Nuclear Engineering and Technology

  • 제56권5호
  • /
  • Pages.1603-1618
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  • 2024
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  • 1738-5733(pISSN)
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  • 2234-358X(eISSN)
한국원자력학회 (Korean Nuclear Society)
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A flow-directed minimal path sets method for success path planning and performance analysis

  • Zhanyu He (School of Electric Power Engineering, South China University of Technology) ;
  • Jun Yang (School of Electric Power Engineering, South China University of Technology) ;
  • Yueming Hong (School of Electric Power Engineering, South China University of Technology)
  • 투고 : 2023.08.10
  • 심사 : 2023.12.02
  • 발행 : 2024.05.25
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⟨ 이전 논문 다음 논문 ⟩

초록

Emergency operation plans are indispensable elements for effective process safety management especially when unanticipated events occur under extreme situations. In the paper, a synthesis framework is proposed for the integration success path planning and performance analysis. Within the synthesis framework, success path planning is implemented through flow-directed signal tracing, renaming and reconstruction from a complete collection of Minimal Path Sets (MPSs) that are obtained using graph traversal search on GO-FLOW model diagram. The performance of success paths is then evaluated and prioritized according to the task complexity and probability calculation of MPSs for optimum action plans identification. Finally, an Auxiliary Feed Water System of Pressurized Water Reactor (PWR-AFWS) is taken as an example system to demonstrate the flow-directed MPSs search method for success path planning and performance analysis. It is concluded that the synthesis framework is capable of providing procedural guidance for emergency response and safety management with optimal success path planning under extreme situations.

키워드

과제정보

The authors would like to thank the reviewers for their valuable comments and suggestions that helped improve the quality of this manuscript.

참고문헌

  1. F. Khan, S. Rathnayaka, S. Ahmed, Methods and models in process safety and risk management: past, present and future, Process Saf. Environ. Protect. 98 (2015) 116-147.  https://doi.org/10.1016/j.psep.2015.07.005
  2. E. Zarei, F. Khan, R. Abbassi, A dynamic human-factor risk model to analyze safety in sociotechnical systems, Process Saf. Environ. Protect. 164 (2022) 479-498.  https://doi.org/10.1016/j.psep.2022.06.040
  3. X.C. Xie, D.Y. Guo, Human factors risk assessment and management: process safety in engineering, Process Saf. Environ. Protect. 113 (2018) 467-482.  https://doi.org/10.1016/j.psep.2017.11.018
  4. National Research Council, Lessons Learned from the Fukushima Nuclear Accident for Improving Safety of U.S. Nuclear Plants, The National Academies Press, 2014. 
  5. Center for Chemical Process Safety, Emergency Planning: Preparedness, Prevention and Response, first ed., Wiley-AIChE, 2005. 
  6. L. Ding, F. Khan, J. Ji, Risk-based safety measure allocation to prevent and mitigate storage fire hazards, Process Saf. Environ. Protect. 135 (2020) 282-293.  https://doi.org/10.1016/j.psep.2020.01.008
  7. T. Dalijono, K. Lowe, H.J. Hoher, Development and verification of a new approach for operator action analysis, Process Saf. Environ. Protect. 83 (4) (2005) 331-337.  https://doi.org/10.1205/psep.05018
  8. D.Y. Ru, H.Y. Wen, Y.T. Zhang, A pre-generation of emergency reference plan model of public health emergencies with case-based reasoning, Risk Manag. Healthc. Pol. 15 (2022) 2371-2388.  https://doi.org/10.2147/RMHP.S385967
  9. Nuclear Energy Institute, Emergency Response Procedures and Guidelines for beyond Design Basis Events and Severe Accidents, 2016. NEI14-01. 
  10. The Federal Emergency Management Agency, Guide for all-hazard emergency operations planning, State and Local Guide (SLG) 101 (1996). 
  11. B. Hanna, T.C. Son, N. Dinh, AI-guided reasoning-based operator support system for the nuclear power plant management, Ann. Nucl. Energy 154 (108079) (2021) 1-15.  https://doi.org/10.1016/j.anucene.2020.108079
  12. R.H. Fusillo, G.J. Powers, A synthesis method for chemical plant operating procedures, Comput. Chem. Eng. 11 (4) (1987) 369-382.  https://doi.org/10.1016/0098-1354(87)85018-4
  13. R. Batres, Generation of operating procedures for a mixing tank with a micro generic algorithm, Comput. Chem. Eng. 57 (2013) 112-121.  https://doi.org/10.1016/j.compchemeng.2013.04.016
  14. R. Batres, Simulation-based planning of shutdown operations, Proc. Comput. Sci. 22 (2013) 1294-1302.  https://doi.org/10.1016/j.procs.2013.09.217
  15. M.L. Yeh, C.T. Chang, An automata based method for online synthesis of emergency response procedures in batch processes, Comput. Chem. Eng. 38 (2012) 151-170.  https://doi.org/10.1016/j.compchemeng.2011.11.008
  16. Y.F. Wang, H.H. Chou, C.T. Chang, Generation of batch operating procedures for multiple material-transfer tasks with Petri nets, Comput. Chem. Eng. 29 (2004) 1822-1836.  https://doi.org/10.1016/j.compchemeng.2005.03.001
  17. C.T. Chang, H.Y. Lee, V.S.K. Adi, Petri net-based operating procedures, in: Process Plant Operating Procedures. Advances in Industrial Control, Springer, Cham, 2021. 
  18. K. Hoshi, K. Nagasawa, Y. Yamashita, et al., Automatic generation of operating procedures for batch production plants by using graph representations, J. Chem. Eng. Jpn. 35 (4) (2002) 377-383.  https://doi.org/10.1252/jcej.35.377
  19. Y. Liu, Z.P. Fan, Y. Yuan, et al., A FTA-based method for risk decision-making in emergency response, Comput. Oper. Res. 42 (2014) 49-57.  https://doi.org/10.1016/j.cor.2012.08.015
  20. G.S. Saini, P. Pournazari, P. Ashok, et al., Intelligent action planning for well construction operations demonstrated for hole cleaning optimization and automation, Energies 15 (15) (2022) 5749. 
  21. M.C. Darling, G.F. Luger, T.B. Jones, et al., Intelligent modeling for nuclear power plant accident management, Int. J. Artif. Intell. Tool. 27 (2) (2018) 1-22.  https://doi.org/10.1142/S0218213018500033
  22. E. Waller, G. Bereznai, J. Shaw, et al., A simulator-based nuclear reactor emergency response training exercise, J.Emerg. Manag. 15 (6) (2017) 367-378.  https://doi.org/10.5055/jem.2017.0345
  23. N. Vaez, F. Nourai, RANDAP: an integrated framework for reliability analysis of detailed action plans of combined automatic-operator emergency response taking into account control room operator errors, J. Loss Prev. Process. Ind. 26 (6) (2013) 1366-1379.  https://doi.org/10.1016/j.jlp.2013.08.011
  24. F. Psarommatis, D. Kiritsis, A hybrid decision support system for automating decision making in the event of defects in the era of zero defect manufacturing, J. Ind. Inform. Integrat. 26 (2022), 100263. 
  25. A. Gofuku, T. Inoue, T. Sugihara, A technique to generate plausible counter-operation procedures for an emergency situation based on a model expressing functions of components, J. Nucl. Sci. Technol. 54 (5) (2017) 578-588.  https://doi.org/10.1080/00223131.2017.1292966
  26. M.C. Song, A. Gofuku, M. Lind, Model-based and rule-based synthesis of operating procedures for planning severe accident management strategies, Prog. Nucl. Energy 123 (2020), 103318. 
  27. M.C. Song, M. Lind, J. Yang, et al. Fan, Y. Yuan, et al., Integrative decision support for accident emergency response by combining MFM and GO-FLOW, Process Saf. Environ. Protect. 155 (2021) 131-144.  https://doi.org/10.1016/j.psep.2021.09.015
  28. J. Yang, Y. Xue, X.Y. Dai, et al., An intelligent operational supervision system for operability and reliability analysis of operators manual actions in task implementation, Process Saf. Environ. Protect. 158 (2022) 340-359.  https://doi.org/10.1016/j.psep.2021.12.023
  29. X.Y. Dai, M. Yang, J.P. Wang, et al., An operation scheme generation method for nuclear power plant operation under the condition of no operating procedures guided, Electronics 12 (2023) 1836. 
  30. M. Ghallab, D. Nau, P. Traverso, Automated Planning-Theory and Practice, Elsevier, 2004. 
  31. R. Nourjou, H. Tatano, Search algorithm for optimal execution of incident commander guidance in macro action planning, Int. J. Intell. Syst. Technol. Appl. 14 (3/4) (2015) 354-384.  https://doi.org/10.1504/IJISTA.2015.074335
  32. C. Chen, Y.B. Yang, M.T. Wang, et al., Characterization and evolution of emergency scenarios using hybrid Petri net, Process Saf. Environ. Protect. 114 (2018) 133-142.  https://doi.org/10.1016/j.psep.2017.12.016
  33. A. Arora, H. Fiorino, D. Pellier, et al., A review of learning planning action models, Knowl. Eng. Rev. 33 (2018), e20. 
  34. S. Jabbar, External Memory Algorithms for State Space Exploration in Model Checking and Action Planning, Doktons der Naturwissenschaften, 2008. 
  35. S. Kubosawa, T. Onishi, Y. Tsuruoka, Computing operation procedures for chemical plants using whole-plant simulation models, Control Eng. Pract. 114 (2021), 104878. 
  36. M.C. Song, A. Gofuku, Planning of alternative countermeasures for a station blackout at a boiling water reactor using multilevel flow modeling, Nucl. Eng. Technol. 50 (2018) 542-552.  https://doi.org/10.1016/j.net.2018.03.004
  37. K. Khandelwal, D.P. Sharma, Hybrid reasoning model for strengthening the problem solving capability of expert systems, Int. J. Adv. Comput. Sci. Appl. 4 (10) (2013) 88-94.  https://doi.org/10.14569/IJACSA.2013.041014
  38. T. Matsuoka, M. Kobayashi, GO-FLOW: a new reliability analysis methodology, Nucl. Sci. Eng. 98 (1) (1988) 64-78.  https://doi.org/10.13182/NSE88-A23526
  39. T. Matsuoka, M. Kobayashi, K. Takemura, The GO-FLOW methodology: a reliability analysis of the emergency core cooling system of a marine reactor under accident conditions, Nucl. Technol. 84 (3) (1989) 285-295.  https://doi.org/10.13182/NT89-A34212
  40. J.K. Li, Y.Z. Lu, X.N. Liu, et al., Reliability analysis of cold-standby phased-mission system based on GO-FLOW methodology and the universal generating function, Reliab. Eng. Syst. Saf. 233 (2023), 109125. 
  41. T. Matsuoka, M. Kobayashi, The GO-FLOW reliability analysis methodology-analysis of common cause failures with uncertainty, Nucl. Eng. Des. 175 (3) (1997) 205-214.  https://doi.org/10.1016/S0029-5493(97)00038-1
  42. M. Hashim, H. Yoshikawa, T. Matsuoka, et al., Common cause failure analysis of PWR containment spray system by GO-FLOW methodology, Nucl. Eng. Des. 262 (2013) 350-357.  https://doi.org/10.1016/j.nucengdes.2013.04.028
  43. M. Hashim, H. Yoshikawa, T. Matsuoka, et al., Considerations of uncertainties in evaluating dynamic reliability by GO-FLOW methodology-example study of reliability monitor for PWR safety system in the risk monitor system, J. Nucl. Sci. Technol. 50 (7) (2013) 695-708.  https://doi.org/10.1080/00223131.2013.790304
  44. M. Hashim, H. Yoshikawa, T. Matsuoka, et al., Reliability analysis of phased mission systems by considering the concept of sensitivity analysis, uncertainty analysis and common cause failure analysis using the GO-FLOW methodology, Res. J. Appl. Sci. Eng. Technol. 5 (12) (2013) 3465-3474.  https://doi.org/10.19026/rjaset.5.4594
  45. M. Hashim, T. Matsuoka, M. Yang, Development of a reliability monitor for the safety related subsystem of a PWR considering the redundancy and maintenance of components by fault tree and GO-FLOW methodologies, Int. Electron.J.Nuclear Saf. Simulat. ISSN 2185-0577, 3(2): 164-175.
  46. T. Matsuoka, Y. Kato, Modeling f a human performance by the GO-FLOW methodology, in: Proceedings of the 1st International Symposium on Socially and Technically Symbiotic Systems, Okayama, Japan, August 29-31, 2012. 
  47. H.X. Gu, G.J. Liu, J.X. Li, et al., A reliability-based mapping scheme for assessing system operational performance with erroneous human behavior at NPPs, IEEE Access 7 (2019) 123416-123429.  https://doi.org/10.1109/ACCESS.2019.2938024
  48. X.Y. Dai, M. Yang, J.P. Wang, et al., Methodology for updating GO-FLOW model to handle scenario changes in nuclear power plants, Front. Energy Res. 10 (2023), 1034845. 
  49. J. Yang, X.Y. Dai, W.Q. Chen, et al., A success-oriented analysis technique for operational risk supervision in sea-borne nuclear power plants, Nucl. Eng. Des. 340 (2018) 229-239.  https://doi.org/10.1016/j.nucengdes.2018.09.030
  50. H.X. Lu, M. Yang, X.Y. Dai, et al., Reliability modeling by extended GO-FLOW methodology for automatic control component and system at NPP, Nucl. Eng. Des. 342 (2019) 264-275.  https://doi.org/10.1016/j.nucengdes.2018.11.030
  51. T. Matsuoka, An exact method for solving logical loops in reliability analysis, Reliab. Eng. Syst. Saf. 94 (8) (2009) 1282-1288.  https://doi.org/10.1016/j.ress.2009.01.007
  52. T. Matsuoka, Reliability analysis of a BWR plant system at startup stage-analysis by the GO-FLOW methodology with consideration of loop structures and phased mission problem, Reliab. Eng. Syst. Saf. 233 (2023), 109086. 
  53. M. Hashim, H. Yoshikawa, T. Matsuoka, et al., Quantitative dynamic reliability evaluation of AP1000 passive safety systems by using FMEA and GO-FLOW methodology, J. Nucl. Sci. Technol. 51 (4) (2014) 526-542.  https://doi.org/10.1080/00223131.2014.881727
  54. F. Tao, D.G. Lu, T. Wakabayashi, Network Reliability Analysis of Digital Instrument and Control System with GO-FLOW Methodology, vol. 18, Transactions of Tianjin University, 2012, pp. 73-78. 
  55. M. Yang, W.L. Wang, J. Yang, et al., Development of a functional platform for system reliability monitoring of nuclear power plant, Nuclear Saf. Simulat. 5 (3) (2014) 177-185. 
  56. M. Hashim, H. Yoshikawa, M. Yang, et al., Development of reliability monitor by GO-FLOW methodology for the safety related sub-systems in PWR, Int. J. Nucl. Energy Sci. Technol. 8 (1) (2014) 21-36.  https://doi.org/10.1504/IJNEST.2014.057880
  57. J. Yang, M. Yang, H. Yoshikawa, et al., Development of a risk monitoring system for nuclear power plants based on GO-FLOW methodology, Nucl. Eng. Des. 278 (2014) 255-267.  https://doi.org/10.1016/j.nucengdes.2014.07.035
  58. J. Yang, M. Yang, H. Yoshikawa, et al., A method for developing Living PSA for NPPs by using the GO-FLOW methodology, Nuclear Saf. Simulat. 5 (1) (2014) 70-82. 
  59. H.X. Lu, M. Yang, Z.H. Xu, et al., Study on evidence-based LPSA method in nuclear power plant under abnormal operating conditions, Ann. Nucl. Energy 151 (107874) (2021) 1-17.  https://doi.org/10.1016/j.anucene.2020.107874
  60. J. Yang, M. Wang, D.Q. Guo, et al., Use of a success-oriented GO-FLOW method for system configuration risk management at NPPs, Ann. Nucl. Energy 143 (5) (2020), 107452. 
  61. J. Yang, M. Yang, W.L. Wang, Online application of a risk management system for risk assessment and monitoring at NPPs, Nucl. Eng. Des. 305 (2016) 200-212.  https://doi.org/10.1016/j.nucengdes.2016.05.025
  62. T. Matsuoka, GO-FLOW methodology-basic concept and integrated analysis framework for its applications, Int. J. Nuclear Saf. Simulat. 1 (3) (2013) 198-206. 
  63. T. Aldemir, Advanced Concepts in Nuclear Energy Risk Assessment and Management, World Scientific, 2018. 
  64. X. Ma, H.S. Gao, Cross-regional cold chain fresh product logistics network based on GO-FLOW analysis, Int. J. Metrol. Qual. Eng. 11 (7) (2020) 1-5.  https://doi.org/10.1051/ijmqe/2019016
  65. D.M. Fan, Z.L. Wang, L.L. Liu, et al., A modified GO-FLOW methodology with common cause failure based on discrete time Bayesian network, Nucl. Eng. Des. 305 (2016) 476-488.  https://doi.org/10.1016/j.nucengdes.2016.06.010
  66. M. Cunningham, B. Chen, D. Grabaskas, et al., Success Path Method: Definitions and Technical Requirements, ANE/ESIA-22/6, 2022. 
  67. D.J. Campbell, Task complexity: a review and analysis, Acad. Manag. Rev. 13 (1) (1988) 40-52.  https://doi.org/10.2307/258353
  68. P. Liu, Z.Z. Li, Comparison of task complexity measures for emergency operating procedures: convergent validity and predictive validity, Reliab. Eng. Syst. Saf. 121 (2014) 289-293.  https://doi.org/10.1016/j.ress.2013.09.006
  69. USNRC, Generic auxiliary feedwater system, Westinghouse Technol. Syst. Manual, Sect. 5.7 (2003). Revision 0603. 
  70. Z.Y. He, J. Yang, Y.Y. Chu, An automated GO-FLOW modeling tool for system reliability analysis, in: Proceedings of the 2023 30th International Conference on Nuclear Engineering (ICONE30), May 21-26, 2023. Kyoto, Japan. 
  71. J.B. Fussel, E.B. Henry, N.H. Marshall, MOCUS: a Computer Program to Obtain Minimal Sets from Fault Trees, ANCR-1156, 1974.