DOI QR코드

DOI QR Code

The development of EASI-based multi-path analysis code for nuclear security system with variability extension

  • Andiwijayakusuma, Dinan (Department of Physics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung) ;
  • Setiadipura, Topan (Research Center for Nuclear Reactor Technology, Research Organization on Nuclear Energy, National Research and Innovation Agency of the Republic of Indonesia (ORTN-BRIN)) ;
  • Purqon, Acep (Earth Physics and Complex System Research Division, Department of Physics, Bandung Institute of Technology Gedung Fisika) ;
  • Su'ud, Zaki (Nuclear Physics and Bio Physics Research Division, Department of Physics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung)
  • 투고 : 2021.07.25
  • 심사 : 2022.05.21
  • 발행 : 2022.10.25

초록

The Physical Protection System (PPS) plays an important role and must effectively deal with various adversary attacks in nuclear security. In specific single adversary path scenarios, we can calculate the PPS effectiveness by EASI (Estimated Adversary Sequence Interruption) through Probability of Interruption (PI) calculation. EASI uses a single value of the probability of detection (PD) and the probability of alarm communications (PC) in the PPS. In this study, we develop a multi-path analysis code based on EASI to evaluate the effectiveness of PPS. Our quantification method for PI considers the variability and uncertainty of PD and PC value by Monte Carlo simulation. We converted the 2-D scheme of the nuclear facility into an Adversary Sequence Diagram (ASD). We used ASD to find the adversary path with the lowest probability of interruption as the most vulnerable paths (MVP). We examined a hypothetical facility (Hypothetical National Nuclear Research Facility - HNNRF) to confirm our code compared with EASI. The results show that implementing the variability extension can estimate the PI value and its associated uncertainty. The multi-path analysis code allows the analyst to make it easier to assess PPS with more extensive facilities with more complex adversary paths. However, the variability of the PD value in each protection element allows a significant decrease in the PI value. The possibility of this decrease needs to be an important concern for PPS designers to determine the PD value correctly or set a higher standard for PPS performance that remains reliable.

키워드

과제정보

This work has been carried out under the SAINTEK scholarships program supported by National Research and Innovation Agency of the Republic of Indonesia (BRIN).

참고문헌

  1. N.I. Zakariya, M.T.E. Kahn, Safety, security and safeguard, Ann. Nucl. Energy 75 (2015) 292-302, https://doi.org/10.1016/j.anucene.2014.08.051.
  2. D. Schriefer, Safeguards, security, safety and the nuclear fuel cycle, Nucl. Fuel Cycle Sci. Eng. (2012) 52-79, https://doi.org/10.1533/9780857096388.1.52.
  3. International-Atomic-Energy-Agency, Nuclear security recommendations on nuclear and other radioactive material out of regulatory control IAEA. Nuclear Security Series No. 15 Nuclear security recommendations on radioactive material and associatedfacilities IAEA. www.iaea.org/books, 2011.
  4. H.A. Bennett, "Easi" - an evaluation method for physical security systems, Nucl. Mater. Manag. 6 (1977) 371-379.
  5. J.C. Matter, SAVI: Systematic Analysis of Vulnerability to Intrusion, 1988.
  6. J.C. Al-Ayat, R.A. Cousins, T.C. Matter, An overview of ASSESS-analytic system and software for evaluating safeguards and security, Orlando, FL, USA, in: Conf. 30. Annu. Meet. Inst. Nucl. Mater. Manag., 1989, pp. 9-12. Jul 1989.
  7. J.S. Sung, K. Sung-Woo, Y. Hosik, K. Jung-Soo, Y.K. Wan, Development of a vulnerability assessment code for a physical protection system: systematic analysis of physical protection Effectiveness (SAPE), Nucl. Eng. Technol. 41 (2009) 747-752. https://doi.org/10.5516/NET.2009.41.5.747
  8. B. Zou, M. Yang, J. Guo, E.R. Benjamin, W. Wu, A heuristic approach for the evaluation of Physical Protection System effectiveness, Ann. Nucl. Energy 105 (2017) 302-310, https://doi.org/10.1016/j.anucene.2017.03.029.
  9. B. Zou, M. Yang, Y. Zhang, E.R. Benjamin, K. Tan, W. Wu, H. Yoshikawa, Evaluation of vulnerable path: using heuristic path-finding algorithm in physical protection system of nuclear power plant, Int. J. Crit. Infrastruct. Prot. 23 (2018) 90-99, https://doi.org/10.1016/j.ijcip.2018.08.006.
  10. Z. Bowen, L. Jian, W. Wenlin, Y. Zhenyu, L. Gaojun, Y. Jun, Y. Ming, Development of an interaction simulator for the scenario analysis of physical protection systems, IEEE Access 7 (2019) 91509e91517, https://doi.org/10.1109/ACCESS.2019.2924239.
  11. Y.A. Setiawan, S.S. Chirayath, E.D. Kitcher, MAPPS: a stochastic computational tool for multi-path analysis of physical protection systems, Ann. Nucl. Energy (2019), 107074, https://doi.org/10.1016/j.anucene.2019.107074.
  12. Sandia-National-Laboratory(SNL), Hypothetical Facility Exercise Data: the Lone Pine Nuclear Power Plant, The Twenty-Sixth International Training Course, Albuquerque, 2016.
  13. M.L. Garcia, Design and Evaluation of Physical Protection Systems, second ed., Butterworth-Heinemann, 2007 https://doi.org/10.1016/C2009-0-25612-1.
  14. N. Terao, M. Suzuki, A probabilistic extension of the EASI model, J. Phys. Secur. 7 (2014) 12-29.