An area defuzzification technique to assess nuclear event reliability data from failure possibilities

International Journal of Computational Intelligence and Applications

Volumn 11, Issue 4, 2012, Pages

  Purba, Julwan Hendry ^a,d   Lu, Jie ^a   Zhang, Guangquan ^a   Ruan, Da ^b,c  

^a UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

^b BELGIAN NUCLEAR RESEARCH CENTRE   (Belgium)

^c GHENT UNIVERSITY   (Belgium)

^d NATIONAL NUCLEAR ENERGY AGENCY   (Indonesia)

Author keywords

Area defuzzification technique; Failure possibilities; Fuzzy failure rate; Nuclear event; Nuclear safety assessment; Reliability data

Indexed keywords

DEFUZZIFICATIONS; FAILURE POSSIBILITY; FAILURE RATE; NUCLEAR EVENT; NUCLEAR SAFETY; RELIABILITY DATA;

FAULT TREE ANALYSIS; FUZZY SETS; MEMBERSHIP FUNCTIONS; NUCLEAR POWER PLANTS; PRESSURIZED WATER REACTORS; SAFETY ENGINEERING;

RELIABILITY;

EID: 84873583695     PISSN: 14690268     EISSN: None     Source Type: Journal    
DOI: 10.1142/S1469026812500228     Document Type: Article

References (45)

1. H. Z. Huang, X. Tonga and M. J. Zuo, Posbist fault tree analysis of coherent systems, Reliab. Eng. Syst. Saf. 84 (2004) 141-148.
2. K. S. Chin, Y. M. Wang, G. K. K. Poon and J. B. Yang, Failure mode and e®ects analysis using a group-based evidential reasoning approach, Comput. Oper. Res. 36 (2009) 1768-1779.
3. L. Shu, J. Li and M. Qiu, Study on applying fault tree analysis based on fuzzy reasoning in risk analysis of construction quality, in Int. Conf. Risk Management & Engineering Management (Beijing, 2008), pp. 393-397.
4. H. Song, H. Y. Zhang and C. W. Chan, Fuzzy fault tree analysis based on t-s model with application to INS/GPS navigation system, Soft Comput. A Fusion of Foundations, Methodol. Appl. 13 (2009) 31-40.
5. K. Y. Cai, C. Y. Wen and M. L. Zhang, Fuzzy variables as a basis for a theory of fuzzy reliability in the possibility context, Fuzzy Sets Syst. 42 (1991) 145-172.
6. H. Z. Huang, M. J. Zuo and Z. Q. Sun, Bayesian reliability analysis for fuzzy lifetime data, Fuzzy Sets Syst. 157 (2006) 1674-1686.
7. T. Onisawa, An approach to human reliability in man-machine systems using error possibility, Fuzzy Sets Syst. 27 (1988) 87-103. (Pubitemid 18653043)
8. L. V. Utkin and S. V. Gurov, A general formal approach for fuzzy reliability analysis in the possibility context, Fuzzy Sets Syst. 83 (1996) 203-213. (Pubitemid 126667502)
9. L. A. Zadeh, Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets Syst. 1 (1978) 3-28.
10. L. A. Zadeh, Fuzzy sets, Inform. Control 8 (1965) 338-353.
11. A. H. Vencheh and M. Allame, On the relation between a fuzzy number and its centroid, Comput. Math. Appl. 59 (2010) 3578-3582.
12. L. B. Page and J. E. Perry, Standard deviation as an alternative to fuzziness in fault tree models, IEEE Trans. Reliab. 43 (1994) 402-407.
13. H. N. Cho, H. H. Choi and Y. B. Kim, A risk assessment methodology for incorporating uncertainties using fuzzy concepts, Reliab. Eng. Syst. Saf. 78 (2002) 173-183.
14. L. P. He, H. Z. Huang, L. Du, X. D. Zhang and Q. Miao, A review of possibilistic approaches to reliability analysis and optimization in engineering design, in Human- Computer Interaction: Hci Applications and Services, eds. J. A. Jacko (Springer-Verlag, Berlin Heidelberg, 2007), pp. 1075-1084.
15. IAEA, Component Reliability Data for Use in Probabilistic Safety Assessment, in IAEATECDOC- 478, IAEA, Editor. 1988, IAEA: Vienna.
16. R. Ferdous, F. Khan, R. Sadiq, P. Amyotte and B. Veitch, Fault and event tree analyses for process systems risk analysis: Uncertainty handling formulations, Risk Anal. 31 (2011) 86-107.
17. A. Mentes and I. H. Helvacioglu, An application of fuzzy fault tree analysis for spread mooring systems, Ocean Eng. 38 (2011) 285-294.
18. C. T. Lin and M. J. J. Wang, Hybrid fault tree analysis using fuzzy sets, Reliab. Eng. Syst. Saf. 58 (1997) 205-213.
19. D. Yuhua and Y. Datao, Estimation of failure probability of oil and gas transmission pipelines by fuzzy fault tree analysis, J. Loss Prev. Process Ind. 18 (2005) 83-88.
20. N. F. Pan, C. Tseng, F. C. Hadipriono and J. W. Duane, Assessing reliability of construction system using failure possibilities, in 4th Int. Conf. Engineering Computational Technology, Lisbon, 2004.
21. N. F. Pan and H. Wang, Assessing failure of bridge construction using fuzzy fault tree analysis, in IEEE Int. Conf. Fuzzy Systems and Knowledge Discovery, Haikou, 2007, Vol. 1, pp. 96-100. (Pubitemid 351710572)
22. N. F. Pan, Evaluation of building performance using fuzzy FTA, Constr. Manag. Econ. 24 (2006) 1241-1252.
23. S. Gupta and J. Bhattacharya, Reliability analysis of a conveyor system using hybrid data, Qual. Reliab. Eng. Int. 23 (2007) 867-882. (Pubitemid 350072700)
24. M. Celik, S. M. Lavasani and J. Wang, A risk-based modelling approach to enhance shipping accident investigation, Saf. Sci. 48 (2010) 18-27.
25. J. H. Purba, J. Lu, D. Ruan and G. Zhang, A hybrid approach for fault tree analysis combining probabilistic method with fuzzy numbers, in Artificial Intelligence and Soft Computing, eds. L. Rutkowski, R. Scherer, R. Tadeusiewicz, L. A. Zadeh and J. M. Zurada (Springer, Berlin/Heidelberg, 2010), pp. 194-201.
26. J. H. Purba, J. Lu, D. Ruan and G. Zhang, Probabilistic safety assessment in nuclear power plants by fuzzy numbers, in 9th Int. FLINS Conf., Chengdu, 2010, Vol. 4, pp. 256-262.
27. J. H. Purba, J. Lu, D. Ruan and G. Zhang, Failure possibilities for nuclear safety assessment by fault tree analysis, Int. J. Nucl. Knowl. Manag. 5 (2011) 162-177.
28. J. H. Purba, J. Lu, D. Ruan and G. Zhang, A failure possibility-based reliability algorithm for nuclear safety assessment by fault tree analysis, in 1st Int. Workshop on Safety & Security Risk Assessment and Organizational Cultures (SSRAOC2012), Antwerp, 2012.
29. D. Huang, T. Chen and M. J. J. Wang, A fuzzy set approach for event tree analysis, Fuzzy Sets Syst. 118 (2001) 153-165.
30. S. H. Chen, Ranking fuzzy numbers with maximizing set and minimizing set, Fuzzy Sets Syst. 17 (1985) 113-129.
31. Y. M. Wang, Centroid defuzzification and the maximizing set and minimizing set ranking based on alpha level sets, Comput. Ind. Eng. 57 (2009) 228-236.
32. S. Opricovic and G. H. Tzeng, Defuzzification within a multicriteria decision model, Int. J. Uncertainty Fuzziness Knowledge Based Syst. 11 (2003) 635-652.
33. N. Bose and N. S. Kumar, Prediction of emissions using combustion parameters in a diesel engine through fuzzy logic techniques, Int. J. Comput. Intell. Appl. 8 (2009) 195-207.
34. M. J. Watts, Fuzzy rule extraction from simple evolving connectionist systems, Int. J. Comput. Intell. Appl. 4 (2004) 299-308.
35. S. Das, S. Sural and A. K. Majumdar, Toward analyzing the impact of advertisement billboards on soccer telecast viewers, Int. J. Comput. Intell. Appl. 9 (2010) 241-269.
36. Y. J. Wang and H. S. Lee, The revised method of ranking fuzzy numbers with an area between the centroid and original points, Comput. Math. Appl. 55 (2008) 2033-2042.
37. T. C. Chu and C. T. Tsao, Ranking fuzzy numbers with an area between the centroid point and original point, Comput. Math. Appl. 43 (2002) 111-117.
38. C. Yuanyuan and J. Limin, Choquet integral-OWA based adaptive neural fuzzy inference system with application, Int. J. Comput. Intell. Appl. 10 (2011) 15-34.
39. H. Pan and C. H. Yeh, Fuzzy project scheduling, in 12th IEEE Int. Conf. Fuzzy Systems, Missouri, 2003, Vol. 1, pp. 755-760.
40. H. Pan and C. H. Yeh, A metaheuristic approach to fuzzy project scheduling, in Knowledge-Based Intelligent Information and Engineering Systems, eds. V. Palade, R. J. Howlett and L. C. Jain (Springer, Berlin/Heidelberg, 2003), pp. 1081-1087. (Pubitemid 37230790)
41. Y. M. Wang, J. B. Yang, D. L. Xu and K. S. Chin, On the centroids of fuzzy numbers, Fuzzy Sets Syst. 157 (2006) 919-926.
42. C. H. Cheng, A new approach for ranking fuzzy numbers by distance method, Fuzzy Sets Syst. 95 (1998) 307-317.
43. J. H. Purba, J. Lu and G. Zhang, An area defuzzification technique and essential fuzzy rules for defuzzifying nuclear event failure possibilities into reliability data, in 10th Int. FLINS Conf. (accepted), 2012.
44. O. Wolkenhauer, Fuzzy mathematics, in Data Engineering: Fuzzy Mathematics in Systems Theory and Data Analysis (John Wiley & Sons, Inc., 2001), pp. 197-212.
45. T. E. Wierman, S. T. Beck, M. B. Calley, S. A. Eide, C. D. Gentillon and W. E. Kohn, Reliability study: Babcock & wilcox reactor protection system, 1984-1998, in NUREG/ CR-5500, Vol. 11, 2001, Idaho Falls, Idaho.