] K. Zhang et al., “Towards safe, efficient long-reach manipulation in nuclear decommissioning: A case study on fuel debris retrieval at Fukushima Daiichi,” Journal of Nuclear Science and Technology, vol. 62, no. 1, pp. 1–16, 2025. Retrieved from: https://doi.org/10.1080/01691864.2023.2169588

[5] B. M. T. Costa Peluzo and E. Kraka, “Uranium: the nuclear fuel cycle and beyond,” International Journal of Molecular Sciences, vol. 23, no. 9, article 4655, 2022. Retrieved from: https://doi.org/10.3390/ijms23094655

[6] B. Dechenaux, T. Delcambre, and E. Dumonteil, “Percolation properties of the neutron population in nuclear reactors,” Physical Review E, vol. 106, no. 6, article 064126, 2022. Retrieved from: https://asnr.hal.science/irsn-04122103/document

[7] P. Budanov, I. Kyrysov, Y. Oliinyk, K. Brovko, and S. Zhukov, “Fractal approach for researching information emergency features of technological parameters,” International Journal of Computing, vol. 24, no. 1, pp. 171–177, 2025. Retrieved from: https://doi.org/10.47839/ijc.24.1.3889

[8] P. Budanov, Y. Oliinyk, A. Cherniuk, and K. Brovko, “Dynamic fractal cluster model of informational space technological process of power station,” Lecture Notes on Data Engineering and Communications Technologies, vol. 221, pp. 141–155, 2024. Retrieved from: https://doi.org/10.1007/978-3-031-71801-4_11

[9] Y. Jiang, D. Tang, H. Yuan, and Y. Zhang, “Eco-zoning management based on thresholds of NPP driving factors,” Frontiers in Forests and Global Change, vol. 8, article 1712019, 2025. Retrieved from: https://doi.org/10.3389/ffgc.2025.1712019

[10] A. Ramezani, T. Nazari, and O. Noori-Kalkhoran, “A proposed improvement for the design of safety injection system in VVER-1000/V446 reactor,” Progress in Nuclear Energy, vol. 137, article 103767, 2021. Retrieved from: https://doi.org/10.1016/j.pnucene.2021.103767

[11] K. Brovko, P. Budanov, N. Vinokurova, and O. Velykohorsky, “Development of an integrated digital twin model for efficient operation of nuclear power plant units,” Tekhnichna Inzheneriya, no. 2(96), pp. 58–67, 2025. Retrieved from: https://doi.org/10.26642/ten-2025-2(96)-58-67

[12] K. Brovko, P. Budanov, O. Velykohorsky, and N. Vinokurova, “Providing quantitative assessment of quality of technological process control of a nuclear power unit using a digital twin,” Visnyk NTU “KhPI”. Series: New Solutions in Modern Technologies, no. 3(25), pp. 3–12, 2025. Retrieved from: https://doi.org/10.20998/2413-4295.2025.03.01

[13] G. Espinosa-Paredes and C. A. Cruz-López, “A new compartmental fractional neutron point kinetic equations with different fractional orders,” Nuclear Engineering and Design, vol. 423, article 113184, 2024. Retrieved from: https://doi.org/10.1016/j.nucengdes.2024.113184

[14] P. Budanov, K. Brovko, Melnykov, M. Yakymchuk, V. Kononov, I. Kyrysov, A. Nosyk, O. Karpenko, S. Kalnoy, and E. Khomiak, “Construction of an information model of the digital twin of the technological process in a power unit at a nuclear power plant,” Eastern-European Journal of Enterprise Technologies, vol. 4, no. 9(136), pp. 39–49, 2025. Retrieved from: https://doi.org/10.15587/1729-4061.2025.335712

[15] S. Kordalivand, R. Akbari, and M. Abbasi, “Quantifying the impact of risk mitigation measures using SPAR-H and RCM approaches: Case study based on VVER-1000 systems,” Nuclear Engineering and Design, vol. 423, article 113174, 2024. Retrieved from: https://doi.org/10.1016/j.nucengdes.2024.113174

SIMULATION MODEL OF A DIGITAL TWIN FOR AN NPP POWER UNIT TECHNOLOGICAL PROCESS

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References

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