Multi-fragmental and Multi-phase Availability Models of the Safety-critical I&C Systems with Two-cascade Redundancy



Traditional availability, reliability, and safety models face the dimension problem due to a huge number of components in modern systems, motivating further research in this field. This paper focuses on multi-fragmental and multiphase models for availability and functional safety assessment of the information and control (I&C) systems with two-cascade redundancy considering design faults manifestation during operation. The methodology of the research is based on Markov and semi-Markov chains with the utilization of multi-phase modeling. Several multi-phase models are developed and investigated considering different conditions of operation and failures caused by version faults. The case study of the research is based on the analysis of safety-critical nuclear power plant I&C systems such as the reactor trip systems developed using the programmable platform RadICS.


FPGA-Based Safety Platform RadICS

IAEA Safety Standards Series No. SSG-2 (Rev. 1). Deterministic Safety Analysis for Nuclear Power Plants. 2019.

S.-M. Shin, S. H. Lee, S. K. Shin, I. Jang, and J. Park, “STPA-based hazard and importance analysis on NPP safety I&C systems focusing on human–system interactions,” Reliability Engineering & System Safety, vol. 213, p. 107698, 2021.

S. J. Lee et al., “Bayesian belief network model quantification using distribution-based node probability and experienced data updates for software reliability assessment,” IEEE Access, vol. 6, pp. 64556–64568, 2018.

M. R. Mamdikar, V. Kumar, and P. Singh, “Dynamic Reliability Analysis Framework Using Fault Tree and Dynamic Bayesian Network: A Case Study of NPP,” Nuclear Engineering and Technology, vol. 54, no. 4, pp. 1213–1220, 2022.

O. Illiashenko and E. Babeshko, “Choosing FMECA-based techniques and tools for safety analysis of Critical Systems,” Information & Security: An International Journal, vol. 28, pp. 275–285, 2012.

Z. Zeng, Y.-P. Fang, Q. Zhai, and S. Du, “A Markov reward process-based framework for resilience analysis of Multistate Energy Systems under the threat of extreme events,” Reliability Engineering & System Safety, vol. 209, p. 107443, 2021.

S. Kaalen, M. Nyberg, and C. Bondesson, “Tool-supported dependability analysis of Semi-Markov processes with application to autonomous driving,” 2019 4th International Conference on System Reliability and Safety (ICSRS), 2019.

F. Felgner and G. Frey, “Multi-phase Markov models for functional safety prediction: Efficient simulation of Markov models used for safety engineering and the online integration of individual systems’ diagnostic and maintenance history,” 2011 3rd International Workshop on Dependable Control of Discrete Systems, 2011.

K. Bobrovnikova, S. Lysenko, B. Savenko, P. Gaj, O. Savenko. Technique for IoT malware detection based on control flow graph analysis, Radioelectron. Comput. Syst. 2022, 1, pp. 141-153,

A. Avizienis, J.-C. Laprie, B. Randell and C. Landwehr, “Basic concepts and taxonomy of dependable and secure computing,” IEEE Transactions on Dependable and Secure Computing, vol. 1, no. 1, pp. 11-33, Jan.-March 2004, Trivedi 2017

K.S. Trivedi, A. Bobbio, “Reliability and Availability Engineering—Modeling, Analysis, and Applications;” Cambridge University Press: Cambridge, UK, 2017; pp. 1–730

L. Ozirkovskyy, B. Volochiy, O. Shkiliuk, M. Zmysnyi, P. Kazan, “Functional Safety Analysis of Safety-Critical System Using State Transition Diagram”, Radioelectron. Comput. Syst. 2022, 1, pp. 145–158,

V. Kovtun, I. Izonin, and M. Gregus, “The functional safety assessment of cyber-physical system operation process described by Markov chain”, Sci Rep 12, 7089 (2022).

A. Farahani, A. Shoja, and H. Tohidi, “Markov and semi-Markov models in system reliability,” in Engineering Reliability and Risk Assessment, Elsevier, 2023, pp. 91-130,

V. Kharchenko, Y. Ponochovnyi, E. Ruchkov, and E. Babeshko, “Safety Assessment of the two-cascade redundant information and control systems considering faults of versions and supervision means,” New Advances in Dependability of Networks and Systems, pp. 88–98, 2022.

V. Kharchenko, Y. Ponochovnyi, I. Babeshko, E. Ruchkov, and A. Panarin, “Safety assessment of maintained control systems with Cascade Two-version 2oo3/1oo2 structures considering version faults,” Lecture Notes in Networks and Systems, pp. 119–129, 2023.

V. Kharchenko, Y. Ponochovnyi, O. Ivanchenko, H. Fesenko, and O. Illiashenko, “Combining markov and semi-markov modeling for assessing availability and cybersecurity of Cloud and IOT Systems,” Cryptography, vol. 6, no. 3, p. 44, 2022.






Security, Safety, Military