Can we trust PRA?

Abstract The Fault-Tree/Event-Tree method is widely used in industry as the underlying formalism of probabilistic risk assessment. Almost all of the tools available to assess Event-Tree models implement the ‘classical’ assessment technique based on minimal cutsets and the rare event approximation. Binary decision diagrams (BDDs) are an alternative approach, but they were up to now limited to medium size models because of the exponential blow up of the memory requirements. We have designed a set of heuristics, which make it possible to quantify, by means of BDD, all of the sequences of a large Event-Tree model coming from the nuclear industry. For the first time, it was possible to compare results of the classical approach with those of the BDD approach, i.e. with exact results. This article reports this comparison and shows that the minimal cutsets technique gives overestimated results in a significant proportion of cases and underestimated results in some cases as well. Hence, the (indeed provocative) question in the title of this article.

[1]  Rajeev Murgai,et al.  Efficient scheduling techniques for ROBDD construction , 1999, Proceedings Twelfth International Conference on VLSI Design. (Cat. No.PR00013).

[2]  Jaejoo Ha,et al.  A fast BDD algorithm for large coherent fault trees analysis , 2004, Reliab. Eng. Syst. Saf..

[3]  W. E. Vesely,et al.  NEW METHODOLOGY FOR OBTAINING CUT SETS FOR FAULT TREES. , 1972 .

[4]  Beate Bollig,et al.  Improving the Variable Ordering of OBDDs Is NP-Complete , 1996, IEEE Trans. Computers.

[5]  Antoine Rauzy.  Toward an efficient implementation of the MOCUS algorithm , 2003, IEEE Trans. Reliab..

[6]  Nagisa Ishiura,et al.  Shared binary decision diagram with attributed edges for efficient Boolean function manipulation , 1990, 27th ACM/IEEE Design Automation Conference.

[7]  Sarah J. Dunnett,et al.  Event-tree analysis using binary decision diagrams , 2000, IEEE Trans. Reliab..

[8]  M. Cheok,et al.  Use of importance measures in risk-informed regulatory applications , 1998 .

[9]  Marko Cepin.  Analysis of truncation limit in probabilistic safety assessment , 2005, Reliab. Eng. Syst. Saf..

[10]  Emanuele Borgonovo,et al.  A new importance measure for risk-informed decision making , 2001, Reliab. Eng. Syst. Saf..

[11]  Ioannis A. Papazoglou.  Mathematical Foundations of Event Trees , 1998 .

[12]  Antoine Rauzy,et al.  Efficient algorithms to assess component and gate importance in fault tree analysis , 2001, Reliab. Eng. Syst. Saf..

[13]  Antoine Rauzy,et al.  New algorithms for fault trees analysis , 1993 .

[14]  Antoine Rauzy.  Mathematical foundations of minimal cutsets , 2001, IEEE Trans. Reliab..

[15]  Randal E. Bryant,et al.  Efficient implementation of a BDD package , 1991, DAC '90.

[16]  Randal E. Bryant,et al.  Graph-Based Algorithms for Boolean Function Manipulation , 1986, IEEE Transactions on Computers.

[17]  Shin-ichi Minato,et al.  Zero-Suppressed BDDs for Set Manipulation in Combinatorial Problems , 1993, 30th ACM/IEEE Design Automation Conference.

[18]  Randal E. Bryant,et al.  Symbolic Boolean manipulation with ordered binary-decision diagrams , 1992, CSUR.

[19]  藤田 昌宏,et al.  Evaluation and Improvements of Boolean Comparison Method Based on Binary Decision Diagrams , 1988 .

[20]  R. Rudell.  Dynamic variable ordering for ordered binary decision diagrams , 1993, Proceedings of 1993 International Conference on Computer Aided Design (ICCAD).

[21]  Hiromitsu Kumamoto,et al.  Probabilistic Risk Assessment and Management for Engineers and Scientists , 1996 .

[22]  Masahiro Fujita,et al.  Evaluation and improvement of Boolean comparison method based on binary decision diagrams , 1988, [1988] IEEE International Conference on Computer-Aided Design (ICCAD-89) Digest of Technical Papers.