Izvestiya of Saratov University.

Mathematics. Mechanics. Informatics

ISSN 1816-9791 (Print)
ISSN 2541-9005 (Online)

For citation:

Rezchikov  . F., Kushnikov V. A., Ivashchenko V. A., Bogomolov A. S., Filimonyuk L. Y., Sholomov K. I. The Dynamical Cause-effect Links’ Presentation in Human-machine Systems. Izvestiya of Saratov University. Mathematics. Mechanics. Informatics, 2017, vol. 17, iss. 1, pp. 109-116. DOI: 10.18500/1816-9791-2017-17-1-109-116

This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
Published online: 
Full text:
(downloads: 81)

The Dynamical Cause-effect Links’ Presentation in Human-machine Systems

Rezchikov  Aleksandr Fedorovich, Institute of Precision Mechanics and Control, Russian Academy of Sciences
Kushnikov Vadim Alexeevich, Institute of Precision Mechanics and Control, Russian Academy of Sciences
Ivashchenko Vladimir Andreevich, Institute of Precision Mechanics and Control, Russian Academy of Sciences
Bogomolov Alexey Sergeevich, Saratov State University
Filimonyuk Leonid Yurievich, Institute of Precision Mechanics and Control, Russian Academy of Sciences
Sholomov Konstantin Igorevich, Institute of Precision Mechanics and Control, Russian Academy of Sciences

A method of presentation variable cause-effect links for modeling processes in dynamic systems is proposed. Such a representation corresponds to the changing conditions that are associated with the action of many diverse factors that accompany the functioning of complex human-machine systems. The presence or absence of a causal relationship between the individual events in the proposed model is defined as a result of a set of stochastic or deterministic functions. Trends in the representation of cause-effect links are achieved by formation of these relations on the basis of common values of variables that correspond to various events in the system. The existing software systems for the analysis of security of technological systems are rather limited in view of dynamics of cause-effect models. The representation under discussion is actual for modeling critical combinations of events leading to beyond design basis accidents. Dynamic cause-effect models make possible to determine time intervals when the system is most vulnerable to the emergence of critical combinations of events, to analyze the causes and ways to prevent such combinations. The proposed model is implemented in developed software that will be used for modeling and analysis of malfunctions in the functioning of man-machine, organizational and other dynamic systems with the help of using event trees.

  1. Bjorkman K. Digital Automation System Reliability Analysis — Literature survey. VTT, Resercher report VTT-R-08153-09. Available at: http://www.vtt.fi/inf/julkaisut/muut/2009/VTT-R-08153-09.pdf (accessed 15.06.2016).
  2. Viktorova V. S., Kuntsher Kh. P., Stepaniants A. S. Analiz programmnogo obespecheniia modelirovaniia nadezhnosti i bezopasnosti sistem [Analysis of simulation software reliability and security systems]. Dependability, 2006, no. 4(19), pp. 46–57 (in Russian).
  3. Strogonov A., Zhadnov V., Polesskii S. Obzor programmnykh kompleksov po raschetu nadezhnosti slozhnykh tekhnicheskikh sistem [Overview of software for analyzing the reliability of complex technical systems]. Components & Technologies, 2007, no. 5, pp. 183– 190 (in Russian).
  4. Bai X., Sun L. P., Sun H. Risk Assessment of Hoisting Aboard and Installation for Offshore Wind Turbine. ASME 2012 31st Intern. Conf. on Ocean, Offshore and Arctic Engineering, Vol. 2 : Structures, Safety and Reliability, pp. 107–114. DOI: https://doi.org/10.1115/OMAE2012-83187.
  5. Sharma P. K., Bhuvana V., Ramakrishnan M. Reliability analysis of Diesel Generator power supply system of Prototype Fast Breeder Reactor. Nuclear engineering and design, 2016, vol. 310, pp. 192–204. DOI: https://doi.org/10.1016/j.nucengdes.2016.10.013
  6. Chaari M., Ecker W., Kruse T., Novello C., Tabacaru B. A. Transformation of Failure Propagation Models into Fault Trees for Safety Evaluation Purposes. 46th Annual IEEE/IFIP Intern. Conf. on Dependable Systems and Networks Workshop (DSN-W), 2016, pp. 226– 229. DOI: https://doi.org/10.1109/DSN-W.2016.18
  7. Bogomolov A. S. Integrated resource control of complex man-machine system. Izv. Saratov Univ. (N. S.), Ser. Math. Mech. Inform., 2013, vol. 13, iss. 3, pp. 83–87 (in Russian).
  8. Kluev V. V., Rezchikov A. F., Bogomolov A. S., Koshevaya E. M., Ukov D. A. Causeconditional approach to resource management of furnace in cement production. Kontrol’. Diagnostika [Testing. Diagnostics], 2012, vol. 7, pp. 30–36 (in Russian).
  9. Rezchikov A., Bogomolov A., Ivaschenko V., Filimonyuk L. Applying automation models to support and maintein safety in complex systems. Large-scale Systems Control, 2015, vol. 54, pp. 179–194 (in Russian).
  10. Rezchikov A. F., Kushnikov V. A., Ivashchenko V. A., Bogomolov A. S., Filimonyuk L., Kachur K. P. Control of the air transportation system with flight safety as a criterion. Advances in Intelligent Systems and Computing, 2016, vol. 466, pp. 423–432.
  11. Novozhilov G. V., Rezchikov A. F., Neumark M. S., Bogomolov A. S., Tsesarskiy L. G., Filimonyuk L. Yu. Problem critical events in the combination “Crew — Aircraft — Manager” system. Polyot, 2015, vol. 2, pp. 10–16 (in Russian).
  12. Sholomov K. I. Complex events critical simulation and analysis programs based on combinations Therefore the structure and processing of dynamic causal trees. Proc. XXVIII Intern. Sci. Conf. on Mathematical Methods in Technics and Technologies — ММТТ-28, Saratov, Publ. Yuri Gagarin State Technical University of Saratov, 2015, pp. 300–304 (in Russian).
  13. Mozhaeva I. A., Nozik A. A., Strukov A. V., Chechulin A. A. Sovremennye tendentsii strukturno-logicheskogo analiza nadezhnosti i kiberbezopasnosti ASUTP [Current trends structural and logical analysis of reliability and cybersecurity PCS]. Modeling and Analysis of Safety and Risk in Complex Systems : Proc. Intern. Sci. School, St. Petersburg, Publ. Institute of Problems of Mechanical Engineering RAS, 2015, pp. 140–145 (in Russian). 
  14. Belova V. V., Filin V. M. Quantitative assessment of the reliability for the spacecraft thermal control system during electrical testing. Vestnik NPO im. S. A. Lavochkina, 2013, no. 3 (19), pp. 50–56 (in Russian).
  15. Belova V. V. Modelirovanie nadezhnosti sistemy obespecheniia teplovogo rezhima kosmicheskogo apparata [Simulation of the system to ensure the reliability of the thermal regime of the spacecraft]. Trudy Mezhdunarodnogo simpoziuma Nadezhnost’ i Кachestvo [Proc. Intern. Symposium "RELIABILITY and QUALITY"], 2013, vol. 1, pp. 148–154 (in Russian).
  16. Viktorova V. S., Stepanyants A. S. Multilevel modeling of system reliability. Datchiki & Systemi [Sensors & Systems], 2014. no. 6(181), pp. 33–37 (in Russian).
  17. Adamovich K. Yu. Matematicheskaia model’ dlia prognozirovaniia znachenii pokazatelei bezopasnosti transportnoi sistemy [Mathematical model to predict the safety performance values transport system]. Mathematical Methods in Technics and Technologies — ММТТ, Saratov, Publ. Yuri Gagarin State Technical University of Saratov, 2015, no. 6(76), pp. 146– 151 (in Russian).
  18. Lychkina N. N. Retrospectives and perspectives of system-dynamics. Analysis of dynamics of the sd development. Business Informatics, 2009, no. 3(9), pp. 55–67 (in Russian).
  19. Forrester J. World Dynamics. Moscow, Nauka, 1978. 168 p. (in Russian).
  20. Oliva R. Structural dominance analysis of large and stochastic models. System dynamics review, 2016, vol. 32, pp. 26–51. DOI: https://doi.org/10.1002/sdr.1549.