Fault tree conversion to binary decision diagrams

Fault tree conversion to binary decision diagrams

A fault tree analysis strategy using binary decision diagrams

The use of Binary Decision Diagrams (BDDs) in fault tree analysis provides both an accurate and efficient means of analysing a system. There is a problem however, with the conversion process of the fault tree to the BDD. The variable ordering scheme chosen for the construction of the BDD has a crucial effect on its resulting size and previous research has failed to identify any scheme that is c...

An enhanced component connection method for conversion of fault trees to binary decision diagrams

Fault Tree Analysis (FTA) is widely applied to assess the failure probability of industrial systems. Many computer packages are available which are based on conventional Kinetic Tree Theory methods. When dealing with large (possibly non-coherent) fault trees, the limitations of the technique in terms of accuracy of the solutions and the efficiency of the processing time becomes apparent. Over r...

Minimal cutsets-based reduction approach for the use of binary decision diagrams on probabilistic safety assessment fault tree models

Binary decision diagrams (BDDs) are a well-known alternative to the minimal cutsets (MCS) approach to assess Boolean reliability models. While the application of fault tree analysis can be considered to be consolidated, its application to the event trees involved in the probabilistic safety assessment (PSA) studies of the nuclear industry require extended efforts. For many real PSA models the f...

Event-tree analysis using binary decision diagrams

and Conclusions This paper is concerned with the analysis of Event Trees where the branch point event causes are defined using Fault Tree structures. Attention is focussed on the non-trivial situation where there are dependencies amongst the branch point events. The dependencies are due to component failure events featuring in one or more of the fault trees. In these situations it is shown that...