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NEW RESULTS TO BDD TRUNCATION METHOD FOR EFFICIENT TOP EVENT PROBABILITY CALCULATION

  • Mo, Yuchang (Department of Computer Science, Zhejiang Normal University) ;
  • Zhong, Farong (Department of Computer Science, Zhejiang Normal University) ;
  • Zhao, Xiangfu (Department of Computer Science, Zhejiang Normal University) ;
  • Yang, Quansheng (School of Computer Science and Engineering, Southeast University) ;
  • Cui, Gang (School of Computer Science and Technology, Harbin institute of technology)
  • Received : 2011.10.19
  • Accepted : 2012.02.08
  • Published : 2012.10.25

Abstract

A Binary Decision Diagram (BDD) is a graph-based data structure that calculates an exact top event probability (TEP). It has been a very difficult task to develop an efficient BDD algorithm that can solve a large problem since its memory consumption is very high. Recently, in order to solve a large reliability problem within limited computational resources, Jung presented an efficient method to maintain a small BDD size by a BDD truncation during a BDD calculation. In this paper, it is first identified that Jung's BDD truncation algorithm can be improved for a more practical use. Then, a more efficient truncation algorithm is proposed in this paper, which can generate truncated BDD with smaller size and approximate TEP with smaller truncation error. Empirical results showed this new algorithm uses slightly less running time and slightly more storage usage than Jung's algorithm. It was also found, that designing a truncation algorithm with ideal features for every possible fault tree is very difficult, if not impossible. The so-called ideal features of this paper would be that with the decrease of truncation limits, the size of truncated BDD converges to the size of exact BDD, but should never be larger than exact BDD.

Keywords

References

  1. B. Akers, "Binary Decision Diagrams," IEEE Transactions on Computers, C-27(6), pp. 509-516, 1978. https://doi.org/10.1109/TC.1978.1675141
  2. R. Bryant, "Graph Based Algorithms for Boolean Function Manipulation," IEEE Transactions on Computers, C- 35(8), pp. 677-691, 1986. https://doi.org/10.1109/TC.1986.1676819
  3. A. Rauzy, "New Algorithms for Fault Trees Analysis," Reliability Engineering and System Safety, 40, pp. 203- 211, 1993. https://doi.org/10.1016/0951-8320(93)90060-C
  4. ARALIA Group. "Computation of prime implicants of a fault tree within ARALIA". Proceedings of the ESREL'95, Bournemouth, UK, 1995.
  5. O. Coudert and J.C. Madre, "Fault Tree Analysis: 1020 Prime Implicants and Beyond," Proceedings of the Annual Reliability and Maintainability Symposium, Atlanta, NC, USA, January 1993.
  6. A. Rauzy and Y. Dutuit, "Exact and Truncated Computations of Prime Implicants of Coherent and Non-coherent Fault Trees Within Aralia," Reliability Engineering and System Safety, 58, pp. 127-144, 1997. https://doi.org/10.1016/S0951-8320(97)00034-3
  7. Y. Dutuit and A. Rauzy, "Efficient Algorithms to Assess Component And Gate Importance in Fault Tree Analysis," Reliability Engineering and System Safety, 72, pp. 213- 222, 2001. https://doi.org/10.1016/S0951-8320(01)00004-7
  8. S. Epstein, A. Rauzy, "Can we trust PRA," Reliability Engineering and System Safety, 88, pp. 195-205, June 2005. https://doi.org/10.1016/j.ress.2004.07.013
  9. K. A. Reay, J. D. Andrews. "A Fault tree analysis strategy using binary decision diagrams". Reliability Engineering and System Safety, 78, pp.45-56, 2002. https://doi.org/10.1016/S0951-8320(02)00107-2
  10. B. Bollig, I. Wegener. "Improving the variable ordering of OBDDs is NP-complete". IEEE Transactions on Computers. 45, pp.993-1002, 1996. https://doi.org/10.1109/12.537122
  11. S.J. Friedman, K.J. Supowit. Finding the Optimal Variable Ordering for Binary Decision Diagrams. IEEE Transactions on Computers. 39, pp.710-713, 1990. https://doi.org/10.1109/12.53586
  12. M. Bouissou, F. Bruyere, A. Rauzy. "BDD-based fault tree processing: A comparison of variable ordering heuristics". Proceedings of ESREL97, 1997.
  13. L. M. Bartlett, J. D. Andrews. "Selecting an Ordering Heuristic for the Fault Tree to Binary Decision Diagram Conversion Process Using Neural Networks". IEEE Transactions on Reliability, 51, pp. 344-349, 2002. https://doi.org/10.1109/TR.2002.802892
  14. J. Gauthier, X. Leduc, A. Rauzy. "Assessment of large automatically generated fault trees by means of binary decision diagrams". Journal of Risk and Reliability, 221, pp.95-105, 2007.
  15. Y. C. Mo. "Variable ordering to improve BDD analysis of phased-mission systems with multimode failures". IEEE Transactions on Reliability, 2009, 58(1):53-57 https://doi.org/10.1109/TR.2008.2011673
  16. Y. C. Mo. "New insights into the BDD-based reliability analysis of phased-mission systems". IEEE Transactions on Reliability, 58, pp. 667-678, 2009. https://doi.org/10.1109/TR.2009.2026804
  17. A. Rauzy. "Mathematical Foundations of Minimal Cutsets". IEEE Transactions on Reliability, 50, pp 389-396, 2001. https://doi.org/10.1109/24.983400
  18. W.S. Jung, S.H. Han, J.J Ha. "A fast BDD algorithm for large coherent fault trees analysis". Reliability Engineering and System Safety, 83, pp.369-374, 2004. https://doi.org/10.1016/j.ress.2003.10.009
  19. W.S. Jung, S.H. Han, J.E. YANG, "Fast BDD Truncation method for efficient top event probability calculation," Nuclear Engineering and Technology, 40, pp. 571-580, 2008. https://doi.org/10.5516/NET.2008.40.7.571

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